Symantec Discovers 'LLMjacking': AI Agent Autonomously Hijacks Unprotected Models for Cyberattacks
Symantec reports a new attack method called 'LLMjacking,' where an AI agent hijacks unprotected large language models to autonomously launch cyberattacks, leaving model owners with the compute bill.
Security firm Symantec has discovered a new attack method dubbed "LLMjacking," in which malicious AI agents hijack unprotected large language models (LLMs) on the internet and use them to launch cyberattacks autonomously. According to Symantec's analysis, the agent can execute up to 100,000 steps without human involvement, while the owners of the hijacked models are left stuck with the compute bill for these attacks.
The discovery stems from a Symantec honeypot system designed to mimic open AI services and lure attackers. Researchers intercepted the full working prompt of the agent in summer 2026, revealing its architecture. The attack process involves scanning for more targets, exploiting flaws in common server software, stealing databases and credentials, and installing cryptominers in the background. To bypass safety rules in commercial models, attackers employed a five-layer jailbreak technique, including assigning fake identities to the model, redefining malicious actions as "normal developer work," and suppressing the model's safety warnings.
Symantec notes that this marks a shift in how attackers use AI: rather than merely manipulating public chatbots, AI is now built into the core of offensive tools, actively seeking out models to power attacks. While individual techniques are not new, combining them into a self-directed agent makes large-scale attacks much easier to execute. Organizations running AI services should assume that unprotected endpoints will be found and probed shortly after going live. It remains unclear whether this jailbreak method fully defeats current commercial models' defenses, but the case confirms the potential threat of autonomous AI agents in the real world.