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Getting Started with AI Guardrails

Guardrails for LLMs​

Securing data in modern architectures demands real-time visibility and control. LeakSignal empowers security teams by providing live traffic analysis to observe data access, mitigate threats, and maintain regulatory compliance.

Key Features of LeakSignal​

  1. Sensitive Data Visibility

    • Achieve GenAI governance through detailed data visibility at the service level. LeakSignal detects abuse and prevents unknown data leaks.

  2. Threat Mitigation

    • Real-time data classification identifies and blocks abusive behavior based on authenticated digital identities.

  3. Incident Response and Attestation

    • Gain holistic, multi-protocol visibility into sensitive data flows with complete audit trails of accessed data.

Setting Up Guardrails for LLMs with LeakSignal​

Step 1: Configure LeakSignal to Monitor LLM Outputs

Step 2: Tune Your Deployment

  • Test your policy with live interactions to ensure accuracy.
  • Configure secondary classifiers to minimize false positives.

Step 3: Enable Real-Time Monitoring and Alerts

  • Set up LeakSignal to notify relevant teams for immediate action.

Step 4: (Optional) Implement Mitigation Actions

  • Automate responses to detected violations based on predefined policies.

Policy Configuration Overview​

LeakSignal's default LLM policy covers a wide range of patterns to ensure comprehensive protection:

Sensitive Information Patterns:

  • Phone Numbers
  • Email Addresses
  • Credit Card Numbers
  • Social Security Numbers

Offensive or Harmful Language:

  • Lists of offensive terms and slurs.

Misinformation and Fake News:

  • Keywords related to conspiracy theories and debunked claims.

Illegal Activities:

  • Terms related to hacking, drugs, fraud, and other illegal activities.

Self-Harm or Violence:

  • Terms associated with self-harm and violence.

Malicious Code or Hacking Instructions:

  • Keywords related to malware, viruses, and hacking techniques.

Explicit or Adult Content:

  • Terms related to adult content and sexual acts.

Political or Propaganda Content:

  • Keywords associated with extreme political views and propaganda.

False Accusations or Defamation:

  • Phrases indicating false accusations and defamatory language.

Financial Scams and Fraud:

  • Phrases related to scams and fraud schemes.

Additional Strategies​

Contextual Analysis

  • Use LeakSignal's NLP capabilities to understand context and reduce false positives.

Machine Learning Models

  • Leverage trained classifiers for more accurate detection of harmful content.

Blacklist and Whitelist Approaches

  • Regularly update blacklists and whitelists to refine detection.

Human Review

  • Have human moderators review flagged outputs, especially ambiguous or context-sensitive content.

By implementing these steps and strategies, organizations can set up effective guardrails for LLMs, ensuring robust data security and compliance. This guide provides a starting point, with future documentation exploring advanced classifier options and NLP techniques for enhanced data protection.