Original Post: Agent Hijacking: The true impact of prompt injection attacks
The article discusses the evolution of Large Language Models (LLMs) like OpenAI’s GPT and Google’s Gemini, highlighting their integration into everyday tools and their transformative potential in the machine learning (ML) and artificial intelligence (AI) landscape. It mentions the development of “agents,” AI programs capable of making autonomous decisions and actions through APIs and user interfaces.
LLMs, while powerful, pose new security risks, such as prompt injection attacks where user input can manipulate the LLM to perform unintended actions. The article illustrates how agents can connect LLMs to tools like LangChain, which uses an LLM as a “reasoning engine” that autonomously interacts with external APIs.
The article notes the susceptibility of agent-based systems to prompt injections and traditional vulnerabilities. For instance, in LangChain, a vulnerability was found where the LLM could be manipulated to run arbitrary code via SQL injections. This vulnerability was patched following its discovery.
Additionally, the article emphasizes the importance of traditional application security practices and the need for new AI-specific security techniques. It concludes by highlighting the creation of the LLM Security Verification Standard, a collaborative effort to provide best practices for securing LLM applications, ensuring that organizations can build reliable and secure AI-driven systems.
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