Affected: Crawl4AI

Crawl4AI before 0.8.8 contains credential exfiltration vulnerabilities in the Docker API server that allow attackers to redirect LLM API calls to attacker-controlled endpoints and read arbitrary environment variables. Attackers can exploit the unauthenticated /md, /llm, and /llm/job endpoints by supplying a malicious base_url parameter and setting api_token to env:VARIABLE_NAME to exfiltrate provider API keys and server secrets including JWT SECRET_KEY for authentication bypass.

Affected: PyPI: crawl4ai

### Summary

The Docker API server let a request control where LLM calls were sent and which environment variable an LLM token resolved from. Both could be abused to exfiltrate server-held secrets. The Docker API is unauthenticated by default.

### Vector 1 - attacker base_url

`/md`, `/llm`, and `/llm/job` accepted a `base_url` in the request and used it as the LLM endpoint while still attaching the server's configured provider API key. An attacker set `base_url` to a server they control and received the provider key (and any provider keys the server holds) in the inbound request.

### Vector 2 - arbitrary environment variable read via `env:`

`LLMConfig(api_token="env:NAME")` resolved `NAME` from the server environment with `os.getenv`. Because request bodies were deserialized into `LLMConfig` (via a crawler config / extraction strategy), an attacker could set `api_token="env:SECRET_KEY"` (or `env:REDIS_PASSWORD`, etc.) and, paired with an attacker `base_url`, exfiltrate that secret. Reading the server's `SECRET_KEY` enables forging authentication tokens.

### Impact

Disclosure of LLM provider API keys and other server secrets to an attacker-controlled endpoint; reading the JWT `SECRET_KEY` can lead to authentication bypass.

### Fix

- The LLM endpoints ignore a request-supplied `base_url`; the endpoint is always derived server-side from the provider name. The field is still accepted but no longer honored (no breaking 4xx). - `LLMConfig` refuses `env:` resolution of prot…