Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2026-77776 is a critical-severity Authorization Bypass Through User-Controlled Key (CWE-639) vulnerability. Its CVSS base score is 9.3 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 28th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as LLM Application Platforms.
The strongest mitigations our analysis identified map to AC-24 (Access Control Decisions) and AC-3 (Access Enforcement) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-63905
Vulnerability Data
Headroom's LLM proxy derives the memory owner from the x-headroom-user-id request header. The header is read directly at several points in headroom/proxy/handlers/openai.py, including the chat completion and websocket paths, and nothing binds the value to the caller. A client can…
more
therefore name another user's identifier and read or write that user's stored LLM memory. The fix introduces a single resolve_memory_identity seam in headroom/proxy/identity.py that honors the header only for loopback or allowlisted callers and otherwise binds the identity to the proxy-token fingerprint or the operating system user. The pip console script binds 127.0.0.1 by default, but the reference docker-compose.yml ships --host 0.0.0.0 with published ports and no required HEADROOM_PROXY_TOKEN, which the server itself warns about at startup, so a deployment following the shipped compose exposes the affected data-plane routes to the network without authentication.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- N/A
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: llm, openai, llm
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Enforcing approved authorizations on every access request structurally stops a user-controlled key from reaching another user's data.
Requiring explicit access-control decisions on each request blocks unauthorized key-driven access.
Least-privilege restrictions limit the scope of data reachable even if a key check is bypassed.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Enforcing authorization policy and least privilege directly blocks user-controlled key tampering that bypasses access checks.
Logical access controls prevent unauthorized data access that results from missing authorization checks on object references.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing can detect missing authorization checks but does not prevent the weakness in production.
Information access restriction explicitly enforces that users may only retrieve data they are authorized to see, directly addressing user-controlled key bypass.
Access control policy directly requires enforcement of authorization rules that prevent unauthorized access via manipulated keys.
Managing access rights includes ensuring users can only access their own records and not bypass authorization by altering identifiers.
Privileged access rights control restricts what data each user may access, mitigating direct object reference attacks.
Secure development lifecycle includes authorization design but does not itself implement runtime access checks.