AI Security
Excessive agency in AI agents: a three-cause checklist
OWASP names three root causes of excessive agency: too much functionality, permission and autonomy. Use this checklist to review each agent you build.
Oct 18, 20263 min read
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EU AI Act Article 15: cybersecurity for AI specific attacks
Article 15 asks high-risk AI to resist data poisoning, model poisoning, adversarial examples and confidentiality attacks. What it means for security teams.
Oct 18, 20263 min read
AI Security
Does RAG or fine-tuning stop prompt injection? Myth vs fact
Myth: grounding a model with RAG or fine-tuning prevents prompt injection. Fact: OWASP says research shows neither fully mitigates it. What to do instead.
Oct 18, 20263 min read
AI Security
Does EDR see prompt injection? Myths and facts
EDR watches processes and files, so it usually cannot read a prompt or judge an agent's intent. Myths and facts about what existing tools miss in AI.
Oct 18, 20263 min read
AI Security
Why you should not trust an AI agent's report of its own actions
AI agents can misreport what they did or whether something can be undone. Reported cases and a simple way to verify agent claims independently.
Oct 18, 20264 min read
AI Security
Do AI systems and SaaS need more than the minimum SBOM elements?
CISA's 2026 page says AI systems and SaaS may need elements beyond the minimum. A separate May 2026 AI SBOM document exists. What to do in the meantime.
Oct 18, 20263 min read
AI Security
Denial of wallet: spend controls for LLM applications
Denial of wallet means attackers or bugs run up pay-per-use inference bills. The OWASP controls: limits, quotas, timeouts, alerts, graceful failure.
Oct 18, 20263 min read
AI Security
Data voids and source quality: lessons for your RAG system
Google named data voids, satire and forum posts as causes of odd AI answers. Five checks to stop a retrieval system answering when it has no good source.
Oct 18, 20263 min read
AI Security
Cross-checking perception: designing for sensor disagreement
A single sensor or model can be fooled or spoofed. How to design robots, drones and vehicles that notice disagreement between sources and fail safely.
Oct 18, 20263 min read
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