We recently argued that an inflection point had been reached in cybersecurity: a point at which AI models had become genuinely useful for cybersecurity operations, both for good and for ill. This was based on systematic evaluations showing cyber capabilities doubling in six months; we’d also been tracking real-world cyberattacks, observing how malicious actors were using AI capabilities. While we predicted these capabilities would continue to evolve, what has stood out to us is how quickly they have done so at scale.
In mid-September 2025, we detected suspicious activity that later investigation determined to be a highly sophisticated espionage campaign. The attackers used AI’s “agentic” capabilities to an unprecedented degree—using AI not just as an advisor, but to execute the cyberattacks themselves.
The threat actor—whom we assess with high confidence was a Chinese state-sponsored group—manipulated our Claude Code tool into attempting infiltration into roughly thirty global targets and succeeded in a small number of cases. The operation targeted large tech companies, financial institutions, chemical manufacturing companies, and government agencies. We believe this is the first documented case of a large-scale cyberattack executed without substantial human intervention.
Upon detecting this activity, we immediately launched an investigation to understand its scope and nature. Over the following ten days, as we mapped the severity and full extent of the operation, we banned accounts as they were identified, notified affected entities as appropriate, and coordinated with authorities as we gathered actionable intelligence.
This campaign has substantial implications for cybersecurity in the age of AI “agents”—systems that can be run autonomously for long periods of time and that complete complex tasks largely independent of human intervention. Agents are valuable for everyday work and productivity—but in the wrong hands, they can substantially increase the viability of large-scale cyberattacks.
These attacks are likely to only grow in their effectiveness. To keep pace with this rapidly-advancing threat, we’ve expanded our detection capabilities and developed better classifiers to flag malicious activity. We’re continually working on new methods of investigating and detecting large-scale, distributed attacks like this one.
In the meantime, we’re sharing this case publicly, to help those in industry, government, and the wider research community strengthen their own cyber defenses. We’ll continue to release reports like this regularly, and be transparent about the threats we find.
How the cyberattack worked
The attack relied on several features of AI models that did not exist, or were in much more nascent form, just a year ago:
Intelligence. Models’ general levels of capability have increased to the point that they can follow complex instructions and understand context in ways that make very sophisticated tasks possible. Not only that, but several of their well-developed specific skills—in particular, software coding—lend themselves to being used in cyberattacks. Agency. Models can act as agents—that is, they can run in loops where they take autonomous actions, chain together tasks, and make decisions with only minimal, occasional human input. Tools. Models have access to a wide array of software tools (often via the open standard Model Context Protocol). They can now search the web, retrieve data, and perform many other actions that were previously the sole domain of human operators. In the case of cyberattacks, the tools might include password crackers, network scanners, and other security-related software.
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