How to Set Up Alerts for Dangerous AI Agent Actions

Blocking dangerous AI agent actions is necessary but not sufficient — you also need to know when an agent attempts something dangerous so you can investigate and respond. SafeClaw by Authensor logs every policy evaluation in a hash-chained audit trail and supports webhook-based alerting, letting you send real-time notifications to Slack, PagerDuty, or any incident management system when critical deny rules fire. You learn about dangerous agent behavior within seconds, not during the next log review.

Quick Start

npx @authensor/safeclaw

Scaffolds a .safeclaw/ directory. Configure alerting as described below.

Step 1: Configure Alert Webhooks

SafeClaw can send webhook notifications when specific policy rules fire:

# .safeclaw/config.yaml
alerts:
  enabled: true
  webhooks:
    - name: slack-security
      url: "${SLACK_WEBHOOK_URL}"
      events:
        - deny
        - escalation
      filter:
        severity: [critical, high]

- name: pagerduty
      url: "${PAGERDUTY_EVENTS_URL}"
      events:
        - deny
      filter:
        severity: [critical]

Step 2: Assign Severity to Policy Rules

Tag your policy rules with severity levels so the alerting system knows what to escalate:

# .safeclaw/policies/coding-assistant.yaml
rules:
  - id: block-env-read
    action: file.read
    effect: deny
    severity: critical
    conditions:
      path:
        pattern: ".env*"
    reason: "Credential file access attempt"

- id: block-destructive-shell
    action: shell.execute
    effect: deny
    severity: critical
    conditions:
      command:
        pattern: "{rm -rf,sudo,mkfs,dd if=}"
    reason: "Destructive system command attempt"

- id: block-external-network
    action: network.request
    effect: deny
    severity: high
    conditions:
      destination:
        not_pattern: "*.internal.company.com"
    reason: "External network access attempt"

- id: block-config-writes
    action: file.write
    effect: deny
    severity: medium
    conditions:
      path:
        pattern: "{.config.,.json,.yaml,*.yml}"
    reason: "Configuration file write attempt"

Step 3: Configure Slack Alert Format

Customize the alert payload for your Slack channel:

alerts:
  webhooks:
    - name: slack-security
      url: "${SLACK_WEBHOOK_URL}"
      format:
        template: |
          {
            "blocks": [
              {
                "type": "header",
                "text": {
                  "type": "plain_text",
                  "text": "🚨 SafeClaw Alert: {{severity}} — {{action}} DENIED"
                }
              },
              {
                "type": "section",
                "fields": [
                  { "type": "mrkdwn", "text": "Agent: {{agentId}}" },
                  { "type": "mrkdwn", "text": "Rule: {{matchedRule}}" },
                  { "type": "mrkdwn", "text": "Action: {{action}}" },
                  { "type": "mrkdwn", "text": "Reason: {{reason}}" }
                ]
              },
              {
                "type": "section",
                "text": {
                  "type": "mrkdwn",
                  "text": "Details:\n

Step 4: Set Up Anomaly-Based Alerts

Beyond rule-specific alerts, detect anomalous behavior patterns:

Step 5: Create an Alert Runbook


Document how to respond to each alert type:

Step 6: Test Your Alerts


Verify alerts fire correctly using SafeClaw's simulation mode:

This triggers the policy evaluation and sends a test alert to your configured webhooks, confirming the full alert pipeline works end-to-end.

Why SafeClaw

• 446 tests ensuring alerting logic and webhook delivery are reliable
• Deny-by-default — dangerous actions are blocked AND alerted simultaneously
• Sub-millisecond evaluation — alerts fire within milliseconds of the action attempt
• Hash-chained audit trail — alert evidence is tamper-proof for incident investigation
• Works with Claude AND OpenAI — one alerting configuration covers all AI providers

Cross-References

• How to Monitor AI Agent Actions in Production
• Incident Response for AI Agents
• How to Log Every AI Agent Action for Compliance
• Fail-Closed Design Pattern