CAI: Framework for AI security and pentesting
LLM-powered Python framework for automated penetration testing workflows.
Learn more about CAI
CAI is a framework designed to apply AI and large language models to cybersecurity operations and penetration testing workflows. The framework provides integration with multiple AI models and security tools, implemented as a Python package available through pip. It supports deployment across Linux, macOS, Windows, and Android environments. Common applications include automated security testing, vulnerability assessment, and AI-assisted penetration testing scenarios.
Multi-Model AI Integration
Supports 300+ language models from different providers with unified API access. Switch between models for specific security tasks without vendor lock-in or code changes.
Cross-Platform Deployment
Runs on Linux, macOS, Windows, and Android from a single Python package. Deploy identical security workflows across desktop and mobile environments without platform-specific code.
Research-Backed Framework
Open-source implementation with peer-reviewed arXiv publications documenting security approaches. Transparent methodology allows engineers to audit and understand the framework's security considerations.
from cai import CAI
# Initialize CAI with default model
cai = CAI()
# Ask security-related question
response = cai.query("Explain SQL injection vulnerabilities")
print(response)See how people are using CAI
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