CVE-2026-85666 (GCVE-0-2026-85666)
Vulnerability from cvelistv5 – Published: 2026-09-04 14:32 – Updated: 2026-09-14 19:33
VLAI
EPSS
VEX
Title
ogx 1.3.1 Server-Side Request Forgery via MCP tool server_url
Summary
OGX (formerly Llama Stack, affected at commit fbe8e0f) contains an unauthenticated server-side request forgery vulnerability in the OpenAI-compatible POST /v1/responses endpoint. MCP tool definitions accept a server_url parameter (along with headers and authorization values) that is fetched server-side without destination validation; the existing validate_url_not_private() guard used for other URL inputs is not applied to server_url. On the default starter configuration, which runs without authentication, a remote unauthenticated attacker can cause the server to open connections to arbitrary internal addresses (including cloud metadata endpoints such as http://169.254.169.254/) and forward attacker-supplied headers and bearer tokens to those destinations.
Severity
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-14 19:20 UTC
CWE
- CWE-918 - Server-Side Request Forgery (SSRF)
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://github.com/ogx-ai/ogx/issues/6287 | issue-tracking |
| https://github.com/ogx-ai/ogx | product |
| https://github.com/ogx-ai/ogx/blob/v1.3.1/src/ogx… | technical-description |
| https://www.vulncheck.com/advisories/ogx-1.3.1-se… | third-party-advisory |
Impacted products
Date Public
2026-07-13 00:00
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Sightings
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|---|
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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.
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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.