LiteLLM Leaks Full SHA-256 Token Hash in 429 Rate Limit Error Messages

What this error means

Rate limit exceeded for api_key: <sha256_hash>. Limit type: parallel_request_limit is a LiteLLM failure pattern reported for developers trying to fix litellm rate limit error exposing api key hash in response body. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

LiteLLM parallel_request_limiter_v3.py line ~1261 includes full token hash in 429 response detail. When descriptor_key is ‘api_key’, descriptor_value is the SHA-256 hash from /key/generate. Visible to any HTTP client hitting rate limit. redact_user_api_key_info doesn’t cover this path.

Common causes

• When parallel request limiter returns 429, the error body includes the full 64-character SHA-256 hash of the virtual key. redact_user_api_key_info setting doesn’t affect this code path. Security concern for proxy deployments.
• LiteLLM parallel_request_limiter_v3.py line ~1261 includes full token hash in 429 response detail. When descriptor_key is ‘api_key’, descriptor_value is the SHA-256 hash from /key/generate. Visible to any HTTP client hitting rate limit. redact_user_api_key_info doesn’t cover this path.

Quick fixes

1. Confirm the exact error signature matches Rate limit exceeded for api_key: <sha256_hash>. Limit type: parallel_request_limit.
2. Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
3. 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

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.

Sources checked

• https://github.com/BerriAI/litellm/issues/27884

Evidence note: LiteLLM parallel_request_limiter_v3.py line ~1261 includes full token hash in 429 response detail. When descriptor_key is ‘api_key’, descriptor_value is the SHA-256 hash from /key/generate. Visible to any HTTP client hitting rate limit. redact_user_api_key_info doesn’t cover this path.

Related errors

• LiteLLM 429 response leaks token
• LiteLLM rate limit error message redaction
• LiteLLM parallel request limiter security

FAQ

What should I check first?

Start with the exact Rate limit exceeded for api_key: <sha256_hash>. Limit type: parallel_request_limit text and the smallest action that reproduces it.

Can I ignore this error?

No. Treat it as a failed LiteLLM workflow until the root cause is understood.

Is this guaranteed to have one fix?

No. The imported evidence supports the troubleshooting path above, but tool behavior can vary by account, plan, version, provider, and local configuration.

How do I know the fix worked?

Rerun the same command, editor action, or request. The fix is working when that action completes without Rate limit exceeded for api_key: <sha256_hash>. Limit type: parallel_request_limit.