CVE-2026-31949
Librechat ≤ 0.8.3
Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:HSummary
CVE-2026-31949 is a medium-severity Uncaught Exception (CWE-248) vulnerability in Librechat Librechat. Its CVSS base score is 6.5 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Endpoint Denial of Service (T1499); ranked at the 31th 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; in the Other ATLAS/OWASP Terms risk domain.
The strongest mitigations our analysis identified map to SA-8 (Security and Privacy Engineering Principles) and SC-24 (Fail in Known State) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-12093
Vulnerability Data
LibreChat is a ChatGPT clone with additional features. Prior to 0.8.3-rc1, a Denial of Service (DoS) vulnerability exists in the DELETE /api/convos endpoint that allows an authenticated attacker to crash the Node.js server process by sending malformed requests. The DELETE…
more
/api/convos route handler attempts to destructure req.body.arg without validating that it exists. The server crashes due to an unhandled TypeError that bypasses Express error handling middleware and triggers process.exit(1). This vulnerability is fixed in 0.8.3-rc1.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: chatgpt, librechat
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Security engineering principles include robust exception management to keep the system in a defined state.
Fail-in-known-state reduces the impact when an uncaught exception occurs by preserving a safe condition.
Error handling requirements force structured catching and response to exceptions instead of allowing them to propagate uncaught.
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.
Secure SDLC practices explicitly require structured exception handling to prevent uncaught exceptions from reaching production.
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 uncaught exceptions before production deployment.
Secure development lifecycle includes exception-handling standards that reduce uncaught exceptions.
Application security requirements typically mandate robust error and exception handling.
Secure architecture principles call for centralized, comprehensive exception management.
Secure coding standards directly require catching and handling exceptions to prevent crashes or leaks.