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Chronicles

The story behind the story

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Cloudflare tests Mythos against 50+ repositories, highlights its ability to chain bugs into a single exploit, and details a vulnerability discovery harness

Grant Bourzikas /Cloudflare:

Cloudflare Grant Bourzikas

Context & Ripple Effects

This coverage sits between Anthropic’s earlier claim that Mythos Preview could find high-severity vulnerabilities across widely used software and later reports of Palo Alto Networks and CISA applying the system to large code bases. Cloudflare adds a concrete evaluation setting: more than 50 repositories and a purpose-built discovery harness.

The important distinction is not just automated bug finding, but Cloudflare’s emphasis on chaining weaknesses into a single exploit. Related coverage also says Mythos can convert disclosed vulnerabilities into working exploits much faster, making validation and remediation workflows as consequential as detection.

First-order effects

  • Cloudflare gains a repeatable internal harness for testing Mythos across its repositories, allowing its security team to assess findings and exploit chains against its own code base.
  • The test raises the priority of triaging combinations of flaws, rather than treating each reported issue as an isolated defect.

Second-order effects

  • Application-security teams evaluating similar systems will need to compare the security value of deeper repository analysis with the compute and token budgets required; Palo Alto Networks’ reported Mythos usage indicates those costs can be material.
  • As exploit chaining becomes part of AI-assisted testing, software vendors and customers face pressure to shorten validation and patching cycles for vulnerabilities that may be low impact in isolation but dangerous in combination.

Third-order effects

  • If deployments such as Cloudflare’s, Palo Alto Networks’, and CISA’s continue, vulnerability management could shift from point-in-time scanning toward continuous, agent-assisted adversarial testing of entire code bases.
  • The same capability creates a durable dual-use challenge: systems that help defenders uncover chained flaws can also reduce the effort needed to operationalize publicly known vulnerabilities, increasing the value of controlled access and rigorous remediation processes.

The trend: Mythos is one data point in the move from AI-assisted code review toward AI systems that autonomously investigate, validate, and chain software vulnerabilities at repository scale.

Discussion

  • @dinodaizovi Dino A. Dai Zovi on x
    This, 1M% this: “The principle is to make exploitation harder for an attacker even when a bug exists, so that the gap between when a vulnerability is disclosed and when it is patched matters less. That means defenses that sit in front of the application and block the bug from
  • @kr0der Anthony Kroeger on x
    good read here by Cloudflare - they used Mythos against their own repositories to find security vulnerabilities. i read it and thought these 2 main points were interesting: 1. Mythos vs other frontier models - Frontier models could find a lot of the individual bugs, but a lot
  • @cloudflare @cloudflare on x
    Cloudflare's security team spent the last few weeks testing Anthropic's Mythos against fifty of our own repositories. What we learned about offensive AI, why faster patching is the wrong reaction, and what the architecture around vulnerabilities has to look like next.
  • @dan_jeffries1 Daniel Jeffries on x
    Finally a semi-useful read on Mythos that is free of myth and talks about what this means more practically (not this is the end of the world as we know it, but how do we deal with faster patches and attacks from AI as other models scale to chained exploits)? This is the kind of
  • @samuelcolvin Samuel Colvin on x
    Reading this, the bun rewrite to rust makes much more sense. My guess: Mythos looked at bun and had a shit fit - generated a deluge of vulnerabilities and memory bugs so vast and profound that they would be effectively impossible to fix in zig. Anthropic looked at the report
  • @zackkorman Zack Korman on x
    Cloudflare is right about this. You're not going to be able to patch fast enough, but you can build your systems so that the vast majority of vulnerabilities don't matter. If you've not done that, you're going to have a bad time. [image]
  • @rekdt @rekdt on x
    It's really funny watching companies learn things like patching at high velocity isn't a cybersecurity silver bullet The state of cybersecurity is so bad in tech today, they're recreating defense in depth from first principles
  • @dok2001 Dane Knecht on x
    Mythos and other frontier models, pointed at live code across critical Cloudflare infrastructure. An honest read on what's working and what comes next. https://blog.cloudflare.com/ ...
  • Anuk Fernando Anuk Fernando on linkedin
    AI has officially entered its “Senior Security Researcher” era.  Cloudflare's security team recently spent weeks testing Anthropic's new Mythos Preview against 50+ of their own code repositories. …
  • Grant Bourzikas Grant Bourzikas on linkedin
    Mythos is the first real step into agentic AI for security, and the direction is hard to miss. As part of Project Glasswing …