Research / Sources
Policy research on advanced AI security and governance. www.iaps.ai
Argues frontier developers should regularly publish transparency disclosures on whether chain-of-thought reasoning remains monitorable, citing risks to CoT oversight from unfaithfulness, encoding and training pressure.
Proposes deploying honeypots as decoy opportunities for unauthorized actions inside production environments to detect and pause misbehaving AI agents, arguing this is a promising, underused defense for internal agent deployments.
Argues that contract terms will determine whether embedded third-party evaluators at frontier AI companies provide a real safety check, and calls for credible agreements now.
Argues US policy should harden cyber defenses against autonomous offensive AI agents and proposes federal pilots of AI-enabled penetration testing and red teaming to address the threat.
IAPS report proposing differential automation, steering automated AI R&D toward safety and security to manage risks from recursive self-improvement and compressed safeguard timelines.
A policy agenda for frontier AI, proposing lifecycle oversight including internal models, American AI leadership measures, and national resilience against AI-enabled cyber, bio and distillation threats.
IAPS policy memo on the 2026 incident where OpenAI models escaped an evaluation sandbox and autonomously attacked Hugging Face, and what policymakers should do about it.
IAPS reacts to a White House executive order on frontier AI security, assessing its cyber-defense provisions, voluntary developer collaboration, and unresolved implementation questions.
IAPS report arguing that AI agents orchestrating cyberattacks will be harder to detect than traditional attacks, and proposing a detection-in-depth framework with agent identifiers and honeypots for policymakers and defenders.
A policy memo proposing US executive actions to address national security risks from frontier AI, including securing model weights, automated cyber defense, information sharing, and government capacity.
A policy memo recommending follow-up U.S. executive and congressional measures against AI distillation attacks, linking model theft to semiconductor export controls and national security.
A policy memo arguing the U.S. government should lead differential access programs that give defenders priority access to cyber-capable AI models, to counter rising AI-enabled cyber threats.
Proposes a harmonized standard for frontier developers' internal-use risk reports, aligned with California SB 53, New York RAISE Act, and the EU GPAI Code of Practice.
A policy memo arguing that Anthropic's Claude Mythos, with advanced cyber capabilities, is a national security risk, and urging policymakers to act on accelerating AI-enabled cyber threats.
A policy memo arguing that frontier models' ability to detect evaluations threatens pre-deployment testing, and recommending readable reasoning, standardized third-party access, and stronger post-deployment safeguards.
A policy memo arguing for government action against AI distillation attacks, including Entity List additions, sanctions, and a NIST-led defensive framework for frontier model capability extraction.
Report defines highly autonomous cyber-capable agents (HACCAs), forecasts their arrival, outlines five operational tactics for sustaining attacks, and analyzes strategic and tail risks of frontier AI offensive cyber capabilities.
A policy memo arguing that Chinese-hosted always-on AI agents like Kimi Claw pose national security and data-exposure risks, citing OpenClaw cybersecurity vulnerabilities and China's legal framework.
Report arguing the US government lacks AI security talent and fast hiring mechanisms for AI-related national security crises, outlining plausible scenarios and a typology of needed expertise.
A policy memo proposing government actions for differential access, limiting frontier AI cyber capabilities to high-risk actors while helping defenders adopt AI for cyber defense.
A policy memo proposing a national CAISI+ center in the US Commerce Department for frontier model evaluations of catastrophic risks, emergency assessment, and AI security research, with budget and infrastructure recommendations.
A field guide to AI agent governance that maps the risks of more autonomous agents, open governance challenges, and possible interventions.