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Anthropic's Claude Mythos Preview shows why critical systems must split

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Anthropic's Claude Mythos Preview shows why critical systems must split

3 Key Points

  1. What happened

    In a contributed column, SCSK advisor Yoshihiko Murowaki cited Anthropic's April 2026 disclosure that its unreleased Claude Mythos Preview found thousands of serious OS and browser vulnerabilities and wrote attack code for many without human instruction — and said critical systems must be split into microservices.

  2. Why it matters

    If such capability reaches attackers, AI could monitor for vulnerabilities and quickly produce exploit programs, so Murowaki argues defense alone is insufficient and critical systems must be divided to minimize the impact of a breach, with data split across services so leaked names and addresses cannot be linked.

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Context & Analysis

Murowaki's column is part of a series on the structural problems in the relationship between user companies and systems integrators (SIers), which he describes as prone to a "goyocho" order-taking tendency rather than optimizing the whole IT system. The piece turns from that organizational theme to a technical one: how to design critical systems when AI makes attacks harder to stop.

The urgency comes from a sequence of reported findings. Murowaki notes that the median time from vulnerability discovery to exploitability is already well under 24 hours, and that AI is now technically capable of writing exploit programs. He references Anthropic's April 2026 statement that Claude Mythos Preview found thousands of serious vulnerabilities and generated attack code for many, which the company did not release publicly at the time for safety reasons. He also cites a July 2026 Sysdig report on an attacker called JADEPUFFER whose AI agent carried out reconnaissance, credential collection, lateral movement and extortion in sequence.

Against that backdrop, Murowaki proposes two directions: strengthen defenses through SBOM management and rapid patching, and reduce the impact of failures by splitting systems into microservices. He uses the Tokyo Stock Exchange's message exchange with securities firms to explain state transition diagrams, then argues that microservices require defining state transitions per API rather than per network connection. The column closes by linking this to a natural-ecosystem metaphor, in which independent services compete and coexist under an "invisible hand," and by arguing that data flow diagrams remain valuable for data analysis and for analyzing existing systems.

FAQ
What evidence does the column cite that AI can find and exploit vulnerabilities?
It cites Anthropic's April 2026 disclosure that Claude Mythos Preview found thousands of serious vulnerabilities in major OSes and web browsers and wrote attack code for many without human instruction. It also cites a reported case where a China-linked attacker used Anthropic's Claude Code to autonomously carry out 80–90% of attack steps.
How does splitting systems into microservices reduce damage?
If customer names and addresses are held by separate services, an attack on one service does not leak them in linked form. Splitting also limits the impact of failures and speeds recovery, Murowaki writes.
What other design methods does the column discuss?
It covers state transition diagrams for message exchanges, and says data flow diagrams (DFD) remain useful for visualizing how transaction data is transformed and for analyzing existing systems.
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