stress-tests AI systems to understand the full extent of their current capabilities and anticipate what comes next. We provide evidence-based analysis about AI’s implications for cybersecurity, national security, and autonomous systems.CVD dashboardVisitOSS ScannerVisit

Our mission

We aim to accelerate coordination around AI safety by producing evidence of emerging risks and prototyping defenses against them.

Bridging research and policy

Our researchers work to translate technical findings into useful evidence for decision-makers in national security, policy, and industry.

  • Launching an opt-in vulnerability-finding service for open-source software
  • GLM-5.3 and the spread of advanced cyber capabilities
  • Patterns and problems in emerging multiagent systems

Launching an opt-in vulnerability-finding service for open-source software

We’re making available OSS Scanner, an opt-in vulnerability scanner for the open-source ecosystem that’s informed by our experience using Claude to find vulnerabilities during Project Glasswing.

Read more

GLM-5.3 and the spread of advanced cyber capabilities

Like Claude Mythos Preview, GLM-5.3 has strong capabilities for autonomously building end-to-end cyber exploits. But GLM-5.3 is unlike other frontier models in that it has been released without meaningful safeguards to limit misuse.

Read more

Patterns and problems in emerging multiagent systems

Here, we identify a few examples of behavioral tendencies in current frontier models and show how they can produce unexpected systemic failures, in hopes of starting a conversation about mitigating these risks.

Read more01/03

33

ARTICLES

    Using Claude to reduce the attack surface of code

    Claude reveals ECDSA curve origins

    AI models may be capable of self-replicating without access to a datacenter

    Launching an opt-in vulnerability-finding service for open-source software

    GLM-5.3 and the spread of advanced cyber capabilities

    Measuring tactical intelligence targeting and conventional weapons capabilities of AI models

    Patterns and problems in emerging multiagent systems

    Discovering cryptographic weaknesses with Claude

    Project Pilot: Can AI control a drone?

    Claude plays robotics

    Project Fetch: Phase two

    Measuring LLMs’ impact on N-day exploits

    Mapping AI-enabled cyber threats: Insights from the LLM ATT&CK Navigator

    Measuring LLMs’ ability to develop exploits

    Trustworthy agents in practice

    Assessing Claude Mythos Preview’s cybersecurity capabilities

    Reverse engineering Claude's CVE-2026-2796 exploit

    Evaluating and mitigating the growing risk of LLM-discovered 0-days

    AI models are showing a greater ability to find and exploit vulnerabilities on realistic cyber ranges

    Finding bugs across the Python ecosystem with Claude and property-based testing

    Experimenting with AI to defend critical infrastructure

    Project Vend: Phase two

    AI agents find $4.6M in blockchain smart contract exploits

    Project Fetch: Can Claude train a robot dog?

    Explore work from other teams

    Alignment

    47 posts

    Works to understand the risks of AI models and develop ways to ensure future ones remain helpful, honest, and harmless.

    Economics

    25 posts

    Studies and monitors the impact of AI systems on individuals, firms, and economies.

    Engineering

    27 posts

    Builds the infrastructure and systems that make Claude reliable and trustworthy.

    Interpretability

    35 posts

    Studies how large language models work internally as a foundation for AI safety.

    Societal Impacts

    24 posts

    Studies how AI affects people, both individually and collectively.

    Science

    18 posts

    Explores how AI can increase the pace of scientific progress through both research and collaborations.

    Frontier Red Team

    33 posts

    Stress-tests AI systems to understand the full extent of their current capabilities and anticipate what comes next.

    Alignment

    47 posts

    Works to understand the risks of AI models and develop ways to ensure future ones remain helpful, honest, and harmless.

    Economics

    25 posts

    Studies and monitors the impact of AI systems on individuals, firms, and economies.

    Engineering

    27 posts

    Builds the infrastructure and systems that make Claude reliable and trustworthy.

    Interpretability

    35 posts

    Studies how large language models work internally as a foundation for AI safety.

    Societal Impacts

    24 posts

    Studies how AI affects people, both individually and collectively.

    Science

    18 posts

    Explores how AI can increase the pace of scientific progress through both research and collaborations.

    Frontier Red Team

    33 posts

    Stress-tests AI systems to understand the full extent of their current capabilities and anticipate what comes next.