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OpenAI News · April 30, 2026

Introducing Advanced Account Security

news Agent SecurityAI EngineeringAI Compliance
Why it matters

OpenAI's opt-in Advanced Account Security applies to ChatGPT and Codex. It replaces password login with passkeys or FIDO security keys, disables email and SMS recovery, shortens sessions, adds login alerts and session management, and automatically excludes conversations from model training. The stronger recovery model also means support cannot restore access for an enrolled user.

My takeaway: Use phishing-resistant authentication for accounts that can reach sensitive conversations, code, tools, or trusted cyber capability, but prepare recovery before enabling it. Register independent backup authenticators, store recovery keys offline, inventory active sessions, and document offboarding so stronger login controls do not create an unrecoverable operational dependency.
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More curated notes connected through Agent Security and AI Engineering.

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.