- Gambit report claims popular AI tools used in Mexico govt breach
- Claude Code + GPT‑4.1 powered exploits, scripts, and RCE
- Single attacker stole hundreds of millions of citizen records
Big enterprises might soon get Claude Mythos to patch security holes in their software, but new research claims hackers are doing just fine with Claude Cowork.
A report from security researchers Gambit claims a single threat actor targeted nine government agencies in Mexico, using Claude Code and GPT-4.1 extensively, both during planning and execution, before making off with “hundreds of millions of citizen records”.
The campaign ran from late December 2025, through mid-February 2026, during which time, roughly 75% of all remote command execution (RCE) activity was generated – and executed – by Claude Code. Furthermore, the attacker used a custom 17,550-line Python tool to pipe harvested server data through OpenAI’s API. This generated “2,597 structured intelligence reports across 305 internal servers”.
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Compressed attack timelines
During the post-mortem, Gambit said it uncovered more than 400 custom attack scripts, as well as 20 tailored exploits targeting 20 different CVEs. The attacker was using Generative Artificial Intelligence to find which vulnerabilities to exploit, and to generate the exploit code.
During the attack, the threat actor made more than 1,000 prompts, through which they generated more than 5,300 AI-executed commands in 34 sessions on live victim infrastructure.
Using AI in cybercrime is nothing new. However, this attack is a testament to what the cybersecurity industry has been warning of for years now – AI is speeding attacks up, and defenders who don’t deploy the same technology stand no chance at all:
“The campaign compressed attack timelines below standard detection and response windows,” Gambit said.
“It transformed raw reconnaissance data from hundreds of servers into structured intelligence, thus enabling a single operator to process volumes that would normally require a team. It turned unfamiliar systems into mapped targets and tailored exploits in hours, not days.”
Gambit’s researchers concluded that this AI-assisted method “represents a significant evolution in offensive capability”, which could have been avoided through standard security controls such as patching, credential rotation, network segmentation, and endpoint detection.
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