Adaptive textual payloads for disrupting LLM-powered cyberattacks

A non-transitory computer-readable medium storing a set of instructions for defending against cyberattacks executed by one or more large language model (LLM)-powered agents, the set of instructions comprising:

• one or more instructions that, when executed by one or more processors of a device, cause the device to:
• deploy one or more traps throughout a computing environment to protect at least one protected entity, wherein each trap of the one or more traps is designed to exploit one or more vulnerabilities of a LLM contained within an LLM-powered agent;
• monitor, in real-time, a plurality of interactions with the deployed traps;
• detect, based on the monitored plurality of interactions, interaction behavior consistent with that of at least one LLM-powered agent of the one or more LLM-powered agents;
• and
• responsive to the detection, cause one or more of the deployed traps to initiate one or more defensive actions.

A system for defending against cyberattacks executed by one or more large language model (LLM)-powered agents comprising:

• one or more processors configured to:
• deploy one or more traps throughout a computing environment to protect at least one protected entity, wherein each trap of the one or more traps is designed to exploit one or more vulnerabilities of a LLM contained within an LLM-powered agent;
• monitor, in real-time, a plurality of interactions with the deployed traps;
• detect, based on the monitored plurality of interactions, interaction behavior consistent with that of at least one LLM-powered agent of the one or more LLM-powered agents;
• and
• responsive to the detection, cause one or more of the deployed traps to initiate one or more defensive actions.