Anthropic warned users over the weekend that a threat actor is using widely available infostealer malware to hijack active Claude login sessions from infected computers, then using those sessions to run up victims’ paid usage without ever needing a password or a two-factor code.
The company said it identified six malware families in the campaign: Vidar, LummaC2, StealC, RedLine and Acreed on Windows, and Atomic Stealer, known as AMOS, on a smaller number of macOS machines. None are novel or bespoke. All are commodity stealers sold or rented on criminal dark web marketplaces, and all work the same basic way – harvesting locally stored browser credentials, autofill data and authentication cookies from a compromised machine and shipping them to an operator’s server.
Claude Session Cookies Heist
What makes the campaign notable is the target rather than the technique. Session cookies represent an already-authenticated state, so an attacker who replays a stolen Claude session token steps past both the account password and multi-factor authentication entirely. This is textbook session hijacking; the new element is that paid AI assistant subscriptions have become worth stealing as a commodity in their own right, alongside the streaming and gaming accounts that stealer log markets have traded for years.
Anthropic told affected users that the tell sign for them was a usage pattern that made no sense. Limits appearing to refill and then drain while the account owner was not using Claude was the biggest red flag.
Also read: Hacker Used Claude AI to Automate Reconnaissance, Harvest Credentials and Penetrate Networks
The company said it is signing affected users out of their sessions, removing saved payment methods from compromised accounts and refunding unauthorized charges identified during its investigation. It also stressed that the malware is not connected to Claude, was not installed through Claude and did not result from anything users did with the product. Infections trace to the usual vectors — pirated software and other illicit downloads.
A Reddit user going by the moniker “WorriedAssociate7029” received the notification from Anthropic and confirmed that he mistakenly installed an infostealer from “a reputable Russian underground forum” while downloading a pirated game. “I got fooled like a rookie by downloading a cracked game,” he said.
Intrestingly though, the user claimed of using Claude’s Opus model to detect and remove the malware.
“I use the models exclusively in permission-free mode on my entire computer,” the Reddit user said.
“Opus was very efficient. It scanned for active processes, then listed my recent downloads. It found the virus almost instantly. My prompt was very simple: “I think I downloaded a virus recently. My login credentials were stolen. Audit the malware and remove it if you find it. Report on the extent of the damage. He deactivated the virus and created a folder on the desktop containing all the relevant information (including the deactivated virus, lol).”
Anthropic has not disclosed how many accounts were affected.
The security implications reach past the billing line. AI assistant accounts increasingly hold conversation histories, uploaded documents, connected data sources and, in developer configurations, API keys and repository access. A hijacked session inherits whatever the account can reach. Organizations that have rolled out AI tools without folding them into identity and access management now have a class of high-value session token sitting in employee browsers, largely outside the monitoring applied to corporate SaaS.
Anthropic’s guidance to compromised users is the standard infostealer playbook. Change credentials across every service used on the affected machine, revoke active sessions, and actually remove the malware, since signing out does not clear an infection that will simply harvest the next session.
There is no formal regulatory hook here yet — no confirmed breach of the provider itself and no disclosure obligation triggered on Anthropic’s side. But the episode lands as regulators and standards bodies are working out how AI system security fits existing frameworks, and it illustrates a gap those frameworks have barely addressed – the weakest point in an AI deployment may be an unmanaged endpoint rather than the model or the platform.
