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CVE-2026-48818 (GCVE-0-2026-48818)
Vulnerability from cvelistv5 – Published: 2026-06-17 17:50 – Updated: 2026-06-17 19:31- CWE-918 - Server-Side Request Forgery (SSRF)
| URL | Tags |
|---|---|
| https://github.com/Kludex/starlette/security/advi… | x_refsource_CONFIRM |
| https://github.com/Kludex/starlette/pull/3287 | x_refsource_MISC |
| https://github.com/Kludex/starlette/commit/fd5316… | x_refsource_MISC |
| https://github.com/Kludex/starlette/releases/tag/1.1.0 | x_refsource_MISC |
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FKIE_CVE-2026-48818
Vulnerability from fkie_nvd - Published: 2026-06-17 19:18 - Updated: 2026-06-17 20:17| Vendor | Product | Version |
|---|
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GHSA-WQP7-X3PW-XC5R
Vulnerability from github – Published: 2026-06-15 20:16 – Updated: 2026-06-15 20:16Summary
When serving static files on Windows, StaticFiles resolves the requested path with os.path.realpath. If a UNC path (such as \\attacker.com\share) reaches the resolver, realpath causes the process to open a connection to the remote host over SMB (port 445). This is a server-side request forgery (SSRF) that leaks the service account's NTLMv2 credentials to the attacker-controlled host, which can then be cracked offline or relayed to other hosts.
Details
StaticFiles.lookup_path() joins the requested path onto the served directory and calls os.path.realpath on the result before checking containment with os.path.commonpath. On Windows, a UNC path is absolute, so os.path.join discards the served directory and realpath resolves the bare UNC path, triggering the outbound SMB connection and NTLM authentication before the containment check rejects the path. The HTTP response is a benign 404, but the credential disclosure has already happened. POSIX systems are not affected.
This only affects the default configuration (follow_symlink=False), which uses os.path.realpath. The follow_symlink=True branch uses os.path.abspath, which performs no I/O.
Impact
Applications running on Windows that serve files with StaticFiles (directly, or via a framework built on Starlette such as FastAPI) in the default configuration are affected. StaticFiles is typically unauthenticated, so any client can trigger the SMB connection and leak the service account's NTLMv2 hash. A secondary impact is discovering internal hosts reachable over SMB by timing responses for valid versus invalid addresses.
Mitigation
Applications not running on Windows are not affected. On Windows, serving static files through a dedicated web server (such as nginx or IIS) instead of StaticFiles avoids the issue. Blocking outbound SMB (port 445) from the application host prevents the credential disclosure even if a UNC path is resolved.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "starlette"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "1.1.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-48818"
],
"database_specific": {
"cwe_ids": [
"CWE-918"
],
"github_reviewed": true,
"github_reviewed_at": "2026-06-15T20:16:30Z",
"nvd_published_at": null,
"severity": "HIGH"
},
"details": "### Summary\n\nWhen serving static files on Windows, `StaticFiles` resolves the requested path with [`os.path.realpath`](https://docs.python.org/3/library/os.path.html#os.path.realpath). If a UNC path (such as `\\\\attacker.com\\share`) reaches the resolver, `realpath` causes the process to open a connection to the remote host over SMB (port 445). This is a server-side request forgery (SSRF) that leaks the service account\u0027s NTLMv2 credentials to the attacker-controlled host, which can then be cracked offline or relayed to other hosts.\n\n### Details\n\n`StaticFiles.lookup_path()` joins the requested path onto the served directory and calls [`os.path.realpath`](https://docs.python.org/3/library/os.path.html#os.path.realpath) on the result before checking containment with [`os.path.commonpath`](https://docs.python.org/3/library/os.path.html#os.path.commonpath). On Windows, a UNC path is absolute, so [`os.path.join`](https://docs.python.org/3/library/os.path.html#os.path.join) discards the served directory and `realpath` resolves the bare UNC path, triggering the outbound SMB connection and NTLM authentication before the containment check rejects the path. The HTTP response is a benign 404, but the credential disclosure has already happened. POSIX systems are not affected.\n\nThis only affects the default configuration (`follow_symlink=False`), which uses [`os.path.realpath`](https://docs.python.org/3/library/os.path.html#os.path.realpath). The `follow_symlink=True` branch uses [`os.path.abspath`](https://docs.python.org/3/library/os.path.html#os.path.abspath), which performs no I/O.\n\n### Impact\n\nApplications running on Windows that serve files with `StaticFiles` (directly, or via a framework built on Starlette such as FastAPI) in the default configuration are affected. `StaticFiles` is typically unauthenticated, so any client can trigger the SMB connection and leak the service account\u0027s NTLMv2 hash. A secondary impact is discovering internal hosts reachable over SMB by timing responses for valid versus invalid addresses.\n\n### Mitigation\n\nApplications not running on Windows are not affected. On Windows, serving static files through a dedicated web server (such as nginx or IIS) instead of `StaticFiles` avoids the issue. Blocking outbound SMB (port 445) from the application host prevents the credential disclosure even if a UNC path is resolved.",
"id": "GHSA-wqp7-x3pw-xc5r",
"modified": "2026-06-15T20:16:30Z",
"published": "2026-06-15T20:16:30Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/Kludex/starlette/security/advisories/GHSA-wqp7-x3pw-xc5r"
},
{
"type": "PACKAGE",
"url": "https://github.com/Kludex/starlette"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
"type": "CVSS_V3"
}
],
"summary": "Starlette: SSRF and NTLM credential theft via UNC paths in StaticFiles on Windows"
}
RHSA-2026:30087
Vulnerability from csaf_redhat - Published: 2026-06-25 19:29 - Updated: 2026-06-27 08:31A vulnerability in vLLM allows attackers to supply malicious serialized prompt-embedding tensors that are deserialized using torch.load() without validation. Due to PyTorch 2.8.0 disabling sparse-tensor integrity checks by default, a crafted tensor can bypass bounds checks and cause an out-of-bounds write during to_dense(), leading to a crash (DoS) and potentially remote code execution on the vLLM server.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
Vendor Fix
fix
Workaround
|
A remote code execution vulnerability has been identified in vLLM. An attacker can exploit a weakness in the model loading process to silently fetch and run unauthorized, malicious Python code on the host system. This happens because the engine mistakenly executes code from a remote repository referenced in a model's configuration, even when explicit security measures are set to prevent it.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
Vendor Fix
fix
Workaround
|
A flaw was found in the libtiff library. A remote attacker could exploit a signed integer overflow vulnerability in the putcontig8bitYCbCr44tile function by providing a specially crafted TIFF file. This flaw can lead to an out-of-bounds heap write due to incorrect memory pointer calculations, potentially causing a denial of service (application crash) or arbitrary code execution.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
Vendor Fix
fix
Workaround
|
A flaw was found in the Python webbrowser.open() API. If a specially crafted URL containing "%action" is processed, an attacker could bypass a previous mitigation for CVE-2026-4519. This bypass allows for command injection into the underlying shell, potentially leading to arbitrary code execution.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
Vendor Fix
fix
Workaround
|
A flaw was found in libcap. A local unprivileged user can exploit a Time-of-check-to-time-of-use (TOCTOU) race condition in the `cap_set_file()` function. This allows an attacker with write access to a parent directory to redirect file capability updates to an attacker-controlled file. By doing so, capabilities can be injected into or stripped from unintended executables, leading to privilege escalation.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
Vendor Fix
fix
Workaround
|
A flaw was found in Python's decompression modules, including `lzma.LZMADecompressor`, `bz2.BZ2Decompressor`, and `gzip.GzipFile`. This vulnerability, a use-after-free, can occur if a program attempts to re-use a decompression object after a memory allocation error, especially when the system is experiencing high memory usage. Exploitation of this flaw could potentially allow an attacker to execute arbitrary code or access sensitive data. The vulnerability is only present if the program re-uses decompressor instances across multiple decompression calls even after a `MemoryError` is raised during decompression. Using the helper functions to one-shot decompress data such as `lzma.decompress()`, `bz2.decompress()`, `gzip.decompress()`, and `zlib.decompress()` are not affected as a new decompressor instance is used per call. If the decompressor instance is not re-used after an error condition, this usage is similarly not vulnerable.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
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| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
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| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
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A flaw was found in Poppler's Splash backend. A remote attacker could exploit this vulnerability by crafting a malicious PDF file that, when rendered, triggers an integer overflow in the `tilingPatternFill` function. This overflow leads to an undersized heap memory allocation, allowing a subsequent out-of-bounds write. Successful exploitation could result in arbitrary code execution, information disclosure, or denial of service within the context of the application processing the PDF.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
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| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
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| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
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A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). A remote attacker can exploit this vulnerability by sending a specially crafted 1x1 pixel image to a vLLM engine serving multimodal models that use the Idefics3 vision model implementation. This leads to a tensor dimension mismatch, causing an unhandled runtime error and resulting in complete server termination, effectively a Denial of Service (DoS).
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
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A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). A remote attacker can exploit this vulnerability by sending a specially crafted video URL to vLLM's multimodal endpoint. This action causes vLLM to leak a heap memory address, significantly reducing the effectiveness of Address Space Layout Randomization (ASLR). This information disclosure can then be chained with a heap overflow vulnerability to achieve remote code execution.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
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| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
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| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
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A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). This vulnerability allows a remote attacker to achieve arbitrary code execution on the vLLM host during model loading. This occurs because vLLM loads Hugging Face `auto_map` dynamic modules without properly validating the `trust_remote_code` setting. By influencing the model repository or path, an attacker can execute malicious Python code at server startup, even before any API requests are handled.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
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| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
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A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). A Server-Side Request Forgery (SSRF) vulnerability exists in the MediaConnector class, specifically within the load_from_url and load_from_url_async methods. An attacker can exploit differing interpretations of backslashes by Python parsing libraries used for host restrictions to bypass these restrictions. This allows the attacker to force the vLLM server to make arbitrary requests to internal network resources, potentially leading to information disclosure, denial of service, or unauthorized access within containerized environments.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
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| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
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A flaw was found in OpenEXR, an image storage format for the motion picture industry. A remote attacker could exploit an integer overflow vulnerability in the `internal_exr_undo_piz()` function by providing a specially crafted EXR file. This flaw leads to out-of-bounds reads and writes, which may allow for arbitrary code execution or sensitive information disclosure.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
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A flaw was found in Vim. A modeline is used to set specific editor options directly from a text file. However, the `complete`, `guitabtooltip`, `printheader` options and the `mapset` function lack proper security checks, allowing an attacker to bypass restrictions and cause arbitrary OS command execution.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
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| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
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A flaw was found in OpenSSH. When the `scp` command is used by a root user to download a file with the legacy protocol option (`-O`) and without preserving original file permissions (`-p`), the downloaded file can be installed with elevated privileges (setuid or setgid). This unexpected behavior could allow a malicious file to execute with higher permissions than intended, posing a security risk through potential privilege escalation.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
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A flaw was found in the libsndfile library. An integer overflow in the IMA ADPCM codec can occur when a specially crafted WAV audio file is processed, specifically with malicious samplesperblock and blocks values. This can lead to a heap-based buffer overflow, causing a crash to the application linked to the library and memory corruption.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
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A flaw was found in jq, a command line JSON processor, specifically in the libjq API. Parsing a malformed JSON input from a non-NUL-terminated buffer using the `jv_parse_sized` function can cause an out-of-bounds read, resulting in an application crash and a possible memory disclosure within the error message generated by the parser.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
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A flaw was found in jq, a command-line JSON processor. A remote attacker could exploit this vulnerability by providing a specially crafted JSON object. This object leverages a weakness in jq's hashing algorithm, which uses a hardcoded, publicly known seed. By crafting the JSON object to cause hash collisions, an attacker can degrade the performance of JSON object hash table operations, leading to significant CPU exhaustion and a denial of service (DoS) for systems processing the malicious JSON data.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
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A flaw was found in urllib3, an HTTP client library for Python. When using the low-level API via `ProxyManager.connection_from_url().urlopen()` with `assert_same_host=False`, cross-origin redirects can still forward sensitive headers. This could allow a remote attacker to gain unauthorized access to sensitive information.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
Vendor Fix
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
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A flaw was found in urllib3, an HTTP client library for Python. This vulnerability allows a remote attacker to cause excessive resource consumption, such as high CPU usage and massive memory allocation, on the client side. This occurs when urllib3 attempts to decompress an entire HTTP response, even if only a partial read was requested, or when draining the connection after a partial decompression. This can lead to a Denial of Service (DoS) condition.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
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A flaw was found in Starlette, a lightweight ASGI framework. On Windows systems, the StaticFiles component is vulnerable to Server-Side Request Forgery (SSRF). A remote attacker can exploit this by providing a specially crafted Universal Naming Convention (UNC) path, which causes the system to initiate an outbound Server Message Block (SMB) connection. This action can expose the service account's NTLMv2 credentials, potentially leading to information disclosure or further attacks.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64 | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le | — |
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{
"document": {
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"text": "Critical"
},
"category": "csaf_security_advisory",
"csaf_version": "2.0",
"distribution": {
"text": "Copyright \u00a9 Red Hat, Inc. All rights reserved.",
"tlp": {
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"notes": [
{
"category": "summary",
"text": "Red Hat AI Inference Server 3.3.5 (Spyre) is now available.",
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{
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"text": "Red Hat\u00ae AI Inference Server",
"title": "Details"
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{
"category": "legal_disclaimer",
"text": "This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original.",
"title": "Terms of Use"
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"contact_details": "https://access.redhat.com/security/team/contact/",
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"name": "Red Hat Product Security",
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"references": [
{
"category": "self",
"summary": "https://access.redhat.com/errata/RHSA-2026:30087",
"url": "https://access.redhat.com/errata/RHSA-2026:30087"
},
{
"category": "external",
"summary": "https://access.redhat.com/security/cve/CVE-2025-62164",
"url": "https://access.redhat.com/security/cve/CVE-2025-62164"
},
{
"category": "external",
"summary": "https://access.redhat.com/security/cve/CVE-2025-66448",
"url": "https://access.redhat.com/security/cve/CVE-2025-66448"
},
{
"category": "external",
"summary": "https://access.redhat.com/security/cve/CVE-2026-10118",
"url": "https://access.redhat.com/security/cve/CVE-2026-10118"
},
{
"category": "external",
"summary": "https://access.redhat.com/security/cve/CVE-2026-22773",
"url": "https://access.redhat.com/security/cve/CVE-2026-22773"
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{
"category": "external",
"summary": "https://access.redhat.com/security/cve/CVE-2026-22778",
"url": "https://access.redhat.com/security/cve/CVE-2026-22778"
},
{
"category": "external",
"summary": "https://access.redhat.com/security/cve/CVE-2026-22807",
"url": "https://access.redhat.com/security/cve/CVE-2026-22807"
},
{
"category": "external",
"summary": "https://access.redhat.com/security/cve/CVE-2026-24779",
"url": "https://access.redhat.com/security/cve/CVE-2026-24779"
},
{
"category": "external",
"summary": "https://access.redhat.com/security/cve/CVE-2026-34588",
"url": "https://access.redhat.com/security/cve/CVE-2026-34588"
},
{
"category": "external",
"summary": "https://access.redhat.com/security/cve/CVE-2026-34982",
"url": "https://access.redhat.com/security/cve/CVE-2026-34982"
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{
"category": "external",
"summary": "https://access.redhat.com/security/cve/CVE-2026-35385",
"url": "https://access.redhat.com/security/cve/CVE-2026-35385"
},
{
"category": "external",
"summary": "https://access.redhat.com/security/cve/CVE-2026-37555",
"url": "https://access.redhat.com/security/cve/CVE-2026-37555"
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{
"category": "external",
"summary": "https://access.redhat.com/security/cve/CVE-2026-39979",
"url": "https://access.redhat.com/security/cve/CVE-2026-39979"
},
{
"category": "external",
"summary": "https://access.redhat.com/security/cve/CVE-2026-40164",
"url": "https://access.redhat.com/security/cve/CVE-2026-40164"
},
{
"category": "external",
"summary": "https://access.redhat.com/security/cve/CVE-2026-44431",
"url": "https://access.redhat.com/security/cve/CVE-2026-44431"
},
{
"category": "external",
"summary": "https://access.redhat.com/security/cve/CVE-2026-44432",
"url": "https://access.redhat.com/security/cve/CVE-2026-44432"
},
{
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"title": "Vulnerability description"
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},
{
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"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"title": "Vulnerability description"
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"text": "vllm: vLLM: Denial of Service via specially crafted image in multimodal model serving",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This vulnerability is rated Moderate for Red Hat products. A remote attacker can trigger a denial of service in vLLM engines serving multimodal models that use the Idefics3 vision model by sending a specially crafted image, leading to complete server termination. This affects Red Hat AI Inference Server and Red Hat OpenShift AI (RHOAI) when configured with the vulnerable vLLM versions.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"title": "vllm: vLLM: Denial of Service via specially crafted image in multimodal model serving"
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{
"cve": "CVE-2026-22778",
"cwe": {
"id": "CWE-209",
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"ids": [
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"title": "Vulnerability description"
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"text": "vLLM: vLLM: Remote code execution via invalid image processing in the multimodal endpoint.",
"title": "Vulnerability summary"
},
{
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"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"url": "https://www.cve.org/CVERecord?id=CVE-2026-22778"
},
{
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"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-22778"
},
{
"category": "external",
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"summary": "https://github.com/vllm-project/vllm/pull/32319",
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"summary": "https://github.com/vllm-project/vllm/security/advisories/GHSA-4r2x-xpjr-7cvv",
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"date": "2026-06-25T19:29:10+00:00",
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"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
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"details": "Critical"
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"cve": "CVE-2026-22807",
"cwe": {
"id": "CWE-94",
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{
"category": "summary",
"text": "vLLM: vLLM: Arbitrary code execution via untrusted model loading",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This vulnerability is rated Important for Red Hat as vLLM, an inference and serving engine for large language models, is vulnerable to arbitrary code execution. An attacker influencing the model repository or path can execute malicious Python code during server startup, affecting vLLM versions 0.10.1 through 0.13.x.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
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"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-22807"
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"date": "2026-06-25T19:29:10+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30087",
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"baseScore": 8.8,
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"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
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"details": "Important"
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"title": "vLLM: vLLM: Arbitrary code execution via untrusted model loading"
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{
"cve": "CVE-2026-24779",
"cwe": {
"id": "CWE-918",
"name": "Server-Side Request Forgery (SSRF)"
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"discovery_date": "2026-01-27T23:00:53.998772+00:00",
"ids": [
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"system_name": "Red Hat Bugzilla ID",
"text": "2433624"
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"title": "Vulnerability description"
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{
"category": "summary",
"text": "vLLM: vLLM: Server-Side Request Forgery allows internal network access",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This IMPORTANT Server-Side Request Forgery (SSRF) vulnerability in vLLM\u0027s `MediaConnector` allows an attacker to bypass host restrictions when processing user-provided URLs. This enables the vLLM server to be coerced into making arbitrary requests to internal network resources. This is critical in containerized deployments, including Red Hat AI Inference Server, Red Hat Enterprise Linux AI, and Red Hat OpenShift AI, where it could facilitate internal network reconnaissance and unauthorized access to other services.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
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"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-24779"
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"name": "Integer Overflow or Wraparound"
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"discovery_date": "2026-04-06T16:02:38.673068+00:00",
"ids": [
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"text": "A flaw was found in OpenEXR, an image storage format for the motion picture industry. A remote attacker could exploit an integer overflow vulnerability in the `internal_exr_undo_piz()` function by providing a specially crafted EXR file. This flaw leads to out-of-bounds reads and writes, which may allow for arbitrary code execution or sensitive information disclosure.",
"title": "Vulnerability description"
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"title": "Vulnerability summary"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"product_ids": [
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],
"restart_required": {
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},
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}
],
"scores": [
{
"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
"products": [
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"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le"
]
}
],
"threats": [
{
"category": "impact",
"details": "Important"
}
],
"title": "urllib3: urllib3: Denial of Service due to excessive HTTP response decompression"
},
{
"cve": "CVE-2026-48818",
"cwe": {
"id": "CWE-918",
"name": "Server-Side Request Forgery (SSRF)"
},
"discovery_date": "2026-06-17T19:03:44.998691+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2490020"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in Starlette, a lightweight ASGI framework. On Windows systems, the StaticFiles component is vulnerable to Server-Side Request Forgery (SSRF). A remote attacker can exploit this by providing a specially crafted Universal Naming Convention (UNC) path, which causes the system to initiate an outbound Server Message Block (SMB) connection. This action can expose the service account\u0027s NTLMv2 credentials, potentially leading to information disclosure or further attacks.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "starlette: Starlette: SSRF and NTLM credential theft via UNC paths in StaticFiles on Windows",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This Important flaw in Starlette\u0027s StaticFiles component, which allows for NTLMv2 credential theft via specially crafted UNC paths, does not affect Red Hat products. The vulnerability is specific to Windows operating systems, and the vulnerable code is not present in Red Hat\u0027s supported configurations.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le"
]
},
"references": [
{
"category": "self",
"summary": "Canonical URL",
"url": "https://access.redhat.com/security/cve/CVE-2026-48818"
},
{
"category": "external",
"summary": "RHBZ#2490020",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2490020"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-48818",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-48818"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-48818",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-48818"
},
{
"category": "external",
"summary": "https://github.com/Kludex/starlette/commit/fd53168a7767b6b55ba5af787fd88f49e33cabc5",
"url": "https://github.com/Kludex/starlette/commit/fd53168a7767b6b55ba5af787fd88f49e33cabc5"
},
{
"category": "external",
"summary": "https://github.com/Kludex/starlette/pull/3287",
"url": "https://github.com/Kludex/starlette/pull/3287"
},
{
"category": "external",
"summary": "https://github.com/Kludex/starlette/releases/tag/1.1.0",
"url": "https://github.com/Kludex/starlette/releases/tag/1.1.0"
},
{
"category": "external",
"summary": "https://github.com/Kludex/starlette/security/advisories/GHSA-wqp7-x3pw-xc5r",
"url": "https://github.com/Kludex/starlette/security/advisories/GHSA-wqp7-x3pw-xc5r"
}
],
"release_date": "2026-06-17T17:50:12.399000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-06-25T19:29:10+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30087",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le"
],
"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:30087"
},
{
"category": "workaround",
"details": "Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability.",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le"
]
}
],
"scores": [
{
"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
"version": "3.1"
},
"products": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:681d191e22994e4da2d4844219e2401ee363d4b3524cd19bb00076dce685a36a_s390x",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:906987407c1ed10139dadc5f8aef64584f407a6017467fce726e2e9c42d9f9c8_amd64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-spyre-rhel9@sha256:9c8187509c26e824143f51f9522d7b6457f3aea33e5f7983bb203e4bb231473d_ppc64le"
]
}
],
"threats": [
{
"category": "impact",
"details": "Important"
}
],
"title": "starlette: Starlette: SSRF and NTLM credential theft via UNC paths in StaticFiles on Windows"
}
]
}
RHSA-2026:30088
Vulnerability from csaf_redhat - Published: 2026-06-25 19:30 - Updated: 2026-06-27 08:55A flaw was found in the libtiff library. A remote attacker could exploit a signed integer overflow vulnerability in the putcontig8bitYCbCr44tile function by providing a specially crafted TIFF file. This flaw can lead to an out-of-bounds heap write due to incorrect memory pointer calculations, potentially causing a denial of service (application crash) or arbitrary code execution.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in the Python webbrowser.open() API. If a specially crafted URL containing "%action" is processed, an attacker could bypass a previous mitigation for CVE-2026-4519. This bypass allows for command injection into the underlying shell, potentially leading to arbitrary code execution.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in libcap. A local unprivileged user can exploit a Time-of-check-to-time-of-use (TOCTOU) race condition in the `cap_set_file()` function. This allows an attacker with write access to a parent directory to redirect file capability updates to an attacker-controlled file. By doing so, capabilities can be injected into or stripped from unintended executables, leading to privilege escalation.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in Python's decompression modules, including `lzma.LZMADecompressor`, `bz2.BZ2Decompressor`, and `gzip.GzipFile`. This vulnerability, a use-after-free, can occur if a program attempts to re-use a decompression object after a memory allocation error, especially when the system is experiencing high memory usage. Exploitation of this flaw could potentially allow an attacker to execute arbitrary code or access sensitive data. The vulnerability is only present if the program re-uses decompressor instances across multiple decompression calls even after a `MemoryError` is raised during decompression. Using the helper functions to one-shot decompress data such as `lzma.decompress()`, `bz2.decompress()`, `gzip.decompress()`, and `zlib.decompress()` are not affected as a new decompressor instance is used per call. If the decompressor instance is not re-used after an error condition, this usage is similarly not vulnerable.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in Poppler's Splash backend. A remote attacker could exploit this vulnerability by crafting a malicious PDF file that, when rendered, triggers an integer overflow in the `tilingPatternFill` function. This overflow leads to an undersized heap memory allocation, allowing a subsequent out-of-bounds write. Successful exploitation could result in arbitrary code execution, information disclosure, or denial of service within the context of the application processing the PDF.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). A remote attacker can exploit this vulnerability by sending a specially crafted video URL to vLLM's multimodal endpoint. This action causes vLLM to leak a heap memory address, significantly reducing the effectiveness of Address Space Layout Randomization (ASLR). This information disclosure can then be chained with a heap overflow vulnerability to achieve remote code execution.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). This vulnerability allows a remote attacker to achieve arbitrary code execution on the vLLM host during model loading. This occurs because vLLM loads Hugging Face `auto_map` dynamic modules without properly validating the `trust_remote_code` setting. By influencing the model repository or path, an attacker can execute malicious Python code at server startup, even before any API requests are handled.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in pyasn1, a generic ASN.1 library for Python. A remote attacker could exploit this vulnerability by sending a specially crafted RELATIVE-OID with excessive continuation octets. This input validation vulnerability leads to memory exhaustion, resulting in a Denial of Service (DoS) for the affected system.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
|
A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). A Server-Side Request Forgery (SSRF) vulnerability exists in the MediaConnector class, specifically within the load_from_url and load_from_url_async methods. An attacker can exploit differing interpretations of backslashes by Python parsing libraries used for host restrictions to bypass these restrictions. This allows the attacker to force the vLLM server to make arbitrary requests to internal network resources, potentially leading to information disclosure, denial of service, or unauthorized access within containerized environments.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in OpenEXR, an image storage format for the motion picture industry. A remote attacker could exploit an integer overflow vulnerability in the `internal_exr_undo_piz()` function by providing a specially crafted EXR file. This flaw leads to out-of-bounds reads and writes, which may allow for arbitrary code execution or sensitive information disclosure.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in Vim. A modeline is used to set specific editor options directly from a text file. However, the `complete`, `guitabtooltip`, `printheader` options and the `mapset` function lack proper security checks, allowing an attacker to bypass restrictions and cause arbitrary OS command execution.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in OpenSSH. When the `scp` command is used by a root user to download a file with the legacy protocol option (`-O`) and without preserving original file permissions (`-p`), the downloaded file can be installed with elevated privileges (setuid or setgid). This unexpected behavior could allow a malicious file to execute with higher permissions than intended, posing a security risk through potential privilege escalation.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in Sudo. A local user could exploit a failure in the setuid, setgid, or setgroups calls, which are used to drop privileges before running the mailer. This oversight allows for privilege escalation, enabling the user to gain elevated access on the system.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
|
A flaw was found in the libsndfile library. An integer overflow in the IMA ADPCM codec can occur when a specially crafted WAV audio file is processed, specifically with malicious samplesperblock and blocks values. This can lead to a heap-based buffer overflow, causing a crash to the application linked to the library and memory corruption.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in the cryptography library. This vulnerability occurs when a non-contiguous buffer is passed to certain application programming interfaces (APIs) that accept Python buffers, such as Hash.update(). A remote attacker could exploit this to cause a buffer overflow, potentially leading to a denial of service.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in jq, a command line JSON processor, specifically in the libjq API. Parsing a malformed JSON input from a non-NUL-terminated buffer using the `jv_parse_sized` function can cause an out-of-bounds read, resulting in an application crash and a possible memory disclosure within the error message generated by the parser.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in jq, a command-line JSON processor. A remote attacker could exploit this vulnerability by providing a specially crafted JSON object. This object leverages a weakness in jq's hashing algorithm, which uses a hardcoded, publicly known seed. By crafting the JSON object to cause hash collisions, an attacker can degrade the performance of JSON object hash table operations, leading to significant CPU exhaustion and a denial of service (DoS) for systems processing the malicious JSON data.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in urllib3, an HTTP client library for Python. When using the low-level API via `ProxyManager.connection_from_url().urlopen()` with `assert_same_host=False`, cross-origin redirects can still forward sensitive headers. This could allow a remote attacker to gain unauthorized access to sensitive information.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
|
A flaw was found in urllib3, an HTTP client library for Python. This vulnerability allows a remote attacker to cause excessive resource consumption, such as high CPU usage and massive memory allocation, on the client side. This occurs when urllib3 attempts to decompress an entire HTTP response, even if only a partial read was requested, or when draining the connection after a partial decompression. This can lead to a Denial of Service (DoS) condition.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
|
A flaw was found in PyJWT, a Python library for JSON Web Token (JWT) implementation. When decoding JWTs, the library fails to validate the use of JSON Web Keys (JWK) in the HMAC algorithm while also supporting asymmetric algorithms. This allows a remote attacker to use the issuer's public key as the secret key for the HMAC algorithm, leading to the ability to forge JWTs. This vulnerability can result in authentication bypass or unauthorized access.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
|
A flaw was found in Starlette, a lightweight ASGI (Asynchronous Server Gateway Interface) framework. A remote attacker could exploit this vulnerability by sending a specially crafted HTTP `Host` request header. This malformed header could cause the `request.url` to be incorrectly reconstructed, leading to a discrepancy with the actual requested path. Consequently, security restrictions enforced by middleware and endpoints that rely on `request.url` for validation could be bypassed, potentially allowing unauthorized access or actions.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). This vulnerability, residing in ASGI web servers and Starlette's trust in them, allows an attacker to bypass the OpenAI API Authentication Middleware. This bypass enables unauthorized access to the API without requiring the configured VLLM_API_KEY or --api-key, leading to critical unauthorized operations.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in Starlette, a lightweight ASGI framework. On Windows systems, the StaticFiles component is vulnerable to Server-Side Request Forgery (SSRF). A remote attacker can exploit this by providing a specially crafted Universal Naming Convention (UNC) path, which causes the system to initiate an outbound Server Message Block (SMB) connection. This action can expose the service account's NTLMv2 credentials, potentially leading to information disclosure or further attacks.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64 | — |
Vendor Fix
fix
Workaround
|
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"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-4878",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-4878"
},
{
"category": "external",
"summary": "https://bugzilla.redhat.com/show_bug.cgi?id=2447554",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2447554"
}
],
"release_date": "2026-04-06T00:00:00+00:00",
"remediations": [
{
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"date": "2026-06-25T19:30:53+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30088",
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"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
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{
"category": "workaround",
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{
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"attackComplexity": "HIGH",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 6.7,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H",
"version": "3.1"
},
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]
}
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"threats": [
{
"category": "impact",
"details": "Important"
}
],
"title": "libcap: libcap: Privilege escalation via TOCTOU race condition in cap_set_file()"
},
{
"cve": "CVE-2026-6100",
"cwe": {
"id": "CWE-825",
"name": "Expired Pointer Dereference"
},
"discovery_date": "2026-04-13T18:01:31.970255+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2457932"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in Python\u0027s decompression modules, including `lzma.LZMADecompressor`, `bz2.BZ2Decompressor`, and `gzip.GzipFile`. This vulnerability, a use-after-free, can occur if a program attempts to re-use a decompression object after a memory allocation error, especially when the system is experiencing high memory usage. Exploitation of this flaw could potentially allow an attacker to execute arbitrary code or access sensitive data. The vulnerability is only present if the program re-uses decompressor instances across multiple decompression calls even after a `MemoryError` is raised during decompression. Using the helper functions to one-shot decompress data such as `lzma.decompress()`, `bz2.decompress()`, `gzip.decompress()`, and `zlib.decompress()` are not affected as a new decompressor instance is used per call. If the decompressor instance is not re-used after an error condition, this usage is similarly not vulnerable.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "python: Python: Arbitrary code execution or information disclosure via use-after-free in decompression modules",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "The severity of this flaw is somewhat mitigated on Red Hat platforms. By default processes are not executed with root user privilege and are limited in their scope which in turn limits the impact of this flaw.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
]
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"references": [
{
"category": "self",
"summary": "Canonical URL",
"url": "https://access.redhat.com/security/cve/CVE-2026-6100"
},
{
"category": "external",
"summary": "RHBZ#2457932",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2457932"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-6100",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-6100"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-6100",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-6100"
},
{
"category": "external",
"summary": "https://github.com/python/cpython/commit/6a5f79c8d7bbf22b083b240910c7a8781a59437d",
"url": "https://github.com/python/cpython/commit/6a5f79c8d7bbf22b083b240910c7a8781a59437d"
},
{
"category": "external",
"summary": "https://github.com/python/cpython/commit/8fc66aef6d7b3ae58f43f5c66f9366cc8cbbfcd2",
"url": "https://github.com/python/cpython/commit/8fc66aef6d7b3ae58f43f5c66f9366cc8cbbfcd2"
},
{
"category": "external",
"summary": "https://github.com/python/cpython/commit/c3cf71c3366fe49acb776a639405c0eea6169c20",
"url": "https://github.com/python/cpython/commit/c3cf71c3366fe49acb776a639405c0eea6169c20"
},
{
"category": "external",
"summary": "https://github.com/python/cpython/issues/148395",
"url": "https://github.com/python/cpython/issues/148395"
},
{
"category": "external",
"summary": "https://github.com/python/cpython/pull/148396",
"url": "https://github.com/python/cpython/pull/148396"
},
{
"category": "external",
"summary": "https://mail.python.org/archives/list/security-announce@python.org/thread/HTWB2Z6KT5QQX4RYEZAFININDHNOSIF3/",
"url": "https://mail.python.org/archives/list/security-announce@python.org/thread/HTWB2Z6KT5QQX4RYEZAFININDHNOSIF3/"
}
],
"release_date": "2026-04-13T17:15:47.606000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-06-25T19:30:53+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30088",
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"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:30088"
},
{
"category": "workaround",
"details": "Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability.",
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],
"scores": [
{
"cvss_v3": {
"attackComplexity": "HIGH",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.1,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"products": [
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]
}
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"threats": [
{
"category": "impact",
"details": "Important"
}
],
"title": "python: Python: Arbitrary code execution or information disclosure via use-after-free in decompression modules"
},
{
"acknowledgments": [
{
"names": [
"AISLE Research"
],
"summary": "This issue was discovered by Red Hat."
}
],
"cve": "CVE-2026-10118",
"cwe": {
"id": "CWE-190",
"name": "Integer Overflow or Wraparound"
},
"discovery_date": "2026-04-21T23:20:23+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2460428"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in Poppler\u0027s Splash backend. A remote attacker could exploit this vulnerability by crafting a malicious PDF file that, when rendered, triggers an integer overflow in the `tilingPatternFill` function. This overflow leads to an undersized heap memory allocation, allowing a subsequent out-of-bounds write. Successful exploitation could result in arbitrary code execution, information disclosure, or denial of service within the context of the application processing the PDF.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "poppler: Integer overflow in Poppler SplashOutputDev::tilingPatternFill leads to heap buffer overflow via unchecked dimension multiplication",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This is an Important heap-based memory corruption flaw in Poppler\u0027s Splash backend. Processing a specially crafted PDF document can lead to an integer overflow, resulting in an undersized heap allocation and a subsequent out-of-bounds write. This could allow an attacker to achieve arbitrary code execution, disclose sensitive information, or cause a denial of service within the context of the application rendering the PDF. To successfully exploit this vulnerability the attacker needs to be able to supply the maliciously crafted PDF file to the application consuming poppler or trick the user to process the PDF file using the Poppler\u0027s backend.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
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"references": [
{
"category": "self",
"summary": "Canonical URL",
"url": "https://access.redhat.com/security/cve/CVE-2026-10118"
},
{
"category": "external",
"summary": "RHBZ#2460428",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2460428"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-10118",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-10118"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-10118",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-10118"
},
{
"category": "external",
"summary": "https://gitlab.freedesktop.org/poppler/poppler/-/work_items/1715",
"url": "https://gitlab.freedesktop.org/poppler/poppler/-/work_items/1715"
}
],
"release_date": "2026-06-01T15:25:35.578000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-06-25T19:30:53+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30088",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
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"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:30088"
},
{
"category": "workaround",
"details": "To mitigate this issue, users should avoid opening untrusted or suspicious PDF documents with applications that utilize the Poppler library for rendering. Limiting exposure to untrusted content can reduce the risk of exploitation.",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
]
}
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"scores": [
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"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 7.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"products": [
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"details": "Important"
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"title": "poppler: Integer overflow in Poppler SplashOutputDev::tilingPatternFill leads to heap buffer overflow via unchecked dimension multiplication"
},
{
"cve": "CVE-2026-22778",
"cwe": {
"id": "CWE-209",
"name": "Generation of Error Message Containing Sensitive Information"
},
"discovery_date": "2026-02-03T00:01:43.512265+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2436113"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). A remote attacker can exploit this vulnerability by sending a specially crafted video URL to vLLM\u0027s multimodal endpoint. This action causes vLLM to leak a heap memory address, significantly reducing the effectiveness of Address Space Layout Randomization (ASLR). This information disclosure can then be chained with a heap overflow vulnerability to achieve remote code execution.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "vLLM: vLLM: Remote code execution via invalid image processing in the multimodal endpoint.",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This vulnerability is rated Critical rather than Important because it allows unauthenticated remote code execution without requiring user interaction, ultimately leading to full compromise of the affected system. An attacker can provide a malicious video URL to a vulnerable vLLM inference endpoint, which causes the service to automatically retrieve and process attacker-controlled media content. During decoding, a heap overflow is triggered in the underlying video processing stack, enabling corruption of heap memory and potential overwriting of control structures to execute arbitrary commands on the host. In addition, an information disclosure condition can leak memory addresses, significantly weakening ASLR protections and making exploitation more reliable when combined with the heap overflow. Successful exploitation compromises the confidentiality, integrity, and availability of the system and can impact deployments such as Red Hat AI Inference Server, Red Hat Enterprise Linux AI, and Red Hat OpenShift AI, thereby meeting Red Hat\u2019s criteria for Critical severity rather than Important impact.\n\nThe vLLM vulnerability depends on CVE-2025-9951, as processing attacker-controlled media can trigger the JPEG2000 decoder heap overflow, which can then be exploited within the vLLM video handling pipeline to cause memory corruption and potentially achieve remote code execution.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
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]
},
"references": [
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"summary": "Canonical URL",
"url": "https://access.redhat.com/security/cve/CVE-2026-22778"
},
{
"category": "external",
"summary": "RHBZ#2436113",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2436113"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-22778",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-22778"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-22778",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-22778"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/pull/31987",
"url": "https://github.com/vllm-project/vllm/pull/31987"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/pull/32319",
"url": "https://github.com/vllm-project/vllm/pull/32319"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/releases/tag/v0.14.1",
"url": "https://github.com/vllm-project/vllm/releases/tag/v0.14.1"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/security/advisories/GHSA-4r2x-xpjr-7cvv",
"url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-4r2x-xpjr-7cvv"
}
],
"release_date": "2026-02-02T21:09:53.265000+00:00",
"remediations": [
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"date": "2026-06-25T19:30:53+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30088",
"product_ids": [
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"restart_required": {
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"category": "workaround",
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"scores": [
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"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"products": [
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]
}
],
"threats": [
{
"category": "impact",
"details": "Critical"
}
],
"title": "vLLM: vLLM: Remote code execution via invalid image processing in the multimodal endpoint."
},
{
"cve": "CVE-2026-22807",
"cwe": {
"id": "CWE-94",
"name": "Improper Control of Generation of Code (\u0027Code Injection\u0027)"
},
"discovery_date": "2026-01-21T22:00:55.823882+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2431865"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). This vulnerability allows a remote attacker to achieve arbitrary code execution on the vLLM host during model loading. This occurs because vLLM loads Hugging Face `auto_map` dynamic modules without properly validating the `trust_remote_code` setting. By influencing the model repository or path, an attacker can execute malicious Python code at server startup, even before any API requests are handled.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "vLLM: vLLM: Arbitrary code execution via untrusted model loading",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This vulnerability is rated Important for Red Hat as vLLM, an inference and serving engine for large language models, is vulnerable to arbitrary code execution. An attacker influencing the model repository or path can execute malicious Python code during server startup, affecting vLLM versions 0.10.1 through 0.13.x.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
]
},
"references": [
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"summary": "Canonical URL",
"url": "https://access.redhat.com/security/cve/CVE-2026-22807"
},
{
"category": "external",
"summary": "RHBZ#2431865",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2431865"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-22807",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-22807"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-22807",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-22807"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/commit/78d13ea9de4b1ce5e4d8a5af9738fea71fb024e5",
"url": "https://github.com/vllm-project/vllm/commit/78d13ea9de4b1ce5e4d8a5af9738fea71fb024e5"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/pull/32194",
"url": "https://github.com/vllm-project/vllm/pull/32194"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/releases/tag/v0.14.0",
"url": "https://github.com/vllm-project/vllm/releases/tag/v0.14.0"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/security/advisories/GHSA-2pc9-4j83-qjmr",
"url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-2pc9-4j83-qjmr"
}
],
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"remediations": [
{
"category": "vendor_fix",
"date": "2026-06-25T19:30:53+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30088",
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"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
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"category": "none"
},
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},
{
"category": "workaround",
"details": "To mitigate this issue, ensure that vLLM instances are configured to load models only from trusted and verified repositories. Restrict access to the model repository path to prevent unauthorized modification or introduction of malicious code. Implement strict access controls and integrity checks for all model sources.",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
]
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{
"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
"version": "3.1"
},
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]
}
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"threats": [
{
"category": "impact",
"details": "Important"
}
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"title": "vLLM: vLLM: Arbitrary code execution via untrusted model loading"
},
{
"cve": "CVE-2026-23490",
"cwe": {
"id": "CWE-770",
"name": "Allocation of Resources Without Limits or Throttling"
},
"discovery_date": "2026-01-16T20:03:33.790513+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2430472"
}
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{
"category": "description",
"text": "A flaw was found in pyasn1, a generic ASN.1 library for Python. A remote attacker could exploit this vulnerability by sending a specially crafted RELATIVE-OID with excessive continuation octets. This input validation vulnerability leads to memory exhaustion, resulting in a Denial of Service (DoS) for the affected system.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "pyasn1: pyasn1: Denial of Service due to memory exhaustion from malformed RELATIVE-OID",
"title": "Vulnerability summary"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
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"fixed": [
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},
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"category": "external",
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"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-23490"
},
{
"category": "external",
"summary": "https://github.com/pyasn1/pyasn1/commit/3908f144229eed4df24bd569d16e5991ace44970",
"url": "https://github.com/pyasn1/pyasn1/commit/3908f144229eed4df24bd569d16e5991ace44970"
},
{
"category": "external",
"summary": "https://github.com/pyasn1/pyasn1/releases/tag/v0.6.2",
"url": "https://github.com/pyasn1/pyasn1/releases/tag/v0.6.2"
},
{
"category": "external",
"summary": "https://github.com/pyasn1/pyasn1/security/advisories/GHSA-63vm-454h-vhhq",
"url": "https://github.com/pyasn1/pyasn1/security/advisories/GHSA-63vm-454h-vhhq"
}
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"release_date": "2026-01-16T19:03:36.442000+00:00",
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{
"category": "vendor_fix",
"date": "2026-06-25T19:30:53+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30088",
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{
"cvss_v3": {
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"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
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]
}
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"category": "impact",
"details": "Important"
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},
{
"cve": "CVE-2026-24779",
"cwe": {
"id": "CWE-918",
"name": "Server-Side Request Forgery (SSRF)"
},
"discovery_date": "2026-01-27T23:00:53.998772+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2433624"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). A Server-Side Request Forgery (SSRF) vulnerability exists in the MediaConnector class, specifically within the load_from_url and load_from_url_async methods. An attacker can exploit differing interpretations of backslashes by Python parsing libraries used for host restrictions to bypass these restrictions. This allows the attacker to force the vLLM server to make arbitrary requests to internal network resources, potentially leading to information disclosure, denial of service, or unauthorized access within containerized environments.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "vLLM: vLLM: Server-Side Request Forgery allows internal network access",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This IMPORTANT Server-Side Request Forgery (SSRF) vulnerability in vLLM\u0027s `MediaConnector` allows an attacker to bypass host restrictions when processing user-provided URLs. This enables the vLLM server to be coerced into making arbitrary requests to internal network resources. This is critical in containerized deployments, including Red Hat AI Inference Server, Red Hat Enterprise Linux AI, and Red Hat OpenShift AI, where it could facilitate internal network reconnaissance and unauthorized access to other services.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
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"fixed": [
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"summary": "Canonical URL",
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"category": "external",
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},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-24779",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-24779"
},
{
"category": "external",
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"url": "https://github.com/vllm-project/vllm/commit/f46d576c54fb8aeec5fc70560e850bed38ef17d7"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/pull/32746",
"url": "https://github.com/vllm-project/vllm/pull/32746"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/security/advisories/GHSA-qh4c-xf7m-gxfc",
"url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-qh4c-xf7m-gxfc"
}
],
"release_date": "2026-01-27T22:01:13.808000+00:00",
"remediations": [
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"date": "2026-06-25T19:30:53+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30088",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
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"restart_required": {
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},
"url": "https://access.redhat.com/errata/RHSA-2026:30088"
},
{
"category": "workaround",
"details": "To mitigate this issue, restrict network access to the vLLM service to only trusted clients. Implement strict network segmentation for vLLM pods in containerized environments to limit potential lateral movement. Ensure that vLLM instances are not exposed to untrusted external networks without proper access controls and input validation at the perimeter.",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
]
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"attackVector": "NETWORK",
"availabilityImpact": "LOW",
"baseScore": 7.1,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:L",
"version": "3.1"
},
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}
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"details": "Important"
}
],
"title": "vLLM: vLLM: Server-Side Request Forgery allows internal network access"
},
{
"cve": "CVE-2026-34588",
"cwe": {
"id": "CWE-190",
"name": "Integer Overflow or Wraparound"
},
"discovery_date": "2026-04-06T16:02:38.673068+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2455408"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in OpenEXR, an image storage format for the motion picture industry. A remote attacker could exploit an integer overflow vulnerability in the `internal_exr_undo_piz()` function by providing a specially crafted EXR file. This flaw leads to out-of-bounds reads and writes, which may allow for arbitrary code execution or sensitive information disclosure.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "OpenEXR: OpenEXR: Arbitrary code execution and information disclosure via crafted EXR file",
"title": "Vulnerability summary"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
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"summary": "Canonical URL",
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},
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"category": "external",
"summary": "RHBZ#2455408",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2455408"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-34588",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-34588"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-34588",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-34588"
},
{
"category": "external",
"summary": "https://github.com/AcademySoftwareFoundation/openexr/security/advisories/GHSA-588r-cr5c-w6hf",
"url": "https://github.com/AcademySoftwareFoundation/openexr/security/advisories/GHSA-588r-cr5c-w6hf"
}
],
"release_date": "2026-04-06T15:31:57.602000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-06-25T19:30:53+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30088",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
],
"restart_required": {
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},
"url": "https://access.redhat.com/errata/RHSA-2026:30088"
},
{
"category": "workaround",
"details": "Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability.",
"product_ids": [
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"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
"version": "3.1"
},
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]
}
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"details": "Important"
}
],
"title": "OpenEXR: OpenEXR: Arbitrary code execution and information disclosure via crafted EXR file"
},
{
"cve": "CVE-2026-34982",
"cwe": {
"id": "CWE-78",
"name": "Improper Neutralization of Special Elements used in an OS Command (\u0027OS Command Injection\u0027)"
},
"discovery_date": "2026-04-06T16:02:10.004743+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2455400"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in Vim. A modeline is used to set specific editor options directly from a text file. However, the `complete`, `guitabtooltip`, `printheader` options and the `mapset` function lack proper security checks, allowing an attacker to bypass restrictions and cause arbitrary OS command execution.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "vim: arbitrary command execution via modeline sandbox bypass",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "To exploit this vulnerability, an attacker needs to convince a user to open a specially crafted file. The arbitrary OS command execution is restricted to the privileges of the user running Vim, limiting the potential of a full system compromise.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
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"summary": "Canonical URL",
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},
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},
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"url": "https://www.cve.org/CVERecord?id=CVE-2026-34982"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-34982",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-34982"
},
{
"category": "external",
"summary": "http://www.openwall.com/lists/oss-security/2026/04/01/1",
"url": "http://www.openwall.com/lists/oss-security/2026/04/01/1"
},
{
"category": "external",
"summary": "https://github.com/vim/vim/commit/75661a66a1db1e1f3f1245c615",
"url": "https://github.com/vim/vim/commit/75661a66a1db1e1f3f1245c615"
},
{
"category": "external",
"summary": "https://github.com/vim/vim/releases/tag/v9.2.0276",
"url": "https://github.com/vim/vim/releases/tag/v9.2.0276"
},
{
"category": "external",
"summary": "https://github.com/vim/vim/security/advisories/GHSA-8h6p-m6gr-mpw9",
"url": "https://github.com/vim/vim/security/advisories/GHSA-8h6p-m6gr-mpw9"
}
],
"release_date": "2026-04-06T15:16:48.809000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-06-25T19:30:53+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30088",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
],
"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:30088"
},
{
"category": "workaround",
"details": "To mitigate this issue, disable the modeline support by adding the following command to the Vim configuration file:\n\n~~~\nset nomodeline\n~~~",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
]
}
],
"scores": [
{
"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "NONE",
"baseScore": 8.2,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "CHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:N",
"version": "3.1"
},
"products": [
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]
}
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"threats": [
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"category": "impact",
"details": "Important"
}
],
"title": "vim: arbitrary command execution via modeline sandbox bypass"
},
{
"cve": "CVE-2026-35385",
"cwe": {
"id": "CWE-281",
"name": "Improper Preservation of Permissions"
},
"discovery_date": "2026-04-02T17:01:07.052864+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2454469"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in OpenSSH. When the `scp` command is used by a root user to download a file with the legacy protocol option (`-O`) and without preserving original file permissions (`-p`), the downloaded file can be installed with elevated privileges (setuid or setgid). This unexpected behavior could allow a malicious file to execute with higher permissions than intended, posing a security risk through potential privilege escalation.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "OpenSSH: OpenSSH: Privilege escalation via scp legacy protocol when not preserving file mode",
"title": "Vulnerability summary"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"title": "OpenSSH: OpenSSH: Privilege escalation via scp legacy protocol when not preserving file mode"
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{
"category": "general",
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"title": "Statement"
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{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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{
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{
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"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"scope": "UNCHANGED",
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"title": "Statement"
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{
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"title": "CVSS score applicability"
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"title": "Vulnerability description"
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"title": "Vulnerability summary"
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{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
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"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-40164"
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"id": "CWE-201",
"name": "Insertion of Sensitive Information Into Sent Data"
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"title": "Vulnerability description"
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"title": "Vulnerability summary"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
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"title": "urllib3: urllib3: Information disclosure via cross-origin redirects forwarding sensitive headers"
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{
"cve": "CVE-2026-44432",
"cwe": {
"id": "CWE-409",
"name": "Improper Handling of Highly Compressed Data (Data Amplification)"
},
"discovery_date": "2026-05-13T17:01:01.083841+00:00",
"ids": [
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"title": "Vulnerability description"
},
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"title": "Vulnerability summary"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"scope": "UNCHANGED",
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"cwe": {
"id": "CWE-347",
"name": "Improper Verification of Cryptographic Signature"
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"discovery_date": "2026-05-28T16:01:22.805235+00:00",
"ids": [
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"text": "2482734"
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"text": "A flaw was found in PyJWT, a Python library for JSON Web Token (JWT) implementation. When decoding JWTs, the library fails to validate the use of JSON Web Keys (JWK) in the HMAC algorithm while also supporting asymmetric algorithms. This allows a remote attacker to use the issuer\u0027s public key as the secret key for the HMAC algorithm, leading to the ability to forge JWTs. This vulnerability can result in authentication bypass or unauthorized access.",
"title": "Vulnerability description"
},
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"category": "summary",
"text": "python-pyjwt: PyJWT: Authentication bypass due to forged JSON Web Tokens",
"title": "Vulnerability summary"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"ids": [
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"text": "2481742"
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"text": "A flaw was found in Starlette, a lightweight ASGI (Asynchronous Server Gateway Interface) framework. A remote attacker could exploit this vulnerability by sending a specially crafted HTTP `Host` request header. This malformed header could cause the `request.url` to be incorrectly reconstructed, leading to a discrepancy with the actual requested path. Consequently, security restrictions enforced by middleware and endpoints that rely on `request.url` for validation could be bypassed, potentially allowing unauthorized access or actions.",
"title": "Vulnerability description"
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"title": "Vulnerability summary"
},
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"text": "The impact is rated as Critical because path-based authentication and access control middleware can be completely bypassed by an unauthenticated remote attacker using a crafted HTTP Host header.\n\nStarlette reconstructs `request.url` by combining the HTTP Host header value with the request path, but performs no validation on the Host header. An attacker can inject path separators or query characters into the Host header (e.g., `Host: example.com/health?x=`), causing `request.url.path` to return a value that differs from the actual HTTP `request path` used for routing. Middleware that enforces authentication or authorization decisions based on `request.url.path` will evaluate the injected path rather than the real one, allowing the attacker to reach protected endpoints.\n\nWith regard to CVSS metrics, the Attack Vector (AV) is Network and Privileges Required (PR) is None, because the attack requires only the ability to send HTTP requests with a crafted Host header. User interaction is not required.\n\nRed Hat Satellite / Insights (IoP): The starlette package is included as a dependency of Connexion, but this flaw is rated Low impact because these services do not use path-based authentication middleware and all services are deployed behind reverse proxies. \n\nOpenShift Lightspeed (OLS): The starlette package is included as a dependency, but this flaw is rated Low impact because authentication is enforced via Kubernetes TokenReview/SubjectAccessReview through FastAPI dependency injection, not path-based middleware; request.url.path is only used for metrics and response header application.\n\nRHOAI Kubeflow Training images: starlette is being used as indirect dependency of mlflow, but this flaw is rated as Low impact because mlflow is used as client library only to store training metrics on remote server, it doesn\u0027t expose any endpoint.\n\nRHOAI odh-automl: The impact is reduced to Low since starlette is only used in the backend and it\u0027s transient dependency and starlette is not used at all to serve any endpoints.\n\nRHOAI odh-kserve-autogluon-server-rhel9: While the Starlette dependency is present in the build, the vulnerable code in starlette is not reachable. This reduces the impact to low.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"summary": "https://badhost.org",
"url": "https://badhost.org"
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"url": "https://github.com/pypa/advisory-database/tree/main/vulns/starlette/PYSEC-2026-161.yaml"
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"category": "external",
"summary": "https://ostif.org/disclosing-the-badhost-vulnerability-in-starlette",
"url": "https://ostif.org/disclosing-the-badhost-vulnerability-in-starlette"
},
{
"category": "external",
"summary": "https://www.secwest.net/starlette",
"url": "https://www.secwest.net/starlette"
},
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"category": "external",
"summary": "https://www.x41-dsec.de/lab/advisories/x41-2026-002-starlette",
"url": "https://www.x41-dsec.de/lab/advisories/x41-2026-002-starlette"
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],
"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:30088"
},
{
"category": "workaround",
"details": "Deploying an RFC-compliant reverse proxy (such as nginx, Apache, HAProxy, or Caddy) in front of the ASGI server will reject malformed Host headers before they reach the application. This is the most straightforward mitigation that does not require code changes.\n\nIf custom middleware is present, it should be updated to use `request.scope[\"path\"]` instead of `request.url.path` for any security decisions. The ASGI scope path is derived from the HTTP request line and is not influenced by the Host header, so it reflects the actual request target.",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
]
}
],
"scores": [
{
"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 6.5,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N",
"version": "3.1"
},
"products": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
]
}
],
"threats": [
{
"category": "impact",
"details": "Critical"
}
],
"title": "starlette: Starlette: Security restriction bypass via malformed HTTP Host header"
},
{
"cve": "CVE-2026-48746",
"cwe": {
"id": "CWE-501",
"name": "Trust Boundary Violation"
},
"discovery_date": "2026-06-22T23:00:57.824402+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2491581"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). This vulnerability, residing in ASGI web servers and Starlette\u0027s trust in them, allows an attacker to bypass the OpenAI API Authentication Middleware. This bypass enables unauthorized access to the API without requiring the configured VLLM_API_KEY or --api-key, leading to critical unauthorized operations.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "vllm: starlette: vLLM: Critical authentication bypass allows unauthorized API access",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "CVE-2026-48746 is an authentication bypass in the vLLM OpenAI-compatible API server. A remote attacker who can reach the vLLM endpoint directly can craft a Host header so the authentication middleware checks a different URL path than the one actually dispatched, bypassing VLLM_API_KEY / --api-key protection. Successful exploitation allows unauthorized inference API access, which can result in confidentiality loss (model/prompt abuse) and availability impact (resource exhaustion). The flaw does not provide integrity compromise or arbitrary code execution. Exploitation requires vLLM API-key authentication to be enabled and the service to be exposed without an RFC-conforming reverse proxy that normalizes the Host header. Because Red Hat AI inference offerings are commonly deployed behind OpenShift Routes or similar proxies, and because the vulnerability is conditional on deployment and configuration, the overall flaw impact is rated Important rather than Critical.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
]
},
"references": [
{
"category": "self",
"summary": "Canonical URL",
"url": "https://access.redhat.com/security/cve/CVE-2026-48746"
},
{
"category": "external",
"summary": "RHBZ#2491581",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2491581"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-48746",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-48746"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-48746",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-48746"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/pull/43426",
"url": "https://github.com/vllm-project/vllm/pull/43426"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/security/advisories/GHSA-94f4-hr76-p5j6",
"url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-94f4-hr76-p5j6"
},
{
"category": "external",
"summary": "https://x41-dsec.de/lab/advisories/x41-2026-002-starlette",
"url": "https://x41-dsec.de/lab/advisories/x41-2026-002-starlette"
}
],
"release_date": "2026-06-22T21:57:28.997000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-06-25T19:30:53+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30088",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
],
"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:30088"
},
{
"category": "workaround",
"details": "Restrict network access to the vLLM API endpoint to only trusted clients and internal networks. Implement firewall rules or network policies to limit inbound connections to the vLLM service, thereby reducing the attack surface. This operational control helps prevent unauthorized external access to the vulnerable API.",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
]
}
],
"scores": [
{
"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.1,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:H",
"version": "3.1"
},
"products": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
]
}
],
"threats": [
{
"category": "impact",
"details": "Important"
}
],
"title": "vllm: starlette: vLLM: Critical authentication bypass allows unauthorized API access"
},
{
"cve": "CVE-2026-48818",
"cwe": {
"id": "CWE-918",
"name": "Server-Side Request Forgery (SSRF)"
},
"discovery_date": "2026-06-17T19:03:44.998691+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2490020"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in Starlette, a lightweight ASGI framework. On Windows systems, the StaticFiles component is vulnerable to Server-Side Request Forgery (SSRF). A remote attacker can exploit this by providing a specially crafted Universal Naming Convention (UNC) path, which causes the system to initiate an outbound Server Message Block (SMB) connection. This action can expose the service account\u0027s NTLMv2 credentials, potentially leading to information disclosure or further attacks.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "starlette: Starlette: SSRF and NTLM credential theft via UNC paths in StaticFiles on Windows",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This Important flaw in Starlette\u0027s StaticFiles component, which allows for NTLMv2 credential theft via specially crafted UNC paths, does not affect Red Hat products. The vulnerability is specific to Windows operating systems, and the vulnerable code is not present in Red Hat\u0027s supported configurations.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
]
},
"references": [
{
"category": "self",
"summary": "Canonical URL",
"url": "https://access.redhat.com/security/cve/CVE-2026-48818"
},
{
"category": "external",
"summary": "RHBZ#2490020",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2490020"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-48818",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-48818"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-48818",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-48818"
},
{
"category": "external",
"summary": "https://github.com/Kludex/starlette/commit/fd53168a7767b6b55ba5af787fd88f49e33cabc5",
"url": "https://github.com/Kludex/starlette/commit/fd53168a7767b6b55ba5af787fd88f49e33cabc5"
},
{
"category": "external",
"summary": "https://github.com/Kludex/starlette/pull/3287",
"url": "https://github.com/Kludex/starlette/pull/3287"
},
{
"category": "external",
"summary": "https://github.com/Kludex/starlette/releases/tag/1.1.0",
"url": "https://github.com/Kludex/starlette/releases/tag/1.1.0"
},
{
"category": "external",
"summary": "https://github.com/Kludex/starlette/security/advisories/GHSA-wqp7-x3pw-xc5r",
"url": "https://github.com/Kludex/starlette/security/advisories/GHSA-wqp7-x3pw-xc5r"
}
],
"release_date": "2026-06-17T17:50:12.399000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-06-25T19:30:53+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30088",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
],
"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:30088"
},
{
"category": "workaround",
"details": "Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability.",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
]
}
],
"scores": [
{
"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
"version": "3.1"
},
"products": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-rocm-rhel9@sha256:993e84c73225a7c5e2df63756643a26b054b665eb6c15599d9decbbce91b6863_amd64"
]
}
],
"threats": [
{
"category": "impact",
"details": "Important"
}
],
"title": "starlette: Starlette: SSRF and NTLM credential theft via UNC paths in StaticFiles on Windows"
}
]
}
RHSA-2026:30089
Vulnerability from csaf_redhat - Published: 2026-06-25 19:32 - Updated: 2026-06-27 08:31A flaw was found in the libtiff library. A remote attacker could exploit a signed integer overflow vulnerability in the putcontig8bitYCbCr44tile function by providing a specially crafted TIFF file. This flaw can lead to an out-of-bounds heap write due to incorrect memory pointer calculations, potentially causing a denial of service (application crash) or arbitrary code execution.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in the Python webbrowser.open() API. If a specially crafted URL containing "%action" is processed, an attacker could bypass a previous mitigation for CVE-2026-4519. This bypass allows for command injection into the underlying shell, potentially leading to arbitrary code execution.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in libcap. A local unprivileged user can exploit a Time-of-check-to-time-of-use (TOCTOU) race condition in the `cap_set_file()` function. This allows an attacker with write access to a parent directory to redirect file capability updates to an attacker-controlled file. By doing so, capabilities can be injected into or stripped from unintended executables, leading to privilege escalation.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in Python's decompression modules, including `lzma.LZMADecompressor`, `bz2.BZ2Decompressor`, and `gzip.GzipFile`. This vulnerability, a use-after-free, can occur if a program attempts to re-use a decompression object after a memory allocation error, especially when the system is experiencing high memory usage. Exploitation of this flaw could potentially allow an attacker to execute arbitrary code or access sensitive data. The vulnerability is only present if the program re-uses decompressor instances across multiple decompression calls even after a `MemoryError` is raised during decompression. Using the helper functions to one-shot decompress data such as `lzma.decompress()`, `bz2.decompress()`, `gzip.decompress()`, and `zlib.decompress()` are not affected as a new decompressor instance is used per call. If the decompressor instance is not re-used after an error condition, this usage is similarly not vulnerable.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in Poppler's Splash backend. A remote attacker could exploit this vulnerability by crafting a malicious PDF file that, when rendered, triggers an integer overflow in the `tilingPatternFill` function. This overflow leads to an undersized heap memory allocation, allowing a subsequent out-of-bounds write. Successful exploitation could result in arbitrary code execution, information disclosure, or denial of service within the context of the application processing the PDF.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). A remote attacker can exploit this vulnerability by sending a specially crafted video URL to vLLM's multimodal endpoint. This action causes vLLM to leak a heap memory address, significantly reducing the effectiveness of Address Space Layout Randomization (ASLR). This information disclosure can then be chained with a heap overflow vulnerability to achieve remote code execution.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). This vulnerability allows a remote attacker to achieve arbitrary code execution on the vLLM host during model loading. This occurs because vLLM loads Hugging Face `auto_map` dynamic modules without properly validating the `trust_remote_code` setting. By influencing the model repository or path, an attacker can execute malicious Python code at server startup, even before any API requests are handled.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). A Server-Side Request Forgery (SSRF) vulnerability exists in the MediaConnector class, specifically within the load_from_url and load_from_url_async methods. An attacker can exploit differing interpretations of backslashes by Python parsing libraries used for host restrictions to bypass these restrictions. This allows the attacker to force the vLLM server to make arbitrary requests to internal network resources, potentially leading to information disclosure, denial of service, or unauthorized access within containerized environments.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in OpenEXR, an image storage format for the motion picture industry. A remote attacker could exploit an integer overflow vulnerability in the `internal_exr_undo_piz()` function by providing a specially crafted EXR file. This flaw leads to out-of-bounds reads and writes, which may allow for arbitrary code execution or sensitive information disclosure.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in Vim. A modeline is used to set specific editor options directly from a text file. However, the `complete`, `guitabtooltip`, `printheader` options and the `mapset` function lack proper security checks, allowing an attacker to bypass restrictions and cause arbitrary OS command execution.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in OpenSSH. When the `scp` command is used by a root user to download a file with the legacy protocol option (`-O`) and without preserving original file permissions (`-p`), the downloaded file can be installed with elevated privileges (setuid or setgid). This unexpected behavior could allow a malicious file to execute with higher permissions than intended, posing a security risk through potential privilege escalation.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in the libsndfile library. An integer overflow in the IMA ADPCM codec can occur when a specially crafted WAV audio file is processed, specifically with malicious samplesperblock and blocks values. This can lead to a heap-based buffer overflow, causing a crash to the application linked to the library and memory corruption.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
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Workaround
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
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fix
Workaround
|
A flaw was found in the cryptography library. This vulnerability occurs when a non-contiguous buffer is passed to certain application programming interfaces (APIs) that accept Python buffers, such as Hash.update(). A remote attacker could exploit this to cause a buffer overflow, potentially leading to a denial of service.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
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fix
Workaround
|
A flaw was found in jq, a command line JSON processor, specifically in the libjq API. Parsing a malformed JSON input from a non-NUL-terminated buffer using the `jv_parse_sized` function can cause an out-of-bounds read, resulting in an application crash and a possible memory disclosure within the error message generated by the parser.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in jq, a command-line JSON processor. A remote attacker could exploit this vulnerability by providing a specially crafted JSON object. This object leverages a weakness in jq's hashing algorithm, which uses a hardcoded, publicly known seed. By crafting the JSON object to cause hash collisions, an attacker can degrade the performance of JSON object hash table operations, leading to significant CPU exhaustion and a denial of service (DoS) for systems processing the malicious JSON data.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in urllib3, an HTTP client library for Python. When using the low-level API via `ProxyManager.connection_from_url().urlopen()` with `assert_same_host=False`, cross-origin redirects can still forward sensitive headers. This could allow a remote attacker to gain unauthorized access to sensitive information.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
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|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
|
A flaw was found in urllib3, an HTTP client library for Python. This vulnerability allows a remote attacker to cause excessive resource consumption, such as high CPU usage and massive memory allocation, on the client side. This occurs when urllib3 attempts to decompress an entire HTTP response, even if only a partial read was requested, or when draining the connection after a partial decompression. This can lead to a Denial of Service (DoS) condition.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
|
A flaw was found in PyJWT, a Python library for JSON Web Token (JWT) implementation. When decoding JWTs, the library fails to validate the use of JSON Web Keys (JWK) in the HMAC algorithm while also supporting asymmetric algorithms. This allows a remote attacker to use the issuer's public key as the secret key for the HMAC algorithm, leading to the ability to forge JWTs. This vulnerability can result in authentication bypass or unauthorized access.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
fix
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
|
A flaw was found in Starlette, a lightweight ASGI (Asynchronous Server Gateway Interface) framework. A remote attacker could exploit this vulnerability by sending a specially crafted HTTP `Host` request header. This malformed header could cause the `request.url` to be incorrectly reconstructed, leading to a discrepancy with the actual requested path. Consequently, security restrictions enforced by middleware and endpoints that rely on `request.url` for validation could be bypassed, potentially allowing unauthorized access or actions.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
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fix
Workaround
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|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). This vulnerability, residing in ASGI web servers and Starlette's trust in them, allows an attacker to bypass the OpenAI API Authentication Middleware. This bypass enables unauthorized access to the API without requiring the configured VLLM_API_KEY or --api-key, leading to critical unauthorized operations.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
A flaw was found in Starlette, a lightweight ASGI framework. On Windows systems, the StaticFiles component is vulnerable to Server-Side Request Forgery (SSRF). A remote attacker can exploit this by providing a specially crafted Universal Naming Convention (UNC) path, which causes the system to initiate an outbound Server Message Block (SMB) connection. This action can expose the service account's NTLMv2 credentials, potentially leading to information disclosure or further attacks.
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64 | — |
Vendor Fix
fix
Workaround
|
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"text": "libtiff: libtiff: Arbitrary code execution or denial of service via signed integer overflow in TIFF file processing",
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},
{
"category": "other",
"text": "A flaw in the libtiff library, affecting the processing of specially crafted TIFF files, could lead to a denial of service or potentially arbitrary code execution. This vulnerability, caused by a signed integer overflow during TIFF image processing, results in an out-of-bounds heap write. Red Hat products that process untrusted TIFF files using libtiff may be impacted.",
"title": "Statement"
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{
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{
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"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-4775",
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"id": "CWE-88",
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"title": "Statement"
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{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"title": "Statement"
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"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"text": "python: Python: Arbitrary code execution or information disclosure via use-after-free in decompression modules",
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"title": "Statement"
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{
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"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"category": "description",
"text": "A flaw was found in Poppler\u0027s Splash backend. A remote attacker could exploit this vulnerability by crafting a malicious PDF file that, when rendered, triggers an integer overflow in the `tilingPatternFill` function. This overflow leads to an undersized heap memory allocation, allowing a subsequent out-of-bounds write. Successful exploitation could result in arbitrary code execution, information disclosure, or denial of service within the context of the application processing the PDF.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "poppler: Integer overflow in Poppler SplashOutputDev::tilingPatternFill leads to heap buffer overflow via unchecked dimension multiplication",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This is an Important heap-based memory corruption flaw in Poppler\u0027s Splash backend. Processing a specially crafted PDF document can lead to an integer overflow, resulting in an undersized heap allocation and a subsequent out-of-bounds write. This could allow an attacker to achieve arbitrary code execution, disclose sensitive information, or cause a denial of service within the context of the application rendering the PDF. To successfully exploit this vulnerability the attacker needs to be able to supply the maliciously crafted PDF file to the application consuming poppler or trick the user to process the PDF file using the Poppler\u0027s backend.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64",
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]
},
"references": [
{
"category": "self",
"summary": "Canonical URL",
"url": "https://access.redhat.com/security/cve/CVE-2026-10118"
},
{
"category": "external",
"summary": "RHBZ#2460428",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2460428"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-10118",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-10118"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-10118",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-10118"
},
{
"category": "external",
"summary": "https://gitlab.freedesktop.org/poppler/poppler/-/work_items/1715",
"url": "https://gitlab.freedesktop.org/poppler/poppler/-/work_items/1715"
}
],
"release_date": "2026-06-01T15:25:35.578000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-06-25T19:32:31+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30089",
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"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:30089"
},
{
"category": "workaround",
"details": "To mitigate this issue, users should avoid opening untrusted or suspicious PDF documents with applications that utilize the Poppler library for rendering. Limiting exposure to untrusted content can reduce the risk of exploitation.",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64",
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"scores": [
{
"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 7.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
"version": "3.1"
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"threats": [
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"category": "impact",
"details": "Important"
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"title": "poppler: Integer overflow in Poppler SplashOutputDev::tilingPatternFill leads to heap buffer overflow via unchecked dimension multiplication"
},
{
"cve": "CVE-2026-22778",
"cwe": {
"id": "CWE-209",
"name": "Generation of Error Message Containing Sensitive Information"
},
"discovery_date": "2026-02-03T00:01:43.512265+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2436113"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). A remote attacker can exploit this vulnerability by sending a specially crafted video URL to vLLM\u0027s multimodal endpoint. This action causes vLLM to leak a heap memory address, significantly reducing the effectiveness of Address Space Layout Randomization (ASLR). This information disclosure can then be chained with a heap overflow vulnerability to achieve remote code execution.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "vLLM: vLLM: Remote code execution via invalid image processing in the multimodal endpoint.",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This vulnerability is rated Critical rather than Important because it allows unauthenticated remote code execution without requiring user interaction, ultimately leading to full compromise of the affected system. An attacker can provide a malicious video URL to a vulnerable vLLM inference endpoint, which causes the service to automatically retrieve and process attacker-controlled media content. During decoding, a heap overflow is triggered in the underlying video processing stack, enabling corruption of heap memory and potential overwriting of control structures to execute arbitrary commands on the host. In addition, an information disclosure condition can leak memory addresses, significantly weakening ASLR protections and making exploitation more reliable when combined with the heap overflow. Successful exploitation compromises the confidentiality, integrity, and availability of the system and can impact deployments such as Red Hat AI Inference Server, Red Hat Enterprise Linux AI, and Red Hat OpenShift AI, thereby meeting Red Hat\u2019s criteria for Critical severity rather than Important impact.\n\nThe vLLM vulnerability depends on CVE-2025-9951, as processing attacker-controlled media can trigger the JPEG2000 decoder heap overflow, which can then be exploited within the vLLM video handling pipeline to cause memory corruption and potentially achieve remote code execution.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64",
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"references": [
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"category": "self",
"summary": "Canonical URL",
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{
"category": "external",
"summary": "RHBZ#2436113",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2436113"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-22778",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-22778"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-22778",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-22778"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/pull/31987",
"url": "https://github.com/vllm-project/vllm/pull/31987"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/pull/32319",
"url": "https://github.com/vllm-project/vllm/pull/32319"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/releases/tag/v0.14.1",
"url": "https://github.com/vllm-project/vllm/releases/tag/v0.14.1"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/security/advisories/GHSA-4r2x-xpjr-7cvv",
"url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-4r2x-xpjr-7cvv"
}
],
"release_date": "2026-02-02T21:09:53.265000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-06-25T19:32:31+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30089",
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"restart_required": {
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{
"category": "workaround",
"details": "Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base, or stability.",
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"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
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"threats": [
{
"category": "impact",
"details": "Critical"
}
],
"title": "vLLM: vLLM: Remote code execution via invalid image processing in the multimodal endpoint."
},
{
"cve": "CVE-2026-22807",
"cwe": {
"id": "CWE-94",
"name": "Improper Control of Generation of Code (\u0027Code Injection\u0027)"
},
"discovery_date": "2026-01-21T22:00:55.823882+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2431865"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). This vulnerability allows a remote attacker to achieve arbitrary code execution on the vLLM host during model loading. This occurs because vLLM loads Hugging Face `auto_map` dynamic modules without properly validating the `trust_remote_code` setting. By influencing the model repository or path, an attacker can execute malicious Python code at server startup, even before any API requests are handled.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "vLLM: vLLM: Arbitrary code execution via untrusted model loading",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This vulnerability is rated Important for Red Hat as vLLM, an inference and serving engine for large language models, is vulnerable to arbitrary code execution. An attacker influencing the model repository or path can execute malicious Python code during server startup, affecting vLLM versions 0.10.1 through 0.13.x.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
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"references": [
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"summary": "Canonical URL",
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},
{
"category": "external",
"summary": "RHBZ#2431865",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2431865"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-22807",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-22807"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-22807",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-22807"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/commit/78d13ea9de4b1ce5e4d8a5af9738fea71fb024e5",
"url": "https://github.com/vllm-project/vllm/commit/78d13ea9de4b1ce5e4d8a5af9738fea71fb024e5"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/pull/32194",
"url": "https://github.com/vllm-project/vllm/pull/32194"
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"summary": "https://github.com/vllm-project/vllm/releases/tag/v0.14.0",
"url": "https://github.com/vllm-project/vllm/releases/tag/v0.14.0"
},
{
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"summary": "https://github.com/vllm-project/vllm/security/advisories/GHSA-2pc9-4j83-qjmr",
"url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-2pc9-4j83-qjmr"
}
],
"release_date": "2026-01-21T21:13:11.894000+00:00",
"remediations": [
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"date": "2026-06-25T19:32:31+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30089",
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"restart_required": {
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{
"category": "workaround",
"details": "To mitigate this issue, ensure that vLLM instances are configured to load models only from trusted and verified repositories. Restrict access to the model repository path to prevent unauthorized modification or introduction of malicious code. Implement strict access controls and integrity checks for all model sources.",
"product_ids": [
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"scores": [
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"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"products": [
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"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64"
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"threats": [
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"category": "impact",
"details": "Important"
}
],
"title": "vLLM: vLLM: Arbitrary code execution via untrusted model loading"
},
{
"cve": "CVE-2026-24779",
"cwe": {
"id": "CWE-918",
"name": "Server-Side Request Forgery (SSRF)"
},
"discovery_date": "2026-01-27T23:00:53.998772+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2433624"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). A Server-Side Request Forgery (SSRF) vulnerability exists in the MediaConnector class, specifically within the load_from_url and load_from_url_async methods. An attacker can exploit differing interpretations of backslashes by Python parsing libraries used for host restrictions to bypass these restrictions. This allows the attacker to force the vLLM server to make arbitrary requests to internal network resources, potentially leading to information disclosure, denial of service, or unauthorized access within containerized environments.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "vLLM: vLLM: Server-Side Request Forgery allows internal network access",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This IMPORTANT Server-Side Request Forgery (SSRF) vulnerability in vLLM\u0027s `MediaConnector` allows an attacker to bypass host restrictions when processing user-provided URLs. This enables the vLLM server to be coerced into making arbitrary requests to internal network resources. This is critical in containerized deployments, including Red Hat AI Inference Server, Red Hat Enterprise Linux AI, and Red Hat OpenShift AI, where it could facilitate internal network reconnaissance and unauthorized access to other services.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
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"summary": "RHBZ#2433624",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2433624"
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"url": "https://www.cve.org/CVERecord?id=CVE-2026-24779"
},
{
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"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-24779",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-24779"
},
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"summary": "https://github.com/vllm-project/vllm/commit/f46d576c54fb8aeec5fc70560e850bed38ef17d7",
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},
{
"category": "general",
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"title": "CVSS score applicability"
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},
{
"category": "general",
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"title": "CVSS score applicability"
}
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"id": "CWE-409",
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"title": "Vulnerability description"
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"text": "urllib3: urllib3: Denial of Service due to excessive HTTP response decompression",
"title": "Vulnerability summary"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
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"url": "https://www.cve.org/CVERecord?id=CVE-2026-44432"
},
{
"category": "external",
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"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-44432"
},
{
"category": "external",
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},
{
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"title": "Vulnerability summary"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
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"ids": [
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"text": "A flaw was found in Starlette, a lightweight ASGI (Asynchronous Server Gateway Interface) framework. A remote attacker could exploit this vulnerability by sending a specially crafted HTTP `Host` request header. This malformed header could cause the `request.url` to be incorrectly reconstructed, leading to a discrepancy with the actual requested path. Consequently, security restrictions enforced by middleware and endpoints that rely on `request.url` for validation could be bypassed, potentially allowing unauthorized access or actions.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "starlette: Starlette: Security restriction bypass via malformed HTTP Host header",
"title": "Vulnerability summary"
},
{
"category": "other",
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"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
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"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-48710"
},
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"category": "external",
"summary": "https://badhost.org",
"url": "https://badhost.org"
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"title": "starlette: Starlette: Security restriction bypass via malformed HTTP Host header"
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{
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"cwe": {
"id": "CWE-501",
"name": "Trust Boundary Violation"
},
"discovery_date": "2026-06-22T23:00:57.824402+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2491581"
}
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"category": "description",
"text": "A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). This vulnerability, residing in ASGI web servers and Starlette\u0027s trust in them, allows an attacker to bypass the OpenAI API Authentication Middleware. This bypass enables unauthorized access to the API without requiring the configured VLLM_API_KEY or --api-key, leading to critical unauthorized operations.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "vllm: starlette: vLLM: Critical authentication bypass allows unauthorized API access",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "CVE-2026-48746 is an authentication bypass in the vLLM OpenAI-compatible API server. A remote attacker who can reach the vLLM endpoint directly can craft a Host header so the authentication middleware checks a different URL path than the one actually dispatched, bypassing VLLM_API_KEY / --api-key protection. Successful exploitation allows unauthorized inference API access, which can result in confidentiality loss (model/prompt abuse) and availability impact (resource exhaustion). The flaw does not provide integrity compromise or arbitrary code execution. Exploitation requires vLLM API-key authentication to be enabled and the service to be exposed without an RFC-conforming reverse proxy that normalizes the Host header. Because Red Hat AI inference offerings are commonly deployed behind OpenShift Routes or similar proxies, and because the vulnerability is conditional on deployment and configuration, the overall flaw impact is rated Important rather than Critical.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
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"category": "external",
"summary": "https://github.com/vllm-project/vllm/security/advisories/GHSA-94f4-hr76-p5j6",
"url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-94f4-hr76-p5j6"
},
{
"category": "external",
"summary": "https://x41-dsec.de/lab/advisories/x41-2026-002-starlette",
"url": "https://x41-dsec.de/lab/advisories/x41-2026-002-starlette"
}
],
"release_date": "2026-06-22T21:57:28.997000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-06-25T19:32:31+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30089",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64"
],
"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:30089"
},
{
"category": "workaround",
"details": "Restrict network access to the vLLM API endpoint to only trusted clients and internal networks. Implement firewall rules or network policies to limit inbound connections to the vLLM service, thereby reducing the attack surface. This operational control helps prevent unauthorized external access to the vulnerable API.",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64"
]
}
],
"scores": [
{
"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.1,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:H",
"version": "3.1"
},
"products": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64"
]
}
],
"threats": [
{
"category": "impact",
"details": "Important"
}
],
"title": "vllm: starlette: vLLM: Critical authentication bypass allows unauthorized API access"
},
{
"cve": "CVE-2026-48818",
"cwe": {
"id": "CWE-918",
"name": "Server-Side Request Forgery (SSRF)"
},
"discovery_date": "2026-06-17T19:03:44.998691+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2490020"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in Starlette, a lightweight ASGI framework. On Windows systems, the StaticFiles component is vulnerable to Server-Side Request Forgery (SSRF). A remote attacker can exploit this by providing a specially crafted Universal Naming Convention (UNC) path, which causes the system to initiate an outbound Server Message Block (SMB) connection. This action can expose the service account\u0027s NTLMv2 credentials, potentially leading to information disclosure or further attacks.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "starlette: Starlette: SSRF and NTLM credential theft via UNC paths in StaticFiles on Windows",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This Important flaw in Starlette\u0027s StaticFiles component, which allows for NTLMv2 credential theft via specially crafted UNC paths, does not affect Red Hat products. The vulnerability is specific to Windows operating systems, and the vulnerable code is not present in Red Hat\u0027s supported configurations.",
"title": "Statement"
},
{
"category": "general",
"text": "The CVSS score(s) listed for this vulnerability do not reflect the associated product\u0027s status, and are included for informational purposes to better understand the severity of this vulnerability.",
"title": "CVSS score applicability"
}
],
"product_status": {
"fixed": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64"
]
},
"references": [
{
"category": "self",
"summary": "Canonical URL",
"url": "https://access.redhat.com/security/cve/CVE-2026-48818"
},
{
"category": "external",
"summary": "RHBZ#2490020",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2490020"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-48818",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-48818"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-48818",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-48818"
},
{
"category": "external",
"summary": "https://github.com/Kludex/starlette/commit/fd53168a7767b6b55ba5af787fd88f49e33cabc5",
"url": "https://github.com/Kludex/starlette/commit/fd53168a7767b6b55ba5af787fd88f49e33cabc5"
},
{
"category": "external",
"summary": "https://github.com/Kludex/starlette/pull/3287",
"url": "https://github.com/Kludex/starlette/pull/3287"
},
{
"category": "external",
"summary": "https://github.com/Kludex/starlette/releases/tag/1.1.0",
"url": "https://github.com/Kludex/starlette/releases/tag/1.1.0"
},
{
"category": "external",
"summary": "https://github.com/Kludex/starlette/security/advisories/GHSA-wqp7-x3pw-xc5r",
"url": "https://github.com/Kludex/starlette/security/advisories/GHSA-wqp7-x3pw-xc5r"
}
],
"release_date": "2026-06-17T17:50:12.399000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-06-25T19:32:31+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:30089",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64"
],
"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:30089"
},
{
"category": "workaround",
"details": "Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability.",
"product_ids": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64"
]
}
],
"scores": [
{
"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
"version": "3.1"
},
"products": [
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9165ca6c4f41ed4f5cdf5c590bfad74e22abe23737adfdc40a4c4b340b10e309_arm64",
"Red Hat AI Inference Server 3.3:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:d869df392f711437069fa0c808428694c945d4b79e5dd77c718f68403cd71629_amd64"
]
}
],
"threats": [
{
"category": "impact",
"details": "Important"
}
],
"title": "starlette: Starlette: SSRF and NTLM credential theft via UNC paths in StaticFiles on Windows"
}
]
}
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.