What this error means
LiteLLM rate limit error message body leaks full SHA-256 token hash on 429 responses is a LiteLLM failure pattern reported for developers trying to fix litellm 429 error response leaking token hash in rate limit error message. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
GitHub issue #27884 reports that when the parallel request limiter returns a 429, the full SHA-256 hash of the API token is included in the error message body. This leaks sensitive token information to logs, monitoring, and potentially end users.
Common causes
- When LiteLLM's parallel request limiter returns a 429 response, the error message body contains the full SHA-256 hash of the API token. This is a credential leak that exposes sensitive token information in logs, error outputs, and monitoring systems. Enterprise users relying on LiteLLM proxy for key management are affected.
- GitHub issue #27884 reports that when the parallel request limiter returns a 429, the full SHA-256 hash of the API token is included in the error message body. This leaks sensitive token information to logs, monitoring, and potentially end users.
Quick fixes
- Confirm the exact error signature matches
LiteLLM rate limit error message body leaks full SHA-256 token hash on 429 responses. - Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
- Reduce request pressure, check quota or plan limits, and retry with backoff instead of immediate repeated requests.
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.