Google reports LLMjacking attacks targeting stolen AI credentials
Google Threat Intelligence Group, as reported by TechRadar, says attackers are stealing AI API keys and cloud credentials to run unauthorized AI workloads, establish proxy services and generate large cloud bills for victims. The report describes a growing LLMjacking ecosystem, including credential-pooling gateways known as “LLM Mixers,” while one case involving UNC6993 reportedly accumulated more than $100,000 in charges.
The findings highlight a direct risk to AI infrastructure credentials and budgets, while showing that unauthorized model access is becoming a specialized cybercrime market.
- Cybercriminals are stealing AI API keys and cloud credentials to hijack expensive LLM services and infrastructure
- Stolen access is used to run AI workloads, create proxy services, and rack up massive bills for victims
- Google warns “LLMjacking” is evolving into a specialized cybercrime ecosystem with dedicated monetization operators
Threat actors are using large language models (LLM) to support almost every stage of a cyberattack, from researching potential victims to developing malware and automating various attacks. However, using AI is not cheap, and for those eager to use frontier models, costs can stack up relatively quickly.
But cybercriminals are used to stealing things, so why not steal someone else’s tokens, too?
A new report from Google’s Threat Intelligence Group (GTIG) says that different hacking groups are doing exactly that and that the practice - known as LLMjacking - has been steadily growing more popular over the last couple of years.
Most groups start by focusing either on publicly exposed LLM endpoints, or on obtaining valid LLM application programming interface (API) keys. In many cases, the crooks would use exposed or stolen cloud identity tokens (IAM credentials, Service Account keys, GitHub Personal Access Tokens, and active session tokens) to establish an initial foothold into the target organizations’ infrastructure.
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