AI Sec Watch: A Security Intelligence Platform for AI Systems

Luu, T.J.

HighVulnerabilityLLM-specific

GHSA-fjcf-3j3r-78rp: LiteLLM Has an Improper Authorization Vulnerability

Source: GitHub Advisory(opens in a new tab)
Identifiers: CVE-2025-0628GHSA-fjcf-3j3r-78rp
Published: March 20, 2025
Record updated: October 10, 2026

View JSON

Affected: litellm < 1.61.15
Fixed in: 1.61.15
Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.3%

Summary

An improper authorization flaw in the main-latest version of BerriAI/litellm gives a user with the role 'internal_user_viewer' an overly privileged API key when they log in. That key reaches admin functionality, including endpoints such as '/users/list' and '/users/get_users'. The result is privilege escalation that lets any account become a PROXY ADMIN.

Mitigation

The source does not state a fix yet. Check the original advisory for updates.

Details

Scores and exploitation

CVSS score: 8.1(high)
Patch available: Yes
CVSS vector: CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:N
Attack vector: network
Attack complexity: low
Privileges required: low
User interaction: none
EPSS: 0.3%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on October 10, 2026.
Disclosure date: March 20, 2025

Weaknesses and techniques

Weakness (CWE): CWE-266
CWE-285

Affected

Packages: litellm@< 1.61.15 (fixed: 1.61.15)

Classification

Attack type: Other
Attack sophistication: Trivial
AI component targeted: API
Impact: Confidentiality,
Integrity
Labels: security

How this record was produced

Summaries, mitigations and labels on this page are generated automatically from the source. The linked source is authoritative.

Original source: https://github.com/advisories/GHSA-fjcf-3j3r-78rp

First tracked: October 10, 2026 at 12:53 AM ET, from GitHub Advisory Database

Classifier: claude-haiku-5-5, prompt v4

Classifier confidence: 95% (self-assessed)

Affected packages in the Exposure Registry

Matched by package name and ecosystem. Each entry shows whether the package delegates to a language model and how many tracked packages depend on it.

litellmPyPILLM dependency since 2023-07-27 · 54 tracked dependents

Summary

Mitigation

Affected packages in the Exposure Registry

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