AMLUCS is a two-day, not-for-profit practitioner conference in London dedicated to applied AI and machine learning in cybersecurity. Its twin-track scope includes AI-system threats and mitigations, offensive and defensive AI, multi-agent design, governance and standards, and a preceding production AI red-team training course.
AMLUCS 2026
Related research
More curated notes connected through AI Red Teaming and Adversarial ML.
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’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.
Cybersecurity in the Intelligence Age
OpenAI proposes a five-pillar strategy for AI-enabled cyber defense: tiered access for trusted defenders, faster government-industry coordination, stronger protection of frontier models and infrastructure, risk-scaled deployment monitoring, and broader defensive support for individuals and small organizations.