Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2024-4889 is a high-severity Code Injection (CWE-94) vulnerability in Litellm Litellm. Its CVSS base score is 7.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Command and Scripting Interpreter (T1059); 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 APIs and Models; in the Other ATLAS/OWASP Terms risk domain.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-44458
Vulnerability Data
A code injection vulnerability exists in the berriai/litellm application, version 1.34.6, due to the use of unvalidated input in the eval function within the secret management system. This vulnerability requires a valid Google KMS configuration file to be exploitable. Specifically,…
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by setting the `UI_LOGO_PATH` variable to a remote server address in the `get_image` function, an attacker can write a malicious Google KMS configuration file to the `cached_logo.jpg` file. This file can then be used to execute arbitrary code by assigning malicious code to the `SAVE_CONFIG_TO_DB` environment variable, leading to full system control. The vulnerability is contingent upon the use of the Google KMS feature.
- CWE(s)
AI Security AnalysisAI
- AI Category
- APIs and Models
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- LiteLLM (berriai/litellm) is a proxy server and Python SDK serving as a unified interface for calling APIs of 100+ LLMs, directly relating to APIs and models in the AI ecosystem. The vulnerability is in its secret management system, part of an AI/ML serving tool targeted by an AI/ML bug bounty platform (huntr).
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.3.1
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation finds code paths that accept and execute externally influenced strings.
Input validation directly stops untrusted data from being used to construct executable code without neutralization.
Least privilege limits the damage an injected code fragment can perform once executed.
Requiring documented secure development standards and tools enforces use of safe code-generation APIs and escaping.
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's SDLC practices directly target injection flaws via secure coding and testing (mostly), yet as a single broad outcome it leaves many code-generation specifics unaddressed (partial).
PR.DS-10 protects runtime data confidentiality/integrity but has no bearing on neutralizing externally influenced input during code generation, so neither direction shows any preventive effect.
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.
Banning unapproved code samples and unauthenticated web services, combined with secure-coding standards and SAST, prevents the dynamic generation or inclusion of attacker-supplied code.
Controls that restrict unauthorized or malicious code from being introduced via external networks or removable media limit opportunities for an attacker to inject and execute arbitrary code.