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Adversa AI Trusted AI Blog · August 25, 2026

OWASP Agentic Skills Top 10 explained: the ten agent skill risks, and which to fix first

guide Agent SecurityPrompt InjectionAI Red Teaming
Why it matters

Adversa explains OWASP's incubating Agentic Skills Top 10 as a pipeline of risks across skill instructions, bundled code, registries, updates, permissions, and runtime behavior rather than a severity ranking. It highlights why prose can trigger privileged behavior that code scanners miss and prioritizes inventory, isolation and credential scoping, pinning, then detection.

My takeaway: Inventory every installed skill and its provenance, read the complete instructions and references, inspect bundled and opaque files, pin reviewed versions, and run each skill with only the identity, tools, filesystem, and network access it needs. Combine artifact scanning with runtime traces because malicious intent can live entirely in natural-language instructions.
Keep exploring

More curated notes connected through Agent Security and Prompt Injection.

OpenAI News · framework

Pacing model development in an era of cyber-critical capabilities

OpenAI says preliminary evidence that Astra may meet its Critical cybersecurity threshold led it to pause frontier reinforcement-learning work for two weeks and keep its largest planned run on hold. New safeguards include stronger workload and network isolation, continuous boundary testing, token-level monitoring that escalates suspicious tool activity, and broader alignment checks for deception, reward hacking, and unauthorized access.

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.

OpenAI News · framework

A blueprint for democratic governance of frontier AI

OpenAI proposes a three-part U.S. frontier-AI governance model: harmonize emerging state safety laws into a federal baseline, strengthen CAISI as an evaluation and standards institution, and coordinate a broader resilience program. Proposed controls include severe-risk evaluations, transparency reports, independent audits, safety-incident reporting, model-weight security, whistleblower protection, and periodic technical assessments.