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
- Confirm the exact error signature matches
CRITICAL: Malicious litellm_init.pth in litellm 1.82.8 — credential stealer (supply chain compromise). - Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
- 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
- Capture the exact error message and the command, editor action, or request that triggered it.
- Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
- Review the source evidence below and compare it with your environment.
- Apply one change at a time and rerun the smallest failing action.
- 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.