OWASP has released a comprehensive AI Security Guide spanning over 300 pages of practical guidance for protecting AI and data-centric systems. The resource consolidates security best practices, threat models, and implementation guidance accumulated from the global security community working to secure AI deployments across industries.

The guide addresses the complete AI system lifecycle from data collection and model training through deployment and ongoing operations. Each phase receives detailed threat analysis identifying specific attack vectors and vulnerabilities, followed by actionable mitigation strategies that organizations can implement regardless of their AI maturity level.

Key sections cover data security for training pipelines, model integrity protection, inference security, and operational monitoring requirements. The guide provides specific implementation guidance for common AI frameworks and platforms, translating abstract security principles into concrete configuration recommendations and code patterns.

The resource addresses both traditional machine learning systems and the emerging category of large language models and AI agents. Dedicated chapters examine prompt injection, data poisoning, model extraction, and other AI-specific attack categories with detailed detection and prevention strategies. Real-world case studies illustrate how organizations have successfully implemented recommended controls.

OWASP emphasizes that the guide represents community knowledge contributed by security practitioners, AI researchers, and enterprise architects. The document undergoes continuous updates as the threat landscape evolves and new vulnerabilities are discovered. Organizations are encouraged to contribute their experiences and proposed additions through the OWASP AI project collaboration channels.