Using SafeClaw for Security Audit Workflows: Compliance-Ready Configuration

Scenario

You are on an enterprise security or compliance team. Your organization uses AI agents across multiple teams: engineering, data, operations. Regulatory requirements (SOC 2, ISO 27001, GDPR, HIPAA) mandate that you can prove what AI agents did, when they did it, and whether those actions were authorized. You need a tamper-proof record of every action, human-in-the-loop approval for sensitive operations, and exportable logs for external auditors.

SafeClaw provides all of this out of the box. Its SHA-256 hash chain audit trail is tamper-proof by design: each log entry's hash includes the previous entry's hash, so any modification to historical records breaks the chain and is immediately detectable.

Threat Model

Without auditable action-level gating, enterprise AI usage creates:

• Unaccountable activity. Auditors ask "what did the AI do with customer data?" and you have no verifiable answer.
• Undetectable policy violations. An agent accesses a restricted system, but there is no log to trigger an investigation.
• Tampered logs. Standard application logs can be edited or deleted by anyone with server access, making them inadmissible for compliance.
• Missing approval chains. Sensitive operations happen without documented human authorization, violating separation-of-duties requirements.
• Inconsistent enforcement. Different teams configure agents differently, with no central visibility into what each agent is permitted to do.
• Delayed incident response. Without real-time logging and alerting, data breaches caused by AI agents go unnoticed for days or weeks.

Recommended Policy

# Enterprise Security Audit Policy
policy:
  name: "enterprise-compliance"
  default: DENY

rules:
    # --- File Read ---
    - action: file_read
      path: "/app/data/public/**"
      decision: ALLOW

- action: file_read
      path: "/app/data/internal/**"
      decision: ALLOW

- action: file_read
      path: "/app/data/confidential/**"
      decision: REQUIRE_APPROVAL

- action: file_read
      path: "/app/data/restricted/**"
      decision: DENY

# --- File Write ---
    - action: file_write
      path: "/app/output/**"
      decision: ALLOW

- action: file_write
      path: "/app/data/**"
      decision: REQUIRE_APPROVAL

- action: file_write
      path: "/app/config/**"
      decision: DENY

- action: file_write
      path: "/app/audit/**"
      decision: DENY

# --- Shell Exec ---
    - action: shell_exec
      command: "python3 /app/scripts/approved/*"
      decision: ALLOW

- action: shell_exec
      command: "psqlSELECT"
      decision: ALLOW

- action: shell_exec
      command: "psqlINSERT"
      decision: REQUIRE_APPROVAL

- action: shell_exec
      command: "psqlUPDATE"
      decision: REQUIRE_APPROVAL

- action: shell_exec
      command: "psqlDELETE"
      decision: DENY

- action: shell_exec
      command: "psqlDROP"
      decision: DENY

- action: shell_exec
      command: "sudo*"
      decision: DENY

- action: shell_exec
      command: "ssh*"
      decision: DENY

# --- Network ---
    - action: network
      domain: "internal-api.company.com"
      decision: ALLOW

- action: network
      domain: "api.openai.com"
      decision: ALLOW

- action: network
      domain: "safeclaw.onrender.com"
      decision: ALLOW

- action: network
      domain: "*.company.com"
      decision: REQUIRE_APPROVAL

- action: network
      domain: "*"
      decision: DENY

Example Action Requests

1. Agent reads public data (ALLOW, logged)

{
  "action": "file_read",
  "path": "/app/data/public/product-catalog.json",
  "agent": "ops-agent-01",
  "timestamp": "2026-02-13T10:00:00Z"
}
// Decision: ALLOW
// Audit entry: hash=sha256(prev_hash + action + decision + timestamp)

2. Agent reads confidential data (REQUIRE_APPROVAL, logged)

{
  "action": "file_read",
  "path": "/app/data/confidential/customer-contracts.pdf",
  "agent": "ops-agent-01",
  "timestamp": "2026-02-13T10:01:00Z"
}
// Decision: REQUIRE_APPROVAL
// Audit entry logged. Notification sent to approver.
// Approver reviews in dashboard, clicks Approve or Deny.
// Approval decision logged with approver identity and timestamp.

3. Agent reads restricted data (DENY, logged)

{
  "action": "file_read",
  "path": "/app/data/restricted/encryption-keys.pem",
  "agent": "ops-agent-01",
  "timestamp": "2026-02-13T10:02:00Z"
}
// Decision: DENY
// Audit entry logged. Security alert triggered.

4. Agent runs an approved script (ALLOW, logged)

{
  "action": "shell_exec",
  "command": "python3 /app/scripts/approved/generate_report.py --date 2026-02-13",
  "agent": "data-agent-02",
  "timestamp": "2026-02-13T10:10:00Z"
}
// Decision: ALLOW
// Audit entry: includes full command, agent identity, and hash chain link

5. Agent attempts a database DELETE (DENY, logged)

{
  "action": "shell_exec",
  "command": "psql -c \"DELETE FROM customers WHERE region = 'EU'\"",
  "agent": "data-agent-02",
  "timestamp": "2026-02-13T10:15:00Z"
}
// Decision: DENY
// Audit entry logged. This entry alone could satisfy a GDPR audit query:
// "Was any EU customer data deleted by an AI agent?" Answer: No, attempt was blocked.

6. Agent attempts to reach an external domain (DENY, logged)

{
  "action": "network",
  "domain": "external-analytics.example.com",
  "method": "POST",
  "agent": "ops-agent-01",
  "timestamp": "2026-02-13T10:20:00Z"
}
// Decision: DENY
// Audit entry logged with full request metadata.

Setup Steps

1. Install SafeClaw on your enterprise infrastructure:

   npx @authensor/safeclaw

1. Create a compliance-grade policy. Use the "Enterprise Compliance" template from the wizard. Classify your data directories into tiers: public (ALLOW), internal (ALLOW), confidential (REQUIRE_APPROVAL), restricted (DENY).

1. Configure REQUIRE_APPROVAL for sensitive operations. Set approvers by email address or team role. When an agent triggers a REQUIRE_APPROVAL action, the designated approver receives a notification in the dashboard with full context.

1. Enable the SHA-256 hash chain audit trail. This is enabled by default. Each log entry contains:

1. Verify hash chain integrity. Use the dashboard's "Verify Integrity" button or the CLI:

   npx @authensor/safeclaw audit verify --from 2026-01-01 --to 2026-02-13

1. Export logs for auditors. The dashboard provides JSON and CSV export. Filter by date range, agent, action type, or decision:

   npx @authensor/safeclaw audit export --format csv --from 2026-01-01 --to 2026-02-13 --output audit-q1-2026.csv

1. Set up alerts. Configure the dashboard to send notifications when specific patterns occur: repeated denials from the same agent, attempts to access restricted data, or hash chain integrity failures.

1. Document your SafeClaw configuration as part of your compliance evidence package. The policy definition, audit export, and hash chain verification output together satisfy auditor requirements for AI agent governance.

Cross-References

• SafeClaw Quickstart Guide — Full installation and first-run walkthrough
• Audit Trail and Hash Chain — Technical details on SHA-256 hash chain implementation
• REQUIRE_APPROVAL Workflow — How human-in-the-loop approval works and how approvals are logged
• Deny-by-Default Architecture — Why SafeClaw blocks everything unless explicitly allowed
• Compliance Export Formats — JSON and CSV schema documentation for audit exports