Countering misuse of AI: September 2026 / Anthropic

Detecting and countering misuse of AI: September 2026Cyber operationsRead moreSurveillance operationsRead moreInfluence operationsRead moreConventional weaponsRead moreBiological misuseRead moreIllicit distillationRead moreOver the past eight months, our Threat Intelligence team identified and disrupted operations in which threat actors tried to use Claude for malicious activity. In this report, we share case studies from those operations and describe how malicious use of Claude has evolved since our previous threat reports in March, August, and November 2025. In each case, we disrupted the activity, used what we learned to strengthen our safeguards, and shared intelligence with authorities and industry partners, where appropriate.This report covers activity we disrupted between December 2025 and August 2026 across seven harm areas: cyber operations, influence operations, surveillance, scams and fraud, biological misuse, conventional weapons development, and distillation. Claude Haiku, Sonnet, and Opus models were used. None of the misuse cases involved the use of Claude Fable or Mythos-class models, with the exception of one illicit distillation case.The cases we share here aren’t typical misuse, but rather examples of the most notable and novel threat activity we’ve identified to date. We’re publishing this work because we believe we have a responsibility to disclose malicious misuse of our services. As models become increasingly capable, their risks will increase, unless AI developers and society’s defenders act to make them safer.The threat actors covered in this report include suspected state-sponsored groups, financially motivated criminals, commercial spyware vendors, state propaganda institutions, and politically motivated individuals. The cases range from a network of fake dating apps designed to defraud users to surveillance systems built to identify and monitor dissidents.Sophisticated and persistent threat actors continuously test our safeguards and try to circumvent the technical measures we use to detect and prevent misuse. We’ll continue to evolve our safeguards and coordinate with our partners to improve our ability to detect, disrupt, and prevent future misuse.We hope that the findings in this report will help other developers recognize similar patterns on their own platforms, give governments and civil society a clearer view of how emerging threats take shape, and strengthen collective defenses.AI-augmented cyber operationsCyber operations: From assistant to orchestratorOver 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.TrendsSophisticated attacks no longer require sophisticated attackersThe 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.For threat intelligence investigators, sophistication has stopped being a reliable signal of who is behind an operation. Every layer of offensive operations has been uplifted by AI, from reconnaissance and tool development to data processing and exploitation. An example of this uplift in capabilities is documented in case study GTG-50014 (described below). The net effect of this uplift in capabilities is access to an increased breadth and depth of knowledge, which in turn drives increased speed of capability development and implementation.In November 2025, we documented an operating model used by a suspected state-sponsored campaign to carry out autonomous attacks. That operating model has now proliferated across every class of actors we investigated. Publicly available offensive agent frameworks, like PentAGI, reproduce much of the same scaffolding for anyone who downloads them. This scaffolding effectively automates each step of the cyber kill chain. The operators behind observed cases range from state services to lone individuals, across a widening set of countries. An example of this adoption of AI-enabled kill chains is documented in case study GTG-20006. As models continue to evolve and improve, we assess that more actors, from lone wolves to organized entities, will continue to adopt AI frameworks to enable more sophisticated cyber attacks at greater speed and scale.AI’s role in cyber operations has become increasingly autonomousA majority of the operations described in this report were enabled by AI via direct execution or orchestration. The use of AI went beyond simple questions and responses from a chatbot but rather involved the use of multi-agent frameworks executing reconnaissance, exploitation, and data exfiltration. Humans remained in the loop by setting the targets of attacks and reviewing exfiltration. An example of this trend is GTG-20006. This actor developed an AI-assisted workflow that automatically rebuilt and re-deployed their toolkit if it was detected by security products.GTG-20006: Russian espionageHistorically, cyber espionage actors have followed a pattern of developing and deploying custom toolkits designed to evade detections. Actors would use these tools until defenders identified and built signatures to detect and block them, and there would then begin a new cycle of evasion and detection. Robust defenses and detections therefore created increased costs for adversaries. Now, however, the adoption of AI threatens to quickly and easily subvert defenders’ ability to impose costs on adversaries via static detections alone.GTG-20006 is an actor who has increased their speed by automating their operations using AI. Our attribution is consistent with public reporting linking the actor to Midnight Blizzard. One of the operators is a Russian speaker using the handle “JackPoterz” whose tradecraft and targeting are consistent with Russian state-nexus espionage. They ran operations attacking military intelligence targets in Ukrainian and European governments, as well as diplomatic and defense organizations and individuals connected to US foreign policy. We observed GTG-20006 operate through customized AI-driven workflows that automated much of their operations from development, infrastructure acquisition, phishing, persistence through command and control, to data exfiltration.GTG-20006 employed a custom toolkit composed of two families of Windows-based implants, a mobile exploitation kit, a credential stealing tool that targets browser password stores, a phishing platform designed to mimic priority targets like government organizations, and an administrative console used to manage compromised accounts. Each of these tools was managed and re-tooled as needed during the cyber operations through AI-assisted workflows.The actor also used AI to monitor how well their tools evaded detections from known security defenses. If their monitoring AI agents identified that any of their deployed malware was detected by a security product, agents would then set about the process of autonomously modifying and rebuilding the malware to evade the existing detections. The agents were designed to continue iterating on GTG-20006’s toolkit until it was undetected. At that point, the tools were staged for live operations from disposable hosting servers where victim traffic was directed to retrieve the malware during their many cyber operations, including phishing, ClickFix, and DNS hijacking schemes.The actor also used AI to drive their phishing operations. They developed AI-driven workflows to research then register domains and then configure the hosting infrastructure used to send phishing emails. Additional workflows were developed to send the emails and monitor the C2 channels for successful compromises. The human actor engaged primarily to modify Claude Code skills that drove the workflows when they needed to be refined.Our investigation identified more than 20 distinct organizations targeted in the actor’s operational planning, reconnaissance, and live operations. They included government ministries, defense and intelligence bodies, embassies and diplomatic missions, think tanks, and