GoKawiilAI-augmented cyber operations
Cyber operations: From assistant to orchestrator
Over the past six months, our Threat Intelligence team identified and disrupted a series of cyber operations in which threat actors used Claude. The actors included suspected state-sponsored groups, financially motivated criminals, and politically motivated individuals. This section presents some of those cases.
Throughout these case studies, the report will reference Generative Threat Groups (GTGs). These are Anthropic’s internal designators for actors observed to be abusing AI. The report also attempts to measure uplift, a term we use to describe the AI capability boost, or how much more harm was caused with AI versus without AI. We view uplift through the lens of speed, scale, and depth, and attempt to determine how an actor’s adoption of AI meaningfully impacts each of these traits.
Many commentators focus on the risk of AI developing exploits at scale. While this is a danger, the risk from AI adoption is more pronounced across the cyber kill chain, where adversaries can operate faster, across a broader and deeper surface area, with fewer resources.
The cases span the period from December 2025 through August 2026. In all cases, Claude Haiku, Sonnet, and Opus models were used; no malicious activity was found on Claude Fable or Mythos (which has a series of safeguards in place that greatly reduce its ability to perform harmful cyber tasks). In each case we disrupted the activity involved, strengthened our AI safeguards based on what we learned, and shared intelligence with authorities and industry partners where appropriate.
In the following report, we begin by discussing the key trends that we’ve observed in these cyber operations, then move to reporting the case studies and how they highlight those trends.
Trends
Sophisticated attacks no longer require sophisticated attackers
The cybersecurity skills of AI models means that AI has collapsed the labor and tooling gap that used to separate well-resourced, state-sponsored operations from individual operators. In the case studies we report below, a hacktivist using stolen API keys, disparate financially motivated individuals, and a state espionage operator each sustained multi-victim campaigns that, even just a year ago, would have required many skilled operators and specialist knowledge.
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