Artificial Intelligence (AI) has become the definitive frontier of digital defense, acting as both a sophisticated shield for defenders and a high-speed engine for adversaries. In a landscape where the volume of data exceeds human processing capacity, AI is essential for cybersecurity because it enables real-time anomaly detection, predictive threat intelligence, and autonomous incident response at machine scale. However, this same technology introduces unique vulnerabilities—such as prompt injection, data poisoning, and the rise of hyper-realistic deepfakes—that require fundamentally new security architectures. By integrating AI-driven defenses while maintaining rigorous governance over the models themselves, organizations can transform their security posture from reactive firefighting to a proactive, resilient strategy that evolves as quickly as the threats it faces.
The ANSSI document “Building Trust in AI Through a Cyber Risk-Based Approach” provides a comprehensive analysis of the cybersecurity risks associated with AI systems and advocates for a risk-based strategy… Read More »ANSSI Building Trust in AI Through a Cyber Risk-Based Approach
The OWASP Top 10 for Large Language Model (LLM) Applications is a community-driven list identifying the most critical security risks specific to LLMs and generative AI systems. It highlights vulnerabilities… Read More »OWASP Top 10 for Large Language Model Applications
ANSSI recommends isolating each phase of the generative AI system lifecycle (training, deployment, production) using network segmentation, dedicated hardware, and strict access controls to prevent data leakage and unauthorized access. Secure… Read More »ANSSI Security Recommendations for a Generative AI System
The EU AI Act is the first comprehensive legal framework regulating artificial intelligence in Europe, designed to foster trustworthy AI while protecting fundamental rights, safety, and ethical principles. It classifies… Read More »EU Regulation 2024/1689 Artificial Intelligence Act (AI Act)
The OWASP LLM AI Cybersecurity & Governance Checklist provides organizations with a structured framework to manage the risks and responsibilities associated with deploying Large Language Models (LLMs). It covers 13… Read More »OWASP LLM Applications Cybersecurity and Governance Checklist v1.1
The NCSC Guidelines for Secure AI System Development provide comprehensive recommendations to ensure that AI systems are designed, developed, deployed, and operated securely throughout their entire lifecycle. The guidelines are… Read More »NCSC Guidelines for Secure AI System Development
The Secure AI Framework (SAIF), developed by Google, is a comprehensive set of guidelines and best practices aimed at ensuring the security, privacy, and integrity of artificial intelligence (AI) systems… Read More »Google Secure AI Framework (SAIF) ★★★★★