UBUNTU-CVE-2026-57161 (CVE-2026-57161)
Vulnerability from osv_ubuntu – Published: 2026-09-04 18:17 – Updated: 2026-09-16 11:36 – Source website
VLAI
Details
PJSIP is a free and open source multimedia communication library written in C. Prior to commit acc03b5, a stack buffer overflow exists in PJSUA when processing Service-Route headers in a registration response (update_service_route() in pjsua_acc.c). This affects applications that register using the PJSUA/PJSUA2 account API (the default registration path). The Service-Route URIs from a 2xx response to REGISTER are stored into a fixed-size array without bounding the number of headers; a registrar that returns an excessive number of Service-Route headers can write past the end of the array on the stack. The values written are internal pointers rather than arbitrary data, so the most likely impact is unexpected application termination (denial of service), though memory corruption cannot be excluded. The malicious response may come from a compromised or malicious registrar, or — over unprotected transports — a spoofed response. This issue has been patched via commit acc03b5.
Severity
8.2 (High)
N/A (UNKNOWN)
References
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"aliases": [],
"details": "PJSIP is a free and open source multimedia communication library written in C. Prior to commit acc03b5, a stack buffer overflow exists in PJSUA when processing Service-Route headers in a registration response (update_service_route() in pjsua_acc.c). This affects applications that register using the PJSUA/PJSUA2 account API (the default registration path). The Service-Route URIs from a 2xx response to REGISTER are stored into a fixed-size array without bounding the number of headers; a registrar that returns an excessive number of Service-Route headers can write past the end of the array on the stack. The values written are internal pointers rather than arbitrary data, so the most likely impact is unexpected application termination (denial of service), though memory corruption cannot be excluded. The malicious response may come from a compromised or malicious registrar, or \u2014 over unprotected transports \u2014 a spoofed response. This issue has been patched via commit acc03b5.",
"id": "UBUNTU-CVE-2026-57161",
"modified": "2026-09-16T11:36:41Z",
"published": "2026-09-04T18:17:00Z",
"references": [
{
"type": "REPORT",
"url": "https://ubuntu.com/security/CVE-2026-57161"
},
{
"type": "REPORT",
"url": "https://www.cve.org/CVERecord?id=CVE-2026-57161"
},
{
"type": "REPORT",
"url": "https://github.com/pjsip/pjproject/security/advisories/GHSA-xc62-j9h2-mp84"
}
],
"related": [],
"schema_version": "1.7.0",
"severity": [
{
"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:L/VA:H/SC:N/SI:N/SA:N",
"type": "CVSS_V4"
},
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:H",
"type": "CVSS_V3"
},
{
"score": "medium",
"type": "Ubuntu"
}
],
"upstream": [
"CVE-2026-57161"
]
}
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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.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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