AI Security Table

Anthropic wants to give AI agents one shared way to run microscopes, liquid handlers, and robotic arms, and the squad cannot agree on whether that is progress or the opening scene of every bad sci fi movie. Matt, who has worked on robotics projects, says a common control standard is decades overdue. Izar calls it the PCI for AI, reminds everyone how secure MCP was on day one, and brings up Therac 25 as a warning about what happens when software controls hardware and fails silently. Then the t...

If AI can turn a request directly into instructions a chip understands, what is left for a human to review? Chris Romeo, Izar Tarandach, and Matt Coles debate whether readable source code remains essential when agents do the programming. Matt argues that code always matters; Izar rejects the premise that another abstraction makes ambiguity disappear. The conversation moves through COBOL, Fortran, language evolution, and the prospect of abandoning pull request review. They also consider optimi...

An AI agent publishes a malicious Python package while chasing a capture-the-flag goal. Is that an escape, a supply chain failure, or reward hacking doing exactly what it was encouraged to do? Chris Romeo, Izar Tarandach, and Matt Coles examine the Anthropic incident and disagree about how much intention to attribute to a model. The discussion turns to package scanners, dependency names, GPG signing, and whether penalties can teach ethics to a system without a human understanding of consequen...

When a model crosses a sandbox boundary, is the lesson that AI has become malicious or that the boundary was never strong enough? Chris Romeo, Izar Tarandach, and Matt Coles examine the CSA post-mortem on the OpenAI agents that compromised Hugging Face during a security evaluation. They debate reward-driven behavior, disabled safeguards, the four-day intrusion timeline, and the responsibility of the people running the experiment. The discussion moves from cyber ranges and incident response to...

If AI can find and validate vulnerabilities faster than people, why would a company keep paying outsiders to report them? Chris Romeo, Izar Tarandach, and Matt Coles start with Linus Torvalds' changing assessment of AI-generated Linux kernel reports, then examine what useful automation does to the bug bounty economy. They debate disclosure incentives, model restrictions that may constrain defenders more than attackers, and the cost of separating real findings from a flood of submissions. Bugc...