🔥 Adversarial Testing

ai+me's adversarial testing simulates real-world attacks against your AI systems to identify vulnerabilities before attackers can exploit them. Unlike generic security testing, our approach generates contextual attacks tailored to your AI's specific business scope and use cases.

🎯 What is Adversarial Testing?

Adversarial testing is a systematic approach to identifying vulnerabilities in AI systems by simulating malicious attacks. Think of it as penetration testing for AI—we systematically test your AI's boundaries and identify potential weaknesses that could be exploited by attackers.

🔍 Key Concepts

Contextual Attacks

  • Purpose: Generate attacks relevant to your AI's business context
  • Method: Create prompts based on your specific use cases and scope
  • Goal: Identify vulnerabilities that matter for your application

Systematic Testing

  • Purpose: Comprehensive coverage of potential attack vectors
  • Method: Structured testing against known vulnerability categories
  • Goal: Ensure no attack vectors are overlooked

Automated Evaluation

  • Purpose: Consistent and scalable vulnerability assessment
  • Method: Use LLM-as-a-Judge to evaluate AI responses
  • Goal: Provide objective, repeatable results

🏗️ How Adversarial Testing Works

🔄 Testing Process

Step 1: Context Analysis

  1. Business Scope Review: Analyze your AI's intended use cases
  2. Policy Extraction: Identify security policies and constraints
  3. Risk Assessment: Determine potential attack vectors
  4. Scope Definition: Define testing boundaries and objectives

Step 2: Attack Generation

  1. Pattern Creation: Generate attack patterns based on context
  2. Prompt Engineering: Create adversarial prompts
  3. Edge Case Identification: Identify boundary conditions
  4. Attack Variation: Create multiple attack variations

Step 3: Test Execution

  1. Automated Testing: Run attacks against your AI system
  2. Response Collection: Capture AI responses to attacks
  3. Performance Monitoring: Track system performance during testing
  4. Error Handling: Manage test failures and timeouts

Step 4: Response Evaluation

  1. Safety Assessment: Evaluate responses for safety violations
  2. Policy Compliance: Check adherence to business policies
  3. Vulnerability Detection: Identify specific vulnerabilities
  4. Risk Scoring: Assign risk scores to identified issues

Step 5: Reporting and Analysis

  1. Vulnerability Reports: Generate detailed vulnerability reports
  2. Risk Assessment: Provide comprehensive risk analysis
  3. Remediation Guidance: Suggest specific fixes and improvements
  4. Trend Analysis: Track vulnerabilities over time
🛡️ AI Assurance🧪 Behavioural Testing