aiqbench analysis
Attackers are abusing stolen cloud credentials and exposed LLM endpoints to run up large, fast-moving bills, with some victims losing up to $1 million before access was cut off. For AI teams, the practical lessons are to treat LLM API keys as high-value secrets, monitor for small or unusual request patterns that evade volume-based alerts, and lock down endpoints like self-hosted Ollama servers.
Google finds ‘LLMjacking’ attackers running up $100K a day in fraudulent cloud charges
A new report out today from Google LLC’s Mandiant and Google Threat Intelligence Group finds that attackers who hijack enterprise access to large language models are running up fraudulent cloud charges of more than $100,000 in a single day. The report, “The Rise of LLMJacking: How Threat Actors Monetize Compromised Cloud and Model Resources,” covers […] The post Google finds ‘LLMjacking’ attackers running up $100K a day in fraudulent cloud charges appeared first on SiliconANGLE.
A new report out today from Google LLC’s Mandiant and Google Threat Intelligence Group finds that attackers who hijack enterprise access to large language models are running up fraudulent cloud charges of more than $100,000 in a single day. The report, “The Rise of LLMJacking: How Threat Actors Monetize Compromised Cloud and Model Resources,” covers multiple LLMjacking cases Mandiant responded to this year. At some organizations, the cumulative bill reached $1 million before access was revoked. Cryptojacking, the older way of stealing cloud compute, tends to drain resources gradually. LLMjacking charges can spike in a matter of hours.…
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