Researchers a Gambit Security recently released a technical report detailing a single hacker who used commercial AI tools to breach nine (9) Mexican government agencies between December 2025 and February 2026, stealing hundreds of millions of citizen records and building live data forgery capabilities. The attacker relied on Anthropic’s Claude Code for active exploitation and OpenAI’s GPT 4.1/ChatGPT for large scale reconnaissance and analysis. Claude Code generated about 75% of all remote commands: 1,088 prompts produced 5,317 AI executed commands across thirty-four (34) live sessions, enabling one operator to work at the speed of a full intrusion team. GPT 4.1, driven by a custom 17,550 line Python tool, processed data from 305 internal servers and produced 2,597 structured intelligence reports, mapping complex environments in hours. Targets included the federal tax authority SAT (195M taxpayer records, domain wide credentials, live API for forged tax certificates), Mexico City’s civil registry (~220M records), Jalisco’s health and social services infrastructure (thirty-seven (37) databases, domestic violence and patient data), multiple state governments, the electoral institute, and utilities. Exposed data spans tax, civil, health, electoral, property, procurement, and sensitive victim information, creating long term risks of fraud, coercion, and political misuse. The attacker bypassed AI safeguards with false “bug bounty” framing and a long hacking manual, then used AI to rapidly refine exploits for twenty (20) known CVEs. Despite the sophistication, entry points were conventional, consisting of unpatched systems, weak credential hygiene, poor segmentation, and aging infrastructure. The case shows AI as a force multiplier, compressing attack timelines and letting a single operator scale across many networks. Defenses still hinge on fundamentals, and CTIX analysts recommend rapid patching, strong credential management, network segmentation, and behavioral detection to catch fast, AI assisted intrusions.