How to Add Pre-Deploy AI Safety Checks

SafeClaw by Authensor provides a pre-deployment safety gate that validates your AI agent's policy configuration, runs simulation tests, and blocks deployment if any check fails. This ensures no agent reaches production with a misconfigured, overly permissive, or invalid safety policy. Install with npx @authensor/safeclaw and add a mandatory safety checkpoint to any CI/CD pipeline.

Prerequisites

• Any CI/CD system (GitHub Actions, GitLab CI, Jenkins, CircleCI, etc.)
• Node.js 18+
• SafeClaw initialized in your project with safeclaw.config.yaml

Step 1 — Install SafeClaw

npx @authensor/safeclaw

Zero dependencies, MIT-licensed, 446 tests. The validation and simulation commands run without making real API calls to your LLM provider.

Step 2 — The Three Pre-Deploy Checks

Every pre-deploy safety gate should run these three checks in order:

Check 1: Policy Validation

npx @authensor/safeclaw validate

This verifies:

• YAML syntax is correct


• All required fields are present


• defaultAction is set to deny


• Rules have valid action types and effects


• No conflicting rules exist


• Path patterns are well-formed

Check 2: Simulation Tests

npx @authensor/safeclaw test --simulation

This runs your agent in simulation mode, where every action is evaluated against the policy but never executed. It verifies:

• Expected legitimate actions are allowed


• Known dangerous actions are denied


• Edge cases are handled correctly


• The first-match-wins rule ordering produces the intended behavior

Check 3: Policy Strength Analysis

npx @authensor/safeclaw analyze

This checks your policy for common weaknesses:

• Are critical paths like /etc, ~/.ssh, and .env explicitly denied?


• Are shell execution rules sufficiently restrictive?


• Are network egress rules scoped to specific hosts?


• Does the policy block credential access?

Step 3 — Generic CI/CD Script

Create a reusable script that works in any CI system:

#!/bin/bash
scripts/pre-deploy-safety.sh
set -euo pipefail

echo "=== SafeClaw Pre-Deploy Safety Gate ==="

echo "[1/3] Validating policy..."
npx @authensor/safeclaw validate

echo "[2/3] Running simulation tests..."
npx @authensor/safeclaw test --simulation --output safety-report.json

echo "[3/3] Analyzing policy strength..."
npx @authensor/safeclaw analyze

echo "=== All safety checks passed ==="

Make it executable and call it from any CI system:

chmod +x scripts/pre-deploy-safety.sh
./scripts/pre-deploy-safety.sh

Step 4 — Platform-Specific Integrations

GitHub Actions

- name: Pre-deploy safety gate
  run: ./scripts/pre-deploy-safety.sh

GitLab CI

safety-gate:
  stage: safety
  script:
    - ./scripts/pre-deploy-safety.sh
  artifacts:
    paths:
      - safety-report.json

Jenkins

stage('Safety Gate') {
    steps {
        sh './scripts/pre-deploy-safety.sh'
        archiveArtifacts 'safety-report.json'
    }
}

CircleCI

- run:
    name: Pre-deploy safety gate
    command: ./scripts/pre-deploy-safety.sh

store_artifacts:
    path: safety-report.json

Step 5 — Block Deployment on Failure

The script uses set -euo pipefail, so any failed check exits with a non-zero code, which blocks the deployment stage in every CI system. Make the safety job a required dependency for deployment:

# GitHub Actions example
deploy:
  needs: [safety-gate, test]
  if: success()

Step 6 — Handle Policy Changes

When a PR modifies safeclaw.config.yaml, run additional checks:

#!/bin/bash
scripts/policy-change-check.sh
set -euo pipefail

Show what changed
npx @authensor/safeclaw diff --base origin/main --head HEAD

Validate the new policy
npx @authensor/safeclaw validate

Run simulation with the new policy
npx @authensor/safeclaw test --simulation

Compare policy strength before and after
echo "--- Policy strength comparison ---"
git stash
npx @authensor/safeclaw analyze > /tmp/before.txt
git stash pop
npx @authensor/safeclaw analyze > /tmp/after.txt
diff /tmp/before.txt /tmp/after.txt || true

Step 7 — Store Safety Reports

Archive the simulation report as a CI artifact. This report shows:

• Every action the agent would attempt


• The policy rule that matched each action


• Whether each action was allowed or denied


• Any actions that hit the default deny

Why This Matters

Without a pre-deploy safety gate, a developer can accidentally weaken the policy (change deny to allow), introduce conflicting rules, or deploy a syntactically invalid policy that fails to load at runtime (causing the agent to run ungated). SafeClaw's pre-deploy checks catch all of these before the code reaches production.

Related Pages

• Simulation Mode Explained
• Policy-as-Code Pattern
• Post-Deploy AI Safety Validation
• GitHub Actions Integration
• Fail-Closed Design Pattern