Something significant just happened in AI safety research, and its implications are hard to overstate. Anthropic’s Claude Mythos Preview has become the first AI model ever to fully complete the UK AI Security Institute’s (AISI) most demanding cyberattack simulation — the 32-stage “The Last Ones” (TLO) scenario. This isn’t a benchmark PR stunt. It’s a capability milestone that the UK government’s own AI safety body is now using to revise its threat forecasting timelines.

What Happened

The UK’s AI Security Institute has been running AI models through increasingly difficult cyberattack simulations to track how quickly these systems are gaining offensive cyber capabilities. Their flagship test, “The Last Ones,” is a 32-stage simulation of a corporate network attack that requires an AI agent to autonomously execute a full kill chain — reconnaissance, lateral movement, privilege escalation, and eventual objective completion.

Until now, no model had completed it.

Claude Mythos Preview cleared the 32-stage corporate network simulation in 6 out of 10 attempts. It also became the first AI to crack an industrial control system (ICS) simulation, succeeding in 3 out of 10 attempts. OpenAI’s GPT-5.5 was the second model to complete the TLO simulation, according to AISI’s concurrent evaluation.

The CTF Milestone

Beyond the simulation results, Claude Mythos hit 73% on expert-level Capture the Flag (CTF) tasks — challenges that were previously considered unsolvable by AI. CTF competitions are the security community’s gold standard for offensive skill assessment. The 73% figure means Mythos can independently solve problems that stumped every prior model.

For context: last year’s top models were struggling to clear 20-30% of CTF challenges even at intermediate difficulty. The leap to 73% expert-level solve rate in under a year represents a capability jump that researchers are describing as “alarming” in how fast it arrived.

AISI’s Revised Timeline

Perhaps the most significant number in this report is the AISI’s revised capability doubling estimate. In November 2025, the institute estimated AI cyber capabilities were doubling every 8 months. By February 2026, they revised that to 4.7 months. Both Claude Mythos and GPT-5.5 have now “substantially exceeded” even this accelerated timeline.

The AISI’s public forecast has been wrong — twice — in the direction of underestimating how quickly these capabilities would emerge. That pattern of underestimation is itself a data point worth noting.

Why This Matters for Agentic AI

The reason this is an agentic AI story, not just a security story, is what TLO actually tests: multi-step autonomous operation. Completing a 32-stage network intrusion isn’t pattern-matching a single exploit — it requires planning, adapting to unexpected responses from defensive systems, chaining many sub-tasks together, and maintaining coherent goal pursuit across an extended operation.

That’s the same cognitive profile required for legitimate agentic work: running autonomous workflows, coordinating tools, and completing complex objectives without human hand-holding at each step. The simulation is a proxy for general autonomous capability, which is why security researchers and AI safety advocates are both paying close attention.

The Dual-Use Dilemma

Anthropic is among the most public advocates for AI safety research and maintains robust internal red-teaming. Publishing these results — even results that look alarming — is part of responsible disclosure. The data helps defenders, security teams, and policymakers understand what they’re preparing for.

But the gap between “capability demonstrated in a controlled AISI simulation” and “capability available to threat actors” is narrowing. The AISI’s revised timeline isn’t an academic curiosity: it’s the agency updating its model of how much time organizations have to prepare.

For security teams deploying AI agents internally, the implication is that agentic systems are becoming meaningful players in the threat landscape, not just tools for defenders. Organizations should be evaluating their AI agent attack surface alongside their traditional security posture.

What’s Next

AISI plans to publish the full technical evaluation report, including comparative scores for all tested models and detailed analysis of which simulation stages proved most difficult. GPT-5.5’s scores alongside Mythos’s will give the security community a clearer picture of where the capability frontier sits today — and how fast it’s moving.

Sources

  1. The Decoder — New Claude Mythos becomes the first AI model to clear all cyberattack simulations from Britain’s AI safety agency
  2. UK AI Security Institute — Official evaluation blog (aisi.gov.uk)
  3. Ars Technica — deep-dive coverage of AISI evaluations

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