CVE-2024-22422
Published: 19 January 2024
Summary
CVE-2024-22422 is a high-severity Improper Check for Unusual or Exceptional Conditions (CWE-754) vulnerability in Mintplexlabs Anythingllm. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Application or System Exploitation (T1499.004); ranked in the top 14.2% 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 Enterprise AI Assistants; in the Other ATLAS/OWASP Terms risk domain; MITRE ATLAS techniques in scope: External Harms (AML.T0048).
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-19968
Vulnerability details
AnythingLLM is an application that turns any document, resource, or piece of content into context that any LLM can use as references during chatting. In versions prior to commit `08d33cfd8` an unauthenticated API route (file export) can allow attacker to…
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crash the server resulting in a denial of service attack. The “data-export” endpoint is used to export files using the filename parameter as user input. The endpoint takes the user input, filters it to avoid directory traversal attacks, fetches the file from the server, and afterwards deletes it. An attacker can trick the input filter mechanism to point to the current directory, and while attempting to delete it the server will crash as there is no error-handling wrapper around it. Moreover, the endpoint is public and does not require any form of authentication, resulting in an unauthenticated Denial of Service issue, which crashes the instance using a single HTTP packet. This issue has been addressed in commit `08d33cfd8`. Users are advised to upgrade. There are no known workarounds for this vulnerability.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Enterprise AI Assistants
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- AnythingLLM is an application that provides document context to LLMs for chatting, functioning as an enterprise AI assistant platform.
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
The unauthenticated API endpoint vulnerability enables attackers to crash the server application via a tricked filename parameter leading to failed deletion without error handling, directly facilitating endpoint denial of service through application exploitation.
MITRE ATLAS TechniquesAI
MITRE ATLAS techniques
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Requires detection and response to audit logging failures as an unusual or exceptional condition.
Implements detection of unusual or exceptional conditions followed by safe mode entry, reducing the window for exploitation of unchecked conditions.
Training ensures users perform required checks for unusual or exceptional conditions as part of contingency roles, limiting attacker leverage from skipped validations.
IR testing directly validates checks for unusual or exceptional conditions that could indicate security incidents.
Requires ongoing monitoring of organization-defined metrics and analysis, enabling checks for unusual or exceptional conditions.
Security testing routinely checks for unusual or exceptional inputs/conditions, identifying missing validation steps that flaw remediation then resolves.
Requires detection of unusual conditions followed by a controlled transition to the defined failure state.
MTTF determination forces explicit checks for conditions that precede predictable component failure.