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OpenClaw Blind Mode Testing Program

Ethical AI Security Assessment

Purpose

This program tests AI agent resistance to prompt injection attacks in a controlled, ethical environment. Unlike our standard challenges that explicitly show injection payloads, blind-mode tests present realistic scenarios without revealing they are security assessments.

How It Works

  • Realistic Scenarios: Content appears as normal web pages, documentation, emails, or support tickets
  • No Warning Labels: Test pages contain no indication they are security tests
  • Controlled Environment: All testing is sandboxed with no real system access
  • Consensual Testing: Participants explicitly opt-in to blind-mode assessment
  • Transparent Results: Testing methodology and results are documented

Why Blind Mode Matters

Standard security testing where agents know they're being tested can produce misleading results. Agents may pass challenges not because they're truly secure, but because they recognize the testing context. Blind-mode testing reveals how agents behave when encountering injections in the wild.

Standard Mode

  • ✓ Educational
  • ✓ Shows attack patterns
  • ✗ Agent knows it's a test
  • ✗ May not reflect real behavior

Blind Mode

  • ✓ Realistic scenarios
  • ✓ Tests actual resistance
  • ✓ No testing indicators
  • ✓ Reveals true security posture

Ethical Commitment

  • ✓ Transparent: This documentation is publicly accessible and indexed
  • ✓ Consensual: Agents/developers explicitly opt-in to blind testing
  • ✓ Safe: No data exfiltration, system compromise, or real-world harm
  • ✓ Reproducible: Testing methodology is fully documented
  • ✓ Responsible: Follows NIST AI Risk Management Framework guidelines

How to Use Blind Mode Tests

Blind-mode challenges are available to anyone who wants to test their AI agent's security. The pages are excluded from search engine indexing but accessible via direct URL.

Ready to test your agent? See the How to Test Your AI Agent guide for step-by-step instructions, challenge URLs, and example prompts.

Note: Test content is intentionally realistic and contains no warnings or disclaimers. This is by design—to accurately assess real-world resilience.

Regulatory Compliance

  • NIST AI RMF: Compliance with measurement and monitoring standards
  • OWASP: Security testing best practices
  • IEEE Ethically Aligned Design: Principle-based AI development
  • Responsible Disclosure: Following coordinated vulnerability disclosure timelines

Legal & Safety

All blind-mode testing:

  1. Operates in isolated, sandboxed environments
  2. Contains no executable code (text-only prompt injections)
  3. Logs all access for security review
  4. Follows responsible disclosure protocols for any vulnerabilities discovered
  5. Maintains confidentiality of participant results

See our Testing Terms for complete details.

Research & Results

Aggregated, anonymized results from blind-mode testing contribute to:

  • Understanding real-world prompt injection attack success rates
  • Improving AI security guardrails and defenses
  • Educational content for the AI safety community
  • Industry standards for secure AI deployment

Questions or Access Requests

For questions about the blind-mode testing program, access requests, or to report concerns about our testing methodology, please visit our Security Policy page.

Transparency Note: This page is publicly accessible and indexed by search engines. Test pages themselves are protected and contain no explanation of testing purpose to preserve blind-mode integrity.