AI-Driven Attacks & Prompt Injection
Attackers use AI for flawless phishing (37% of AI attacks) and deepfake impersonation (35%), and target AI systems directly via prompt injection and data poisoning. Defenses include out-of-band verification, input validation, and output filtering, controls traditional security never needed.
AI on offense
AI makes phishing perfect and impersonation convincing. Deepfake voice and video defeat the human instinct to trust a familiar voice, so identity can no longer be verified by sound or sight alone.
16% of breaches now involve AI-driven attacks, led by AI-generated phishing (37%) and deepfake impersonation (35%) (IBM, 2025). The old defenses, spotting bad grammar, recognizing a voice, no longer work. High-stakes requests must be verified through a separate, pre-agreed channel, because a convincing call or video is no longer proof of anything.
Attacks on the AI itself
Prompt injection tricks a model into ignoring its instructions; data poisoning corrupts what it learns. Any AI that accepts external input is a new attack surface requiring input validation and output filtering.
Any content an AI ingests from outside, a web page, an email, a document, can carry a hidden instruction. Validate inputs, constrain what the model is allowed to do, and filter outputs, exactly as you would sanitize any untrusted data.
Frequently asked questions.
What is prompt injection?
An attack where hidden instructions in content the AI reads, a web page, email, or document, trick it into ignoring its real instructions and doing something harmful. Defend it by treating all external input as untrusted, validating inputs, and constraining what the model can do.