CVE-2024-3029
Published: 16 April 2024
Summary
CVE-2024-3029 is a high-severity Improper Input Validation (CWE-20) vulnerability in Mintplexlabs Anythingllm. Its CVSS base score is 8.0 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Create Account (T1136); ranked at the 42.9th 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 Enterprise AI Assistants; in the Other ATLAS/OWASP Terms risk domain.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-31637
Vulnerability details
In mintplex-labs/anything-llm, an attacker can exploit improper input validation by sending a malformed JSON payload to the '/system/enable-multi-user' endpoint. This triggers an error that is caught by a catch block, which in turn deletes all users and disables the 'multi_user_mode'.…
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The vulnerability allows an attacker to remove all existing users and potentially create a new admin user without requiring a password, leading to unauthorized access and control over the application.
- 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
- mintplex-labs/anything-llm is an all-in-one AI/LLM application platform supporting multi-user modes, local/cloud LLM integration, and enterprise features, fitting 'Enterprise AI Assistants'. The vulnerability is in its API endpoint for multi-user management.
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Vulnerability in public-facing endpoint enables exploitation (T1190), deletion of all user accounts (T1531), and potential creation of new admin account without password (T1136).
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.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Directly implements checks on information inputs to reject invalid data before processing.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.