AI Red Team Engineering notes, research references, and field notes on AI systems, responsible AI, governance, and compliance.
Global search

Search AI Red Team

Search across the complete knowledge base.

Enter at least two characters to begin.
↑↓ select Enter open Browse the full research archive
Cleafy · September 28, 2026

RATHat: model-assisted targeting and UI recovery rely on an existing Android foothold

news Agent SecurityAI Red Teaming
Why it matters

Cleafy’s analysis distinguishes two AI uses in RATHat: the operator panel estimates victim value from stolen SMS messages, while device-side Gemini calls help locate controls when fixed UI automation fails. The malware first requires an Accessibility grant and a successful wireless-debugging pairing path; an operator can then deploy a separate shell-level service. That service can survive app removal until reboot. The analyzed samples do not show an LLM performing fraudulent transfers, and some native capture tools fail on Android 14 and later.

My takeaway: Investigate unexpected Accessibility grants, wireless debugging, shell-user processes and reverse tunnels together. App removal alone may leave the separate service active. Preserve device evidence, contain affected sessions and accounts, and distinguish observed UI assistance from claims of autonomous payment fraud.
Keep exploring

More curated notes connected through Agent Security and AI Red Teaming.

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.

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.

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.