CVE-2024-9606
Published: 20 March 2025
Description
Adversaries may search local file systems and remote file shares for files containing insecurely stored credentials.
Security Summary
CVE-2024-9606 is a logging vulnerability in the berriai/litellm Python library, specifically affecting versions before 1.44.12, with the issue confirmed in v1.44.9. Located in the file `litellm/litellm_core_utils/litellm_logging.py`, the flaw stems from API key masking logic that obscures only the first five characters of the key, resulting in logs that expose nearly the entire secret. This improper output neutralization (CWE-116) and improper encoding (CWE-117) carries a CVSS v3.1 base score of 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N), highlighting high confidentiality impact.
The vulnerability enables exploitation by any attacker who gains access to the application's logs, such as through log aggregation systems, shared storage, or compromised logging endpoints. No privileges, user interaction, or special conditions are required beyond log visibility, which is often granted to developers, operators, or external monitoring services. Successful exploitation allows extraction of almost complete API keys, potentially granting unauthorized access to downstream services proxied by LiteLLM, such as LLM providers, leading to unauthorized API usage, data exfiltration, or further compromise.
Mitigation is addressed in the GitHub commit 9094071c4782183e84f10630e2450be3db55509a, which fixes the masking logic in LiteLLM version 1.44.12 and later. Security practitioners should upgrade affected installations immediately and review historical logs for exposed keys. The issue was reported via Huntr (bounty ID 4a03796f-a8d4-4293-84ef-d3959456223a), emphasizing proactive auditing of logging mechanisms in LLM proxy deployments.
Details
- CWE(s)
Affected Products
AI Security Analysis
- AI Category
- APIs and Models
- Risk Domain
- Privacy and Disclosure
- OWASP Top 10 for LLMs 2025
- None mapped
- MITRE ATLAS Techniques
- None mapped
- Classification Reason
- LiteLLM (berriai/litellm) is a library providing a unified SDK for calling 100+ LLM APIs (e.g., OpenAI, Anthropic), making it directly related to APIs and models in the AI ecosystem.
MITRE ATT&CK Enterprise Techniques
Why these techniques?
The vulnerability leaks nearly full API keys in application logs due to improper masking, facilitating theft of application access tokens (T1528) and unsecured credentials in files (T1552.001).