What this error means

CRITICAL: Malicious litellm_init.pth in litellm 1.82.8 — credential stealer (supply chain compromise) is a LiteLLM failure pattern reported for developers trying to check if installed litellm version is compromised, understand scope of credential theft, and remediate. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

487+ comments on the primary security issue. The malicious .pth file (34,628 bytes) was double base64-encoded, exfiltrating SSH keys, AWS credentials, kube configs, git credentials, and all environment variables to attacker-controlled server. Compromise originated from trivy security scan dependency. Packages deleted, Mandiant engaged.

Common causes

  • LiteLLM is a widely-used LLM proxy. Versions 1.82.7 and 1.82.8 on PyPI contained a malicious litellm_init.pth file that executed a credential-stealing script on every Python interpreter startup — stealing SSH keys, AWS credentials, Kubernetes configs, API keys, and environment variables. Developers using these versions need immediate remediation guidance.
  • 487+ comments on the primary security issue. The malicious .pth file (34,628 bytes) was double base64-encoded, exfiltrating SSH keys, AWS credentials, kube configs, git credentials, and all environment variables to attacker-controlled server. Compromise originated from trivy security scan dependency. Packages deleted, Mandiant engaged.

Quick fixes

  1. Confirm the exact error signature matches CRITICAL: Malicious litellm_init.pth in litellm 1.82.8 — credential stealer (supply chain compromise).
  2. Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
  3. Compare the failing environment with a known working setup, then change one configuration value at a time.

Platform/tool-specific checks

  • Verify the command, editor, extension, or API client that produced the error.
  • Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
  • Avoid deleting credentials, local model data, or project settings until the failing scope is clear.

Step-by-step troubleshooting

  1. Capture the exact error message and the command, editor action, or request that triggered it.
  2. Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
  3. Review the source evidence below and compare it with your environment.
  4. Apply one change at a time and rerun the smallest failing action.
  5. Keep the working fix documented for the team or deployment environment.

How to prevent it

  • Keep provider/tool configuration documented.
  • Record non-secret diagnostics such as tool version, provider name, model name, and command path.
  • Add a lightweight check before CI or production workflows depend on the tool.