{"id":43172,"date":"2026-07-31T18:41:10","date_gmt":"2026-07-31T18:41:10","guid":{"rendered":"https:\/\/fidelissecurity.com\/?post_type=glossary&p=43172"},"modified":"2026-07-31T18:41:10","modified_gmt":"2026-07-31T18:41:10","slug":"llmjacking","status":"publish","type":"glossary","link":"https:\/\/fidelissecurity.com\/es\/glossary\/llmjacking\/","title":{"rendered":"LLMjacking"},"content":{"rendered":"\t\t
\n\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
\n\t
\n\n \n
\n <\/path><\/path><\/path><\/path><\/path><\/path><\/path><\/path><\/path><\/path><\/g><\/circle><\/circle><\/path><\/g><\/svg> <\/div>\n \n \n <\/div>\n
\n
\n

LLMjacking Defined<\/h2> <\/div>\n

LLMjacking is a cyberattack in which threat actors gain unauthorized access to Large Language Model (LLM) services or AI infrastructure and exploit them for their own purposes. Instead of targeting the AI model itself, attackers typically steal API keys, compromise user accounts, or exploit misconfigured cloud environments to use paid LLM services without authorization. This can lead to financial losses, service disruptions, data exposure, and increased security risks for organizations relying on AI-powered applications.<\/p><\/div> <\/div>\n <\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

As enterprises rapidly adopt generative AI across customer support, software development, content creation, and security operations, understanding what is LLMjacking and how to prevent it has become an essential part of modern cybersecurity.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t

How Does LLMjacking Work?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

LLMjacking usually begins with attackers obtaining unauthorized access to an organization’s AI resources. Common attack methods include:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t\t\t