Cyber Posture

CVE-2024-9606

HighPublic PoC

Published: 20 March 2025

Published
20 March 2025
Modified
07 April 2025
KEV Added
Patch
CVSS Score 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
EPSS Score 0.0031 53.8th percentile
Risk Priority 15 60% EPSS · 20% KEV · 20% CVSS

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)
CWE-117CWE-116

Affected Products

litellm
litellm
≤ 1.44.12

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

T1528 Steal Application Access Token Credential Access
Adversaries can steal application access tokens as a means of acquiring credentials to access remote systems and resources.
T1552.001 Credentials In Files Credential Access
Adversaries may search local file systems and remote file shares for files containing insecurely stored credentials.
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).

References