CVE-2024-3283
Mintplexlabs Anythingllm ≤ 1.0.0
Raw vector
CVSS:3.0/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2024-3283 is a high-severity Improperly Controlled Modification of Dynamically-Determined Object Attributes (CWE-915) vulnerability in Mintplexlabs Anythingllm. Its CVSS base score is 7.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 42% 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.
The strongest mitigations our analysis identified map to AC-3 (Access Enforcement) and AC-6 (Least Privilege) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-31873
Vulnerability Data
A vulnerability in mintplex-labs/anything-llm allows users with manager roles to escalate their privileges to admin roles through a mass assignment issue. The '/admin/system-preferences' API endpoint improperly authorizes manager-level users to modify the 'multi_user_mode' system variable, enabling them to access the…
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'/api/system/enable-multi-user' endpoint and create a new admin user. This issue results from the endpoint accepting a full JSON object in the request body without proper validation of modifiable fields, leading to unauthorized modification of system settings and subsequent privilege escalation.
- 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
- The vulnerability affects mintplex-labs/anything-llm, an open-source multi-user LLM application/platform designed as an enterprise AI assistant for running and managing local/private LLMs with features like multi-user mode and admin privileges.
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Enforces authorizations so that only permitted attributes may be modified on an object.
Limits the set of modifiable attributes a subject is authorized to touch.
Validates incoming attribute names and values so that only explicitly allowed fields are accepted for update.
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 directly require allow-listing of mutable object attributes and input validation to block mass-assignment 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.
Secure coding standards explicitly forbid unsafe dynamic attribute assignment and require property allow-lists.
Security testing can detect mass-assignment flaws but does not itself prevent them at runtime.
Secure development lifecycle requires input validation and object-property whitelisting that directly mitigates mass-assignment risks.
Application security requirements include explicit rules for allowable object attributes and safe deserialization.
Secure architecture principles mandate strict control over dynamic object modification and attribute binding.
Information access restriction limits who can modify objects but does not address which attributes may be changed.