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Claude Mythos Preview: AI hacks networks in tests

Claude Mythos Preview model from Anthropic showed outstanding results in cyberattack tests, successfully executing complex scenarios. The analysis highlights risks for business and the need to strengthen protection. Future tests will take into account real conditions.

AI Breakthrough: Claude autonomously attacks corporate networks
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Claude Mythos Preview Shows Breakthrough in Autonomous Cyberattacks

Claude Mythos Preview by Anthropic has successfully passed advanced security tests, executing multi-stage cyberattack simulations without human intervention. This marks a significant leap in AI capabilities for identifying vulnerabilities and exploiting network weaknesses.

Progress in Security Testing

The AI Security Institute evaluated Claude Mythos Preview in controlled cyberattack simulations. The model outperformed earlier versions in Capture the Flag challenges—competitions focused on uncovering system vulnerabilities. At high difficulty levels, it achieved a 73% success rate.

In "The Last Ones" simulation—a 32-step scenario mimicking corporate network infiltration—the AI fully completed the mission in 30% of attempts. On average, it reached step 22, significantly surpassing competing models. A human expert would typically need around 20 hours to complete a similar operation.

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Despite failing a test involving industrial systems—where the model stalled at the IT phase—these results highlight growing AI autonomy in offensive cybersecurity tasks.

Success Factors and Limitations

Tests were conducted in isolated environments without active defense mechanisms, intrusion detection, or penalties for suspicious behavior. This differs from real-world networks, where protective systems respond dynamically to threats.

The performance gains stem from rapid model evolution: within two years, AI has progressed from simple tasks to complex, multi-step attack chains. Improvements in sequence processing and data analysis now allow the model to autonomously plan and execute attacks.

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Key advantages over previous versions:

  • Autonomous vulnerability discovery
  • Multi-step execution without prompts
  • High success rate in advanced scenarios

Implications for Cybersecurity

Such AI capabilities increase risks for poorly defended networks. Organizations now face the threat of automated attacks, where adversaries use AI for reconnaissance and exploitation. Foundational security hygiene—software updates, access control, and log monitoring—has become more critical than ever.

Demand is rising for AI-powered defenses: models capable of analyzing traffic in real time, predicting threats, and automating responses. However, ethical concerns remain unresolved. Anthropic developers emphasize the need for strict safeguards to prevent misuse.

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Broader context: the global cybersecurity market exceeds $200 billion annually, with AI-driven solutions accounting for 10–15%. Claude’s progress intensifies competition, driving investment into adaptive defense systems.

Key Takeaways

  • Claude Mythos Preview leads in network takeover simulations, outperforming rivals
  • Tests revealed limitations: no success in industrial control scenarios
  • Business recommendation: strengthen basic defenses against automated threats
  • Dual-use nature of AI: both attack risk and defense potential
  • Future evaluations will include realistic conditions with active resistance

Development Outlook

Upcoming tests are expected to shift toward more realistic environments, including live defensive countermeasures. This will better assess AI performance in dynamic, real-world settings. For the industry, Claude’s breakthrough signals an urgent need for balance: defensive innovation must outpace offensive tools.

— Editorial Team

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