Adversarial AI: Prompt Injections

"Prompt injections represent another class of attacks that involve the malicious insertion of prompts or requests in LLM-based interactive systems, leading to unintended actions or disclosure of sensitive information. The prompt injection is somewhat related to the classic structured query language (SQL) injection attack in cybersecurity where the embedded command looks like a regular input at the start but has a malicious impact. The injected prompt can deceive the application into executing the unauthorized code, exploit the vulnerabilities, and compromise security in its entirety. More recently, security researchers have demonstrated the use of indirect prompt injections. These attacks on AI systems enable adversaries to remotely (without a direct interface) exploit LLM-integrated applications by strategically injecting prompts into data likely to be retrieved. Proof-of-concept exploits of this nature have demonstrated that they can lead to the full compromise of a model at inference time analogous to traditional security principles. This can entail remote control of the model, persistent compromise, theft of data, and denial of service. As advanced AI assistants are likely to be integrated into broader software ecosystems through third-party plugins and extensions, with access to the internet and possibly operating systems, the severity and consequences of prompt injection attacks will likely escalate and necessitate proper mitigation mechanisms."