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LLMJacking: Threat Actors Rack Up $1M in Fraudulent Cloud Charges

LLMJacking: Threat Actors Rack Up $1M in Fraudulent Cloud Charges

First seen 2 Nov 2026, 17:45 UTC • •

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ThreatCluster AI
ThreatCluster •November 2, 2026 at 19:47 UTC
  • •LLMJacking incidents led to over $1 million in fraudulent charges for some organizations.
  • •Attackers primarily exploited exposed cloud identity tokens and misconfigured service accounts.
  • •The threat landscape includes multiple financially motivated clusters operating globally.

Mandiant and Google Threat Intelligence Group reported multiple incidents of 'LLMJacking' in 2026, where attackers hijacked enterprise access to large language models (LLMs), resulting in fraudulent cloud charges exceeding $100,000 in a single day. Victims, including organizations in North America, South America, and Asia-Pacific across various sectors, faced cumulative charges reaching $1 million before access was revoked. Unlike cryptojacking, LLMJacking can generate rapid spikes in costs. Attackers primarily exploited exposed or stolen cloud identity tokens, such as service account keys and GitHub personal access tokens, to gain initial access. A notable group, UNC6993, compromised a cloud instance through a misconfigured service account key and created a fake portal to harvest access tokens. The report highlights a growing underground market for LLM credentials and emphasizes the need for organizations to secure their cloud infrastructure against these threats.

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Timeline

2026-04-10
CVE-2026-40217 published
Vulnerability assigned a CVE identifier and published in the National Vulnerability Database.
MITRE
2026-11-02
Mandiant report on LLMJacking released
Mandiant and Google Threat Intelligence Group disclosed findings on LLMJacking, detailing the financial impact on organizations.
Siliconangle

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Common questions

What sectors are affected by LLMJacking?
Victims include organizations in financial services, retail, technology, and transportation.
How do attackers gain access to LLMs?
Attackers typically exploit exposed or stolen cloud identity tokens, such as service account keys.
What should organizations do to protect against LLMJacking?
Organizations should secure their cloud infrastructure, particularly by protecting LLM endpoints and managing identity tokens carefully.