sure/docs/hosting/pipelock.md

Pipelock: AI Agent Security Proxy

Pipelock is an optional security proxy that scans AI agent traffic flowing through Sure. It protects against secret exfiltration, prompt injection, and tool poisoning.

What Pipelock does

Pipelock runs as a separate proxy service alongside Sure with two listeners:

Listener	Port	Direction	What it scans
Forward proxy	8888	Outbound (Sure to LLM)	DLP (secrets in prompts), response injection
MCP reverse proxy	8889	Inbound (agent to Sure /mcp)	Prompt injection, tool poisoning, DLP

Forward proxy (outbound)

When HTTPS_PROXY=http://pipelock:8888 is set, outbound HTTPS requests from Faraday-based clients (like ruby-openai) are routed through Pipelock. It scans request bodies for leaked secrets and response bodies for prompt injection.

Covered: OpenAI API calls via ruby-openai (uses Faraday). Not covered: SimpleFIN, Coinbase, Plaid, or anything using Net::HTTP/HTTParty directly. These bypass HTTPS_PROXY.

MCP reverse proxy (inbound)

External AI assistants that call Sure's /mcp endpoint should connect through Pipelock on port 8889 instead of directly to port 3000. Pipelock scans:

• Tool call arguments (DLP, shell obfuscation detection)
• Tool responses (injection payloads)
• Session binding (detects tool inventory manipulation)
• Tool call chains (multi-step attack patterns like recon then exfil)

Docker Compose setup

The compose.example.ai.yml file includes Pipelock. To use it:

1. Download the compose file and Pipelock config:

   curl -o compose.ai.yml https://raw.githubusercontent.com/we-promise/sure/main/compose.example.ai.yml
   curl -o pipelock.example.yaml https://raw.githubusercontent.com/we-promise/sure/main/pipelock.example.yaml
   

2. Start the stack:

   docker compose -f compose.ai.yml up -d
   

3. Verify Pipelock is healthy:

   docker compose -f compose.ai.yml ps pipelock
   # Should show "healthy"
   

Connecting external AI agents

External agents should use the MCP reverse proxy port:

http://your-server:8889

The agent must include the MCP_API_TOKEN as a Bearer token in requests. Set this in your .env:

MCP_API_TOKEN=generate-a-random-token
MCP_USER_EMAIL=your@email.com

Running without Pipelock

To use compose.example.ai.yml without Pipelock, remove the pipelock service and its depends_on entries from web and worker, then unset the proxy env vars (HTTPS_PROXY, HTTP_PROXY).

Or use the standard compose.example.yml which does not include Pipelock.

Helm (Kubernetes) setup

Enable Pipelock in your Helm values:

pipelock:
  enabled: true
  image:
    tag: "0.3.2"
  mode: balanced

This creates a separate Deployment, Service, and ConfigMap. The chart auto-injects HTTPS_PROXY/HTTP_PROXY/NO_PROXY into web and worker pods.

Exposing MCP to external agents (Kubernetes)

In Kubernetes, external agents cannot reach the MCP port by default. Enable the Pipelock Ingress:

pipelock:
  enabled: true
  ingress:
    enabled: true
    className: nginx
    hosts:
      - host: pipelock.example.com
        paths:
          - path: /
            pathType: Prefix
    tls:
      - hosts: [pipelock.example.com]
        secretName: pipelock-tls

Or port-forward for testing:

kubectl port-forward svc/sure-pipelock 8889:8889 -n sure

Monitoring

Enable the ServiceMonitor for Prometheus scraping:

pipelock:
  serviceMonitor:
    enabled: true
    interval: 30s
    additionalLabels:
      release: prometheus

Metrics are available at /metrics on the forward proxy port (8888).

Eviction protection

For production, enable the PodDisruptionBudget:

pipelock:
  pdb:
    enabled: true
    maxUnavailable: 1

See the Helm chart README for all configuration options.

Pipelock configuration file

The pipelock.example.yaml file (Docker Compose) or ConfigMap (Helm) controls scanning behavior. Key sections:

Section	What it controls
mode	strict (block threats), balanced (warn + block critical), audit (log only)
forward_proxy	Outbound HTTPS scanning (tunnel timeouts, idle timeouts)
dlp	Data loss prevention (scan env vars, built-in patterns)
response_scanning	Scan LLM responses for prompt injection
mcp_input_scanning	Scan inbound MCP requests
mcp_tool_scanning	Validate tool calls, detect drift
mcp_tool_policy	Pre-execution rules (shell obfuscation, etc.)
mcp_session_binding	Pin tool inventory, detect manipulation
tool_chain_detection	Multi-step attack patterns
websocket_proxy	WebSocket frame scanning (disabled by default)
logging	Output format (json/text), verbosity

For the Helm chart, most sections are configurable via values.yaml. For additional sections not covered by structured values (session profiling, data budgets, kill switch), use the extraConfig escape hatch:

pipelock:
  extraConfig:
    session_profiling:
      enabled: true
      max_sessions: 1000

Modes

Mode	Behavior	Use case
strict	Block all detected threats	Production with sensitive data
balanced	Warn on low-severity, block on high-severity	Default; good for most deployments
audit	Log everything, block nothing	Initial rollout, testing

Start with audit mode to see what Pipelock detects without blocking anything. Review the logs, then switch to balanced or strict.

Limitations

• Forward proxy only covers Faraday-based HTTP clients. Net::HTTP, HTTParty, and other libraries ignore HTTPS_PROXY.
• Docker Compose has no egress network policies. The /mcp endpoint on port 3000 is still reachable directly (auth token required). For enforcement, use Kubernetes NetworkPolicies.
• Pipelock scans text content. Binary payloads (images, file uploads) are passed through by default.

Troubleshooting

Pipelock container not starting

Check the config file is mounted correctly:

docker compose -f compose.ai.yml logs pipelock

Common issues:

• Missing pipelock.example.yaml file
• YAML syntax errors in config
• Port conflicts (8888 or 8889 already in use)

LLM calls failing with proxy errors

If AI chat stops working after enabling Pipelock:

# Check Pipelock logs for blocked requests
docker compose -f compose.ai.yml logs pipelock --tail=50

If requests are being incorrectly blocked, switch to audit mode in the config file and restart:

mode: audit

MCP requests not reaching Sure

Verify the MCP upstream is configured correctly:

# Test from inside the Pipelock container
docker compose -f compose.ai.yml exec pipelock /pipelock healthcheck --addr 127.0.0.1:8888

Check that MCP_API_TOKEN and MCP_USER_EMAIL are set in your .env file and that the email matches an existing Sure user.