What Is a Prompt Injection Attack?

IBM describes prompt injection as a major cyberattack vector against LLMs in which attackers craft malicious prompts or hide payloads in data sources consumed by generative AI systems to override guardrails.[5] The article notes that prompt injection is listed as the number one security vulnerability in the OWASP Top 10 for LLM applications and can lead to sensitive data leakage, malware propagation, or system compromise in enterprise and regulated environments such as fintech and healthcare.[5]

The article explains that prompt injection is a leading vulnerability for LLM applications, where attackers craft malicious prompts or hide instructions in data sources to override system guardrails and intended behavior.[3][9] It notes that OWASP ranks prompt injection as the top LLM risk because it can cause sensitive data leakage, malware spread, or broader system compromise in high‑stakes domains like fintech and healthcare.[6][9] From a CyberSE.AI perspective, organizations should implement ongoing adversarial testing and red teaming against LLM prompts and tools, enforce least‑privilege and constrained agent capabilities, and rigorously audit agent business logic and data access flows to prevent untrusted instructions from triggering high‑risk actions.[2][6] These controls materially reduce the impact of a successful prompt injection, even if some attacks bypass in-model safety measures.