RHSA-2026:36005
Vulnerability from csaf_redhat - Published: 2026-07-06 16:43 - Updated: 2026-07-08 06:40Summary
Red Hat Security Advisory: Red Hat AI Inference Server 3.2.2 (CUDA)
Severity
Important
Notes
Topic: Red Hat AI Inference Server 3.2.2 (CUDA) is now available.
Details: Red Hat® AI Inference Server
Terms of Use: 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.
A flaw was found in giflib. A remote attacker can exploit a buffer overflow vulnerability in the EGifGCBToExtension function by providing a specially crafted Graphics Control Extension (GCE) block. This allows overwriting an existing GCE block without proper size validation, leading to a denial of service (DoS) on the system.
7.5 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
A flaw in GnuTLS DTLS handshake parsing allows malformed fragments with zero length and non-zero offset, leading to an integer underflow during reassembly and resulting in an out-of-bounds read. This issue is remotely exploitable and may cause information disclosure or denial of service.
7.5 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
A heap buffer overflow vulnerability exists in the DTLS handshake fragment reassembly logic of GnuTLS. The issue arises in merge_handshake_packet() where incoming handshake fragments are matched and merged based solely on handshake type, without validating that the message_length field remains consistent across all fragments of the same logical message. An attacker can exploit this by sending crafted DTLS fragments with conflicting message_length values, causing the implementation to allocate a buffer based on a smaller initial fragment and subsequently write beyond its bounds using larger, inconsistent fragments. Because the merge operation does not enforce proper bounds checking against the allocated buffer size, this results in an out-of-bounds write on the heap. The vulnerability is remotely exploitable without authentication via the DTLS handshake path and can lead to application crashes or potential memory corruption.
7.5 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
A flaw was found in vLLM, an inference and serving engine for large language models. A remote attacker can exploit a vulnerability in the VideoMediaIO.load_base64() method by sending a single API request containing a large number of comma-separated base64-encoded JPEG frames. This bypasses the intended frame count limit, causing the server to decode all frames into memory. This can lead to an Out-of-Memory (OOM) crash, resulting in a Denial of Service (DoS) for the affected system.
6.5 (Medium)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). An unauthenticated attacker can exploit this vulnerability by sending a specially crafted HTTP request with an excessively large 'n' parameter to the vLLM OpenAI-compatible API server. This can lead to a Denial of Service (DoS) by consuming excessive memory and blocking the system's event loop, causing the server to crash.
6.5 (Medium)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
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.
8.2 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). An unauthenticated attacker can exploit an assert-based security check during activation function loading. By publishing a malicious HuggingFace model, an attacker can achieve arbitrary code execution on the server when vLLM runs in Python optimized mode.
7.5 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
A flaw was found in gnutls. A remote attacker could exploit an issue in the Datagram Transport Layer Security (DTLS) packet reordering logic. The comparator function, responsible for ordering DTLS packets by sequence numbers, did not correctly handle packets with duplicate sequence numbers. This could lead to unstable packet ordering or undefined behavior, resulting in a denial of service.
7.5 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64 | — |
Vendor Fix
fix
|
|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64 | — |
Vendor Fix
fix
|
Threats
Impact
Important
A flaw was found in gnutls. Servers configured with RSA-PSK (Rivest–Shamir–Adleman – Pre-Shared Key) wrongfully matched usernames containing a NUL character with truncated usernames. A remote attacker could exploit this by sending a specially crafted username, leading to an authentication bypass. This vulnerability allows an attacker to gain unauthorized access by circumventing the authentication process.
7.1 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64 | — |
Vendor Fix
fix
|
|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64 | — |
Vendor Fix
fix
|
Threats
Impact
Important
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.
9.1 (Critical)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). The temperature validation gates, which use comparison operators, incorrectly handle Not-a-Number (NaN) and positive Infinity values in Python's IEEE 754 float semantics. These invalid values can bypass validation and propagate to GPU sampling kernels, leading to undefined behavior or CUDA errors that can crash the inference worker. This could allow an attacker to cause a Denial of Service (DoS) by providing specially crafted input.
6.5 (Medium)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Moderate
A flaw was found in Starlette where the request.form() method silently ignores configured resource limits (max_fields and max_part_size) when parsing application/x-www-form-urlencoded data. An unauthenticated attacker can exploit this by sending a urlencoded request body with an arbitrarily large number of fields or an oversized field, causing denial of service through resource exhaustion.
7.5 (High)
Affected products
Fixed
2 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64 | — |
Vendor Fix
fix
Workaround
|
|
| Unresolved product id: Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64 | — |
Vendor Fix
fix
Workaround
|
Threats
Impact
Important
References
85 references
Acknowledgments
AISLE Research Team
Joshua Rogers
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{
"category": "summary",
"text": "giflib: giflib: Denial of Service via buffer overflow in EGifGCBToExtension",
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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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"text": "A flaw in GnuTLS DTLS handshake parsing allows malformed fragments with zero length and non-zero offset, leading to an integer underflow during reassembly and resulting in an out-of-bounds read. This issue is remotely exploitable and may cause information disclosure or denial of service.",
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"text": "gnutls: GnuTLS: Denial of Service via DTLS zero-length fragment",
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{
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"text": "This issue marked as Important severity due to its remote, pre-authentication reachability and its impact on a critical DTLS handshake parsing path. The vulnerability can be triggered by an unauthenticated attacker sending crafted DTLS handshake fragments, requiring no prior access or interaction. It leads to an out-of-bounds read caused by an integer underflow in fragment reassembly, operating entirely on attacker-controlled input. Such flaws in low-level protocol parsing are particularly serious, as they may result in disclosure of sensitive process memory, including cryptographic or session-related data, and can also cause reliable application crashes leading to denial of service. Given that DTLS is commonly used in network-facing services such as VPNs and real-time communication systems, the exposure surface is broad. The combination of unauthenticated remote exploitation, memory safety violation, and potential confidentiality and availability impact justifies classifying this issue as high severity rather than moderate.",
"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": "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",
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"category": "external",
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{
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"cwe": {
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},
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"category": "description",
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"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"
}
],
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},
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"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-34982"
},
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"category": "external",
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"category": "external",
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"category": "external",
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"name": "Reachable Assertion"
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{
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"title": "Vulnerability summary"
},
{
"category": "other",
"text": "Red Hat rates this issue as having Important impact for Red Hat AI Inference Server and Red Hat OpenShift AI vLLM serving images, and Moderate impact for Red Hat Enterprise Linux AI bootc images that bundle vLLM. Exploitation requires loading an untrusted HuggingFace cross-encoder model while the vLLM process runs with Python optimized mode (python -O or PYTHONOPTIMIZE=1). Red Hat AI Inference Server 3.2/3.3 images and other components without the vulnerable pooler activation loader (vLLM \u003c 0.14.0) are not affected.",
"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 summary"
},
{
"category": "other",
"text": "The impact for this flaw has been downgraded on Red Hat Enterprise Linux due to the following reason:\n\n- The number of elements passed to the vulnerable function at runtime is known and is at most 6 and the element size is sufficiently small. glibc\u2019s qsort implementation will not exercise the quick sort code path, which would otherwise cause an infloop or out-of-bound write.",
"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-2026-42009"
},
{
"category": "external",
"summary": "https://www.gnutls.org/security-new.html#GNUTLS-SA-2026-04-29-2",
"url": "https://www.gnutls.org/security-new.html#GNUTLS-SA-2026-04-29-2"
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"scope": "UNCHANGED",
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{
"system_name": "Red Hat Bugzilla ID",
"text": "2467289"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in gnutls. Servers configured with RSA-PSK (Rivest\u2013Shamir\u2013Adleman \u2013 Pre-Shared Key) wrongfully matched usernames containing a NUL character with truncated usernames. A remote attacker could exploit this by sending a specially crafted username, leading to an authentication bypass. This vulnerability allows an attacker to gain unauthorized access by circumventing the authentication process.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "gnutls: gnutls: Authentication Bypass via NUL Character in Username",
"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": [
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64",
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64"
]
},
"references": [
{
"category": "self",
"summary": "Canonical URL",
"url": "https://access.redhat.com/security/cve/CVE-2026-42010"
},
{
"category": "external",
"summary": "RHBZ#2467289",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2467289"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-42010",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-42010"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-42010",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-42010"
},
{
"category": "external",
"summary": "https://www.gnutls.org/security-new.html#GNUTLS-SA-2026-04-29-4",
"url": "https://www.gnutls.org/security-new.html#GNUTLS-SA-2026-04-29-4"
}
],
"release_date": "2026-04-29T00:00:00+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-07-06T16:43:22+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:36005",
"product_ids": [
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64",
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64"
],
"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:36005"
}
],
"scores": [
{
"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 7.1,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "LOW",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N",
"version": "3.1"
},
"products": [
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64",
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64"
]
}
],
"threats": [
{
"category": "impact",
"details": "Important"
}
],
"title": "gnutls: gnutls: Authentication Bypass via NUL Character in Username"
},
{
"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 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64",
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64"
]
},
"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": "2026-07-06T16:43:22+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:36005",
"product_ids": [
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64",
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64"
],
"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:36005"
},
{
"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 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64",
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]
}
],
"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": [
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"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64"
]
}
],
"threats": [
{
"category": "impact",
"details": "Important"
}
],
"title": "vllm: starlette: vLLM: Critical authentication bypass allows unauthorized API access"
},
{
"cve": "CVE-2026-54235",
"cwe": {
"id": "CWE-1287",
"name": "Improper Validation of Specified Type of Input"
},
"discovery_date": "2026-06-22T23:01:07.102249+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2491584"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). The temperature validation gates, which use comparison operators, incorrectly handle Not-a-Number (NaN) and positive Infinity values in Python\u0027s IEEE 754 float semantics. These invalid values can bypass validation and propagate to GPU sampling kernels, leading to undefined behavior or CUDA errors that can crash the inference worker. This could allow an attacker to cause a Denial of Service (DoS) by providing specially crafted input.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "vllm: vLLM: Denial of Service due to improper floating-point validation",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "This Moderate impact flaw in vLLM, as used in Red Hat AI Inference Server, Red Hat OpenShift AI, and Red Hat Enterprise Linux AI, allows for a denial of service. Improper validation of floating-point values like Not-a-Number (NaN) or positive Infinity in temperature parameters can bypass security checks, leading to undefined behavior or CUDA errors that crash the inference worker. This could be exploited by providing specially crafted input to the LLM inference engine.",
"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 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64",
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64"
]
},
"references": [
{
"category": "self",
"summary": "Canonical URL",
"url": "https://access.redhat.com/security/cve/CVE-2026-54235"
},
{
"category": "external",
"summary": "RHBZ#2491584",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2491584"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-54235",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-54235"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-54235",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-54235"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/commit/d598d239737cfa37bcfcb98886ec3f3557fc7198",
"url": "https://github.com/vllm-project/vllm/commit/d598d239737cfa37bcfcb98886ec3f3557fc7198"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/pull/45116",
"url": "https://github.com/vllm-project/vllm/pull/45116"
},
{
"category": "external",
"summary": "https://github.com/vllm-project/vllm/security/advisories/GHSA-7h4p-rffg-7823",
"url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-7h4p-rffg-7823"
}
],
"release_date": "2026-06-22T21:59:02.710000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-07-06T16:43:22+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:36005",
"product_ids": [
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"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64"
],
"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:36005"
},
{
"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 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64",
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64"
]
}
],
"scores": [
{
"cvss_v3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "LOW",
"baseScore": 6.5,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:L",
"version": "3.1"
},
"products": [
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64",
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64"
]
}
],
"threats": [
{
"category": "impact",
"details": "Moderate"
}
],
"title": "vllm: vLLM: Denial of Service due to improper floating-point validation"
},
{
"cve": "CVE-2026-54283",
"cwe": {
"id": "CWE-770",
"name": "Allocation of Resources Without Limits or Throttling"
},
"discovery_date": "2026-06-22T18:01:06.194658+00:00",
"ids": [
{
"system_name": "Red Hat Bugzilla ID",
"text": "2491440"
}
],
"notes": [
{
"category": "description",
"text": "A flaw was found in Starlette where the request.form() method silently ignores configured resource limits (max_fields and max_part_size) when parsing application/x-www-form-urlencoded data. An unauthenticated attacker can exploit this by sending a urlencoded request body with an arbitrarily large number of fields or an oversized field, causing denial of service through resource exhaustion.",
"title": "Vulnerability description"
},
{
"category": "summary",
"text": "starlette: Starlette: request.form() limits silently ignored for application/x-www-form-urlencoded enable DoS",
"title": "Vulnerability summary"
},
{
"category": "other",
"text": "A flaw was found in Starlette where the request.form() method silently ignores configured resource limits (max_fields and max_part_size) when parsing application/x-www-form-urlencoded data. An unauthenticated attacker can exploit this by sending a urlencoded request body with an arbitrarily large number of fields or an oversized field, causing denial of service through resource exhaustion. This only affects applications that explicitly call request.form() on urlencoded input; JSON-only APIs and services where Starlette is a transitive dependency not used for form parsing are not affected.",
"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 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64",
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64"
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},
"references": [
{
"category": "self",
"summary": "Canonical URL",
"url": "https://access.redhat.com/security/cve/CVE-2026-54283"
},
{
"category": "external",
"summary": "RHBZ#2491440",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2491440"
},
{
"category": "external",
"summary": "https://www.cve.org/CVERecord?id=CVE-2026-54283",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-54283"
},
{
"category": "external",
"summary": "https://nvd.nist.gov/vuln/detail/CVE-2026-54283",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-54283"
},
{
"category": "external",
"summary": "https://github.com/Kludex/starlette/security/advisories/GHSA-82w8-qh3p-5jfq",
"url": "https://github.com/Kludex/starlette/security/advisories/GHSA-82w8-qh3p-5jfq"
}
],
"release_date": "2026-06-22T16:46:16.706000+00:00",
"remediations": [
{
"category": "vendor_fix",
"date": "2026-07-06T16:43:22+00:00",
"details": "For more information visit https://access.redhat.com/errata/RHSA-2026:36005",
"product_ids": [
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"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64"
],
"restart_required": {
"category": "none"
},
"url": "https://access.redhat.com/errata/RHSA-2026:36005"
},
{
"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 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64",
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64"
]
}
],
"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": [
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:6b93986199cc8e02e9672374938a2aac7b7452d1bf7d1a8a6445bfe1940f6328_amd64",
"Red Hat AI Inference Server 3.2:registry.redhat.io/rhaiis/vllm-cuda-rhel9@sha256:9533230dd9b2ab392c96f4e8a556ddbebf0be308befdf92691dc7e228da361bf_arm64"
]
}
],
"threats": [
{
"category": "impact",
"details": "Important"
}
],
"title": "starlette: Starlette: request.form() limits silently ignored for application/x-www-form-urlencoded enable DoS"
}
]
}
Loading…
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
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.
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