Cyber Resilience

CVE-2024-11169

Librechat ≤ 0.7.6

Public PoC
Published
20 March 2025
Modified
15 July 2025
Patch / advisory
CVSS Score v3 7.5
Click a component to see what it means
Raw vectorCVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
EPSS Score 0.0086 55th percentile
Risk Priority 59 floored blend · peak EPSS

Summary

CVE-2024-11169 is a high-severity Misinterpretation of Input (CWE-115) vulnerability in Librechat Librechat. Its CVSS base score is 7.5 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Masquerading (T1036); ranked in the top 45% of CVEs by exploit likelihood; 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 Supply Chain and Deployment risk domain.

The strongest mitigations our analysis identified map to SI-10 (Information Input Validation) — see the control section below for these in your framework.

OWASP Top 10 for Web (2025)

EU & UK References

Vulnerability Data

An unhandled exception in danny-avila/librechat version 3c94ff2 can lead to a server crash. The issue occurs when the fs module throws an exception while handling file uploads. An unauthenticated user can trigger this exception by sending a specially crafted request,…

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causing the server to crash. The vulnerability is fixed in version 0.7.6.

CWE(s)

AI Security AnalysisAI

AI Category
LLM Application Platforms
Risk Domain
Supply Chain and Deployment
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
Matched keywords: librechat

Related Threats

MITRE ATT&CK Enterprise Techniques

T1036 Masquerading Stealth
Adversaries may attempt to manipulate features of their artifacts to make them appear legitimate or benign to users and/or security tools.
T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
T1204 User Execution Execution
An adversary may rely upon specific actions by a user in order to gain execution.
T1221 Template Injection Stealth
Adversaries may create or modify references in user document templates to conceal malicious code or force authentication attempts.
T1659 Content Injection Initial Access
Adversaries may gain access and continuously communicate with victims by injecting malicious content into systems through online network traffic.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2026-54025Same product: Librechat Librechat
CVE-2025-66452Same product: Librechat Librechat
CVE-2024-10366Same product: Librechat Librechat
CVE-2026-54033Same product: Librechat Librechat
CVE-2024-11167Same product: Librechat Librechat
CVE-2024-10361Same product: Librechat Librechat
CVE-2026-34371Same product: Librechat Librechat
CVE-2026-31945Same product: Librechat Librechat
CVE-2025-69222Same product: Librechat Librechat
CVE-2026-31943Same product: Librechat Librechat

Affected Assets

librechat
librechat
≤ 0.7.6

Mitigating Controls

Mitigating Controls (NIST 800-53 r5) AI

Input validation directly stops the system from accepting and acting on misinterpreted data values.

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.

PR.PS-06 mostly match
prevents

Secure SDLC practices directly require correct input parsing/validation to avoid misinterpretation flaws.

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.

finds

Security testing can detect input misinterpretation flaws but does not itself implement the preventive controls.

prevents

Secure development lifecycle mandates input validation and canonicalization that directly prevent misinterpretation of inputs.

prevents

Application security requirements explicitly call for robust input handling and sanitization to avoid misinterpretation.

prevents

Secure architecture principles include defensive input processing and error handling that reduce misinterpretation risks.

prevents

Secure coding standards require strict input validation and canonical forms to eliminate misinterpretation vulnerabilities.

References