Automated AI Security Testing
Comprehensive automated testing suite for AI systems. Detect vulnerabilities, test defenses, and ensure robust security.
Test Categories
Automated testing for prompt injection vulnerabilities with 500+ attack patterns and bypass techniques.
Test model resilience against training data poisoning and backdoor attacks with automated validation.
Evaluate protection against model extraction attacks and intellectual property theft attempts.
Test model resilience against adversarial examples and evasion attacks across multiple domains.
Automated detection of training data leakage, PII exposure, and membership inference vulnerabilities.
Comprehensive testing for autonomous agent security including tool misuse and policy violations.
Key Features
Integrate with CI/CD pipelines for automated security testing
Schedule regular security scans and vulnerability assessments
Automated regression testing for security fixes
Detailed vulnerability reports with severity ratings
Remediation recommendations and code examples
Export reports in multiple formats (PDF, JSON, HTML)
Create custom test cases for your specific use cases
Configure test parameters and thresholds
Extend with custom plugins and test modules
Quick Start Guide
1. Install the Testing Suite
pip install ai-security-testing2. Initialize Configuration
ai-security-test init --config my-config.yaml3. Run Your First Test
ai-security-test run --suite prompt-injection --target https://api.example.comfrom ai_security_testing import SecurityTester
# Initialize tester
tester = SecurityTester(
target_model="gpt-4",
api_endpoint="https://api.openai.com/v1/chat/completions"
)
# Run comprehensive test suite
results = tester.run_all_tests(
test_suites=[
"prompt_injection",
"data_leakage",
"adversarial_robustness"
],
severity_threshold="medium"
)
# Generate report
tester.generate_report(
results=results,
output_format="html",
output_path="security_report.html"
)Example GitHub Actions workflow for automated security testing:
name: AI Security Tests
on: [push, pull_request]
jobs:
security-test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Run AI Security Tests
run: |
pip install ai-security-testing
ai-security-test run --all --fail-on-highDownload Testing Suite
Start automated security testing for your AI systems today.
Related Resources
Frequently Asked Questions
Automated AI Security Testing is a comprehensive testing suite that automatically detects vulnerabilities, tests defenses, and ensures robust security in AI systems. It includes automated scanning, penetration testing, and security validation for AI applications.
The suite includes prompt injection testing, model inversion detection, adversarial example generation, data poisoning tests, output validation, access control verification, and compliance checking for AI systems.
Automated testing provides continuous, scalable security validation that can run in CI/CD pipelines, detect known vulnerabilities quickly, and perform repetitive tests efficiently. Manual testing offers deeper analysis and creative attack scenarios that complement automated testing.
Yes, the automated testing suite is designed for CI/CD integration, allowing you to run security tests automatically on code commits, pull requests, and deployments to catch vulnerabilities early in the development lifecycle.
The suite supports testing for major AI frameworks including OpenAI, Anthropic, Google AI, Azure OpenAI, AWS Bedrock, and custom LLM deployments across various platforms and cloud providers.
The suite uses advanced detection algorithms with high accuracy rates, but results should be reviewed by security professionals. False positives are minimized through machine learning-based pattern recognition and continuous algorithm improvements.