- Google said threat actors hijacked enterprise access to large language models in incidents affecting three regions and four sectors.
- Google said fraudulent resource-consumption charges exceeded $100,000 in a day in individual incidents and reached $1 million at some organizations.
- The campaign monetized foundation models through token proxying, automated model streaming and GPU provisioning.
Google said on Nov 2, 2026, that threat actors hijacked enterprise access to large language models in multiple 2026 incidents.
The activity affected organizations in North America, South America and Asia Pacific across financial services, retail, technology and transportation. Google said fraudulent resource-consumption charges exceeded $100,000 in a single day in individual incidents, while cumulative charges at some organizations reached $1 million before access was revoked.
Google said threat actors achieved monetization and resource-hijacking of foundation models through token proxying, automated model streaming and GPU provisioning.
On this page
Exposed cloud tokens gave attackers their initial access
Google said the dominant initial access vector was exposed or stolen cloud identity tokens, including IAM credentials, service-account keys, GitHub personal access tokens and active session tokens. Attackers used those tokens to establish a foothold in target organizations’ infrastructure.
In one mid-2026 case, UNC6993 compromised a cloud instance through a misconfigured service-account key and used access to grant further access to an LLM API. It also hosted a session-hijacking page that masqueraded as an application portal to join a group of LLM users.
The group validated exposed LLM API keys with automated sweeps using minimal single-token requests, with max_tokens=1. Google said the approach let the attackers confirm stolen keys while remaining undetected by endpoint detection and response and security information and event management volume alerts.
Attackers expanded access before monetizing model services
After gaining a foothold, threat actors worked to escalate privileges, solidify access and conduct internal reconnaissance. They searched repositories, logs, databases and secret managers for additional credentials.
Across the intrusions, attackers abused cloud identity permissions and virtual-machine configurations to escalate privileges and maintain persistent access. Google said they created unauthorized accounts, injected SSH keys and generated temporary high-privilege credentials to maintain access and exfiltrate secrets.
UNC6993 attempted to generate additional API keys and enable associated services in victim cloud projects, quickly accumulating more than $100,000 in billing charges.
Google described a division of labor behind LLMjacking
Google identified a division between actors that establish initial access to compromised environments and operators that manage downstream monetization infrastructure, which it called LLM Mixers.
Google said Jet Night offers an unlimited token plan for about $60 per month with alleged access to frontier models, a consumer service level that would typically run between $100 and $250 per month.
Google said defenders should prioritize detection of modifications to LLM accounts and services and treat any unauthorized enablement as a critical security event.
What to do now
- Treat any unauthorized enablement of cloud LLM services as a critical security event.
- Implement granular API quotas on LLM services and use spending caps to set budgets and avoid over-spending.
- Restrict and segment API keys by specific model endpoints, environments and usage limits.
- Monitor model gateway and API access logs for anomalous, low-volume requests such as max_tokens=1 or zero-temperature pings.
FAQ
What happened in the Google LLMjacking campaign?
Google said threat actors hijacked enterprise access to large language models in multiple 2026 incidents.
Who was affected by the LLMjacking incidents?
Google said organizations in North America, South America and Asia Pacific were affected across financial services, retail, technology and transportation.
How much did the fraudulent LLM charges cost?
Google said individual incidents produced fraudulent resource-consumption charges exceeding $100,000 in one day, with cumulative charges at some organizations reaching $1 million before access was revoked.
How did attackers get access to LLM services?
The dominant access vector was exposed or stolen cloud identity tokens, including IAM credentials, service-account keys, GitHub personal access tokens and active session tokens.
What are LLM Mixers?
Google used the term for operators managing downstream monetization infrastructure.
Sources
- The Rise of LLMJacking: How Threat Actors Monetize Compromised Cloud and Model Resources | Google Cloud Blog, Google CloudPrimary
- Sandbox Flipped to ‘Danger-Full-Access’: Unauthorized AI Relays Create Risk for Organizations, SymantecPrimary
- Breaking LiteLLM: From Low-Privilege User to Admin and RCE (CVE-2026-47101, CVE-2026-47102, CVE-2026-40217), Obsidian SecurityPrimary
- Google: LLMjacking attacks rack up $1 million in cloud AI charges, BleepingComputer
- Google finds ‘LLMjacking’ attackers running up $100K a day in fraudulent cloud charges, SiliconANGLE
How we checked this story
| Claim | Source | Status |
|---|---|---|
| Google said Mandiant responded to multiple LLMjacking incidents in 2026 affecting organizations across three regions and four sectors. | Google, via Google Cloud | Attributed |
| Google said LLMjacking can create fraudulent charges exceeding $100,000 in one day and reaching $1 million before access is revoked. | Google, via Google Cloud | Attributed |
| BleepingComputer reported that some organizations incurred more than $100,000 in fraudulent cloud charges per day from LLMjacking. | BleepingComputer | Attributed |
| Google said attackers primarily gained initial access through exposed or stolen cloud identity tokens, including IAM credentials, service-account keys, GitHub tokens, and session tokens. | Google, via Google Cloud | Confirmed |
| Google said threat actors used token proxying, automated model streaming, and GPU provisioning to monetize and hijack foundation models. | Google, via Google Cloud | Confirmed |
| Google said UNC6993 attempted to generate additional API keys and enable services in victim projects, quickly accumulating more than $100,000 in charges. | Google, via Google Cloud | Confirmed |
| Google said Jet Night offered an unlimited frontier-model token plan for about $60 monthly, below typical consumer pricing of $100 to $250. | Google, via Google Cloud | Confirmed |
| Obsidian said its LiteLLM research found a chained exploit path from a low-privilege user to administrator access and remote code execution. | Obsidian Security | Attributed |
| Google Cloud published its report on Nov 2, 2026. | Google Cloud | Confirmed |
| obsidiansecurity.com published its report on Sep 8, 2026. | obsidiansecurity.com | Confirmed |



