AI security means keeping AI systems, the data they use and the people who depend on them safe from attack and misuse. It covers two kinds of problems. The first is ordinary software flaws that happen to sit inside AI products, such as a bug that lets an outsider run their own commands on an AI server. The second is attacks aimed at how AI itself works, like prompt injection or data poisoning. For example, someone could send a carefully worded message to a chatbot on your website and trick it into sharing information it was told to keep private. AI security is close to AI safety, but it is not the same thing.
Why it matters
When your organization starts using an AI tool, you take on its weak spots along with its benefits. Ask any vendor three questions: how they find and fix security flaws, how fast they release updates, and what stops their tool from being tricked into leaking your data. Keep the AI products you use up to date. Securaity’s advisories track known software flaws in 30 AI products. The LLM security basics guide is a good next step.
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