Deep dives into LLM vulnerabilities, adversarial ML, OWASP Top 10 for AI, and the evolving threat landscape targeting intelligent systems.
A deep dive into all 10 risks in the 2025 OWASP LLM framework — from Prompt Injection to Unbounded Consumption — with real-world attack scenarios, vulnerable code patterns, and mitigation strategies for each.
How attackers hijack LLM behavior through direct and indirect prompt injection — jailbreaks (DAN, roleplay, base64 encoding), RAG poisoning, and malicious documents that take over autonomous agents.
From the classic panda-gibbon FGSM attack to physical adversarial patches that fool self-driving cars: a technical breakdown of evasion attacks, the mathematics behind them, and practical defenses.
Backdoor trojans, clean-label attacks, federated learning exploits, and gradient inversion — how attackers compromise AI models at the training stage and steal private data from deployed models.
SecureAI is a research blog dedicated to understanding, documenting, and defending against security vulnerabilities in artificial intelligence and machine learning systems. As AI becomes embedded in critical infrastructure, autonomous agents, and decision-making pipelines, the attack surface grows dramatically. This blog covers the technical depth of these threats — from OWASP LLM risks and prompt injection to adversarial examples and training-time attacks — so builders and defenders can stay ahead.