For years, we viewed artificial intelligence primarily as a tool for productivity. However, a new report from Google‘s threat intelligence experts suggests another reality: AI has officially become both a high-tech cybersecurity weapon and a high-value target for attackers in 2026. As companies embed these models into their core infrastructure, they are inadvertently creating a new and risky surface.
Distillation attack: The AI cybersecurity threat for 2026, according to Google
Traditionally, cyberattacks focused on breaching a network to steal a database or install ransomware. Today, attackers are increasingly interested in the “logic” behind the AI itself. John Hultquist, chief analyst at Google Threat Intelligence Group, highlights a growing trend called “distillation” or IA model extraction attacks.
In these scenarios, attackers don’t necessarily “break in” through a back door. Instead, they use legitimate access to pelt a model like Gemini with hundreds of thousands of prompts. The goal is to observe the AI’s reasoning patterns and reverse-engineer its capabilities. Essentially, they are trying to clone a multi-billion dollar asset without ever triggering a traditional security alarm.
Faster, smarter, and more Convincing
Beyond targeting the models themselves, state-sponsored groups from countries like Russia, China, Iran, and North Korea are integrating generative AI into their daily workflows. This isn’t just about writing better phishing emails—though they are doing that, too.
AI allows attackers to conduct reconnaissance that used to take weeks in just a matter of minutes. They can research specific industry conferences, translate localized context, and mimic internal corporate communications with unsettling accuracy. For cybercriminals, speed is a massive asset; it allows them to launch ransomware and move through systems faster than human defenders can patch vulnerabilities.
A machine-on-machine future
We are rapidly entering an era of “agentic” threats—AI systems capable of planning and executing multi-step campaigns with very little human help. While defenders are also using AI to scan for bugs and respond to threats in real-time, attackers currently hold a strategic advantage: they aren’t slowed down by corporate bureaucracy or risk management protocols. If an attacker’s experimental AI fails, they lose nothing; if a defender’s AI fails, the consequences are catastrophic.
As Hultquist suggests, we are leaning on machines more than ever before. In this race, the only way to keep up with an automated adversary is to embrace an equally automated defense. The human element will always provide the final judgment, but the heavy lifting of the future belongs to the algorithms.
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