Updated the testing methodology for training data exposure vulnerabilities in AI systems, detailing the setup and execution of tests for direct storage access and inference-based data extraction.
Updated the document to improve structure and clarity, including sections on testing methodology, expected outputs, remediation strategies, and suggested tools.
Updated the document to enhance clarity and detail in the explanation of testing for explainability and interpretability in AI systems. Added specific objectives, expected outputs, remediation strategies, and suggested tools.
Updated the structure and content of the testing document to improve clarity and organization, including renaming sections and enhancing remediation strategies.
Expanded testing documentation for model extraction attacks, including detailed payloads, prerequisites, and step-by-step instructions for data acquisition, surrogate model training, and evaluation.
Expanded the section on embedding manipulation to include detailed explanations of vulnerabilities, attack vectors, and testing objectives. Updated suggested tools for testing embedding robustness.
This guide aims to provide a structured framework for assessing AI systems' security, targeting various roles involved in AI security and compliance. It outlines a methodology for threat modeling, mapping, and testing specific to AI applications.
This document outlines the principles of OWASP AI Testing, detailing four macro domains: Security, Privacy, Responsible AI, and Trustworthy AI Systems. It also describes the phases of the AI system lifecycle and the importance of integrating testing throughout.
aggiunta maggiore chiarezza su come la mappatura dalla minaccia al componente SAIF, al test e alle vulnerabilità (CVEs e CWEs) di quel componente renda il report di penetration testing più concreto e orientato all’azione, facilitando la formulazione di raccomandazioni di correzione efficaci.
This document serves as the preface and contributor acknowledgment for the OWASP AI Testing Guide, outlining the purpose, methodology, and contributors involved in the project.
Matteo Meucci