An LLM-powered security scanner is a triage tool that uses a language model to classify, summarize, or flag suspicious files, code, or logs. It can help analysts review large volumes of content faster by highlighting risky patterns, extracting indicators, or explaining why a sample looks dangerous.
In cyber security, these scanners matter because attackers can try to manipulate the model with adversarial text, hidden instructions, or prompt injection inside the file being inspected. If the model treats untrusted content as instructions, it may refuse analysis, give a misleading summary, or miss malicious behavior. Defenders should treat model output as one signal among many and back it with deterministic checks such as signatures, sandboxing, static analysis, and human review.


