AntiLM

Anti-Cyberattack

• Hacking Back the AI-Hacker: Prompt Injection as a Defense Against LLM-driven Cyberattacks

Large language models (LLMs) are increasingly being harnessed to automate cyberattacks, making sophisticated exploits more accessible and scalable. In response, propose a new defense strategy tailored to counter LLM-driven cyberattacks. We introduce Mantis, a defensive framework that exploits LLMs’ susceptibility to prompt injections to undermine malicious operations. Upon detecting an automated cyberattack, Mantis plants carefully crafted inputs into system responses, leading the attacker’s LLM to disrupt their own operations (passive defense) or even compromise the attacker’s machine (active defense).

Anti-Agent

• Attacking Vision-Language Computer Agents via Pop-ups

• Watch Out for Your Agents! Investigating Backdoor Threats to LLM-Based Agents

• Evil Geniuses: Delving into the Safety of LLM-based Agents

• Testing Language Model Agents Safely in the Wild

Anti-Virus

• prompt injection in VirusTotal