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Adversa AI Trusted AI Blog · May 18, 2026

OWASP ASI02: tool misuse and exploitation — the definitive security guide

guide Agent SecurityAI Red TeamingAI Engineering
Why it matters

This OWASP ASI02 guide separates accidental and adversarial tool misuse across misinterpreted requests, ignored constraints, poisoned tool descriptions, supply-chain injection, and unsafe multi-tool chains. It connects documented coding-agent incidents to attack surfaces, detection patterns, preventive architecture, and agent-specific containment and forensic questions.

My takeaway: Enforce boundaries below the prompt: use narrow single-purpose tools and typed parameters, validate resolved targets, default to dry runs, protect production with scoped identities and sandboxes, require out-of-band approval for destructive actions, retain command and tool-call logs, and test recovery from independent backups.
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More curated notes connected through Agent Security and AI Red Teaming.

OpenAI News · framework

OpenAI’s Frontier Governance Framework

OpenAI's 22-page Frontier Governance Framework maps its frontier-model processes to California's Transparency in Frontier AI Act and the EU AI Act's general-purpose AI code. It documents lifecycle risk assessment, cyber-offense and other risk tiers, mitigation and residual-risk decisions, critical-incident handling, security risk management, model reporting, external review, responsibility allocation, and change control.

OWASP GenAI Security Project · guide

OWASP Top 10 for Agentic Applications for 2026

OWASP's community guide organizes agentic-system risk into ten categories, including goal hijacking, tool misuse, identity and privilege abuse, memory poisoning, insecure inter-agent communication, cascading failures, and rogue-agent behavior. It provides a shared taxonomy and mitigation starting point rather than a certification checklist or evidence that a deployed system is secure.

OECD.AI Wonk · guide

A five-step roadmap to closing the AI evaluation gap

The roadmap addresses evaluation results that overstate real-world performance or fail to transfer across deployment contexts. Its five steps balance standardized and local tests, evaluate throughout the lifecycle, build qualified assurance and communication capacity, tailor tests to each value-chain actor and technology, and use a coordinated, trusted process for updating methods.