T05 · Unauthorized Access and Privilege Escalation
Warning
- Location
- pipeline-mcp.yaml:27
- Finding
- Unauthenticated Network-Exposed OpenAI Inference Endpoint<![CDATA[ ## Vulnerability Details **File Location**: `pipeline-mcp.yaml:27-34` and `pipeline-mcp.yaml:70-73` **Vulnerability Type**: Missing authentication and unrestricted network binding **Risk Level**: Medium ### Vulnerable Code ```yaml http: enabled: true address: "0.0.0.0:${PORT:-8080}" input: http_server: path: /summarize allowed_verbs: [POST] timeout: 60s ``` ```yaml - openai_chat_completion: api_key: "${OPENAI_API_KEY}" model: gpt-4o-mini ``` ### Technical Analysis The MCP pipeline binds its HTTP server to `0.0.0.0`, making it listen on every available network interface. The `/summarize` endpoint does not enforce authentication or authorization, and the configuration contains no rate limiting. Every accepted request invokes OpenAI using the API key supplied by the service operator. Consequently, any party able to reach the listening port can consume the operator's OpenAI quota without possessing that credential. The pipeline limits individual input text to 1 MB and applies a 60-second request timeout, but these controls do not prevent repeated or concurrent requests. Actual external exposure depends on host firewalls, container port mappings, cloud security groups, and surrounding network controls. ### Attack Path 1. An operator configures `OPENAI_API_KEY` and starts `pipeline-mcp.yaml`. 2. The service listens on port 8080, or the configured `PORT`, across all network interfaces. 3. A remote party discovers or otherwise reaches the exposed port. 4. The party submits unauthenticated `POST` requests to `/summarize` containing attacker-selected text. 5. The pipeline forwards each accepted request to OpenAI using the operator's API key. 6. The attacker repeats requests or sends requests concurrently, consuming API quota and service resources. ### Impact Assessment An attacker can invoke the summarization service and receive generated responses without authorization. This can result in: - Unauthorized consumption of th ...[truncated 563 chars]
- Remediation
- <![CDATA[ ## Remediation Suggestions 1. Bind the service to the loopback interface by default: ```yaml http: enabled: true address: "127.0.0.1:${PORT:-8080}" ``` 2. If remote access is required, place the endpoint behind an authenticated reverse proxy or API gateway. Require a strong API token, mutual TLS, or another appropriate identity mechanism. 3. Enforce authorization so only explicitly approved clients can invoke the endpoint. 4. Add per-client and global rate limits, concurrency limits, request quotas, and OpenAI spending alerts. 5. Use TLS for all non-loopback traffic to prevent interception or modification in transit. 6. Restrict network exposure with host firewalls, container networking rules, cloud security groups, or private-network access controls. 7. Apply tighter input and generated-token limits based on expected use rather than relying only on the existing 1 MB body-size check. 8. Return generic error messages and monitor failed authentication, unusual request volume, latency, and quota consumption. ]]>