Skip to content
Welcome, thoughtbot's Giant Robots listeners!Start here
AI: Jobs, Power & Money
16APR

GPT-5.5 clears 32-step attack chain; two models in five days

4 min read
13:29UTC

The UK AI Safety Institute confirmed on 6 May 2026 that GPT-5.5 cleared the 32-step autonomous cyber attack chain benchmark, becoming the second model to do so after Claude Mythos, with AISI's Frontier AI Trends Report recording frontier cyber capability doubling every four months.

EconomicDeveloping
Key takeaway

GPT-5.5 and Claude Mythos both cleared the 32-step attack chain within five days, making it a class-level capability.

The AISI (UK AI Safety Institute, the UK government body established in November 2023 to evaluate frontier AI capabilities) published its Frontier AI Trends Report on 6 May 2026, confirming that GPT-5.5, OpenAI's frontier language model, cleared the 32-step autonomous cyber attack chain benchmark known as "The Last Ones" (TLO). GPT-5.5 achieved 71.4% on the expert cyber suite and solved the TLO benchmark end-to-end in 2 of 10 attempts. GPT-5.5 is the second model to clear the benchmark; Anthropic's Claude Mythos cleared the same threshold on 1 May 2026.

AISI's report assesses frontier cyber capability as doubling every four months. The 32-step attack chain benchmark triggered an emergency convening of five Wall Street bank CEOs by Treasury Secretary Bessent and Fed Chair Powell in April 2026, after Claude Mythos became the first model to clear it. Five days after Mythos cleared the threshold on 1 May, GPT-5.5 repeated the result on 6 May.

Two separate frontier models clearing the same benchmark within five days changes the nature of the risk assessment. A single-model capability that is deliberately kept under restricted access (as Mythos Preview was, through Project Glasswing with access limited to twelve partners) can be managed through deployment controls. A benchmark cleared by two models from different organisations within five days of each other is no longer a single-deployment governance question; it is a class of capability that has arrived across the frontier.

AISI's four-month doubling rate, if it holds, means the next iteration of the same benchmark class will be cleared by a broader set of models within months. AISI's evaluation function, confirming which models have crossed which thresholds, is doing the work that no other institution with formal standing has yet stepped in to perform. Whether that evaluation function informs regulatory action in any jurisdiction within a timeframe that is operationally relevant to the doubling rate is the question AISI's report leaves open.

Deep Analysis

In plain English

On 6 May 2026, the UK AI Safety Institute published a report confirming that GPT-5.5, an AI model from OpenAI, had passed a difficult cyber security test. The test involves completing 32 consecutive steps in a simulated computer attack without human HELP. Only one other model, Anthropic's Claude Mythos, had passed this test before, and it did so just five days earlier. The report also said that frontier AI models are getting twice as capable at cyber attacks every four months. This matters because cybersecurity has been one of the sectors least affected by AI job cuts, because the technology was not yet reliable enough to replace human security analysts. A confirmed four-month capability doubling, if it continues, changes that assumption within 12-18 months.

Deep Analysis
Root Causes

The relevance to the AI-jobs topic is the labour market implication of the four-month capability doubling that the body does not name explicitly. Cybersecurity is one of the few technology employment sectors that has remained at full employment or near it throughout the 2025-2026 restructuring cycle: demand for human cyber analysts has been resilient because autonomous cyber capability has been below the operational reliability threshold.

The AISI confirmation that two models have now cleared the 32-step benchmark changes the supply side of the cybersecurity labour market: if frontier AI models can autonomously execute 32-step attack chains at a 20% success rate today, security operations centres will face pressure to reduce analyst headcount as that rate improves toward operational reliability.

Lloyd's of London cyber underwriters base pricing partly on the probability of a successful autonomous attack on insured infrastructure, making the AISI benchmark confirmation an underwriting input. A confirmed four-month doubling of frontier cyber capability is an underwriting input that re-prices coverage upward, affecting every enterprise that carries cyber insurance.

What could happen next?
  • Risk

    Security operations centre headcount justifications at major banks and critical infrastructure operators begin to face the same AI displacement pressure as software engineering if the four-month doubling sustains through 2026.

    Medium term · 0.6
  • Consequence

    Cyber insurance pricing must incorporate the AISI-confirmed capability doubling as a loss probability input; Lloyd's and specialist cyber underwriters will reprice 2027 coverage upward.

    Short term · 0.7
  • Risk

    The absence of a second interagency convening following GPT-5.5's clearance, five days after the first model cleared the same benchmark, suggests the institutional alarm response is not scaling with the capability curve.

    Immediate · 0.65
First Reported In

Update #9 · GitLab signs the manifesto, Brussels backs out

Bloomberg / CFO Dive· 15 May 2026
Read original →
Causes and effects
This Event
GPT-5.5 clears 32-step attack chain; two models in five days
Two separate frontier models clearing the same 32-step attack chain within five days of each other confirms the benchmark is no longer a single-model capability threshold, removing the assumption that frontier cyber risk remains isolated to a single controlled deployment.
Different Perspectives
Salesforce, Synopsys and TD Bank Group
Salesforce, Synopsys and TD Bank Group
Salesforce, Synopsys and TD Bank Group each filed quarterly disclosures in late August booking restructuring charges, or none at all, without naming AI as a cause. Their silence matters because Challenger's tracker shows AI as a stated reason fell to fourth place in August even as the year-to-date AI-cut total still leads at 116,175.
Singapore, South Korea, Taiwan and Indonesia
Singapore, South Korea, Taiwan and Indonesia
Singapore launched its Skills and Workforce Development Agency on 16 September, giving citizens six months of free premium AI tools, while South Korea ring-fenced its AI tax windfall in a new Future Response Fund. Taiwan kept funding its AI build past NT$190bn and Indonesia rewired vocational training around AI literacy, betting state-built skills beat a market-led adjustment.
ver.di, CGT Fonction Publique and CCOO
ver.di, CGT Fonction Publique and CCOO
Germany's ver.di banked a 3.3% pay rise on 1 September and opened talks on a Tarifvertrag Transformation covering dismissal bans and reskilling, while France's CGT rejected Paris's AI negotiating timetable the same week. Spain's CCOO went further on 21 September, proposing to tax companies by the jobs they generate rather than wait for the next bargaining round.
BIS General Manager and Federal Reserve governors
BIS General Manager and Federal Reserve governors
The BIS's General Manager said on 10 September that AI displacement remains limited, even as the BIS's own survey found nearly 80% of firms plan to automate roles. Two Federal Reserve governors made the same point in July, arguing the labour-market data does not yet show a mass-firing event.
Bank of Canada, ONS and ECB
Bank of Canada, ONS and ECB
The Bank of Canada found the job-finding gap between AI-exposed and unexposed occupations widened from 2.2 to 13.9 percentage points since 2015-19, while separations barely moved. That framing, a hiring freeze rather than a firing wave, is echoed by the ECB's finding that euro-area AI use hit 52% of workers in 2026, concentrated among the university-educated.
Office for National Statistics
Office for National Statistics
Deferred its Transformed Labour Force Survey beyond November 2027 and disclosed a May 2026 telephone-collection failure. The ONS carries no AI-attribution layer at all, so Britain sits outside this month's cohort of measuring states by its own admission.