Research & practice

AI Security

Artificial intelligence can support cybersecurity work when it is applied to well-defined tasks, fed appropriate data, and kept under human oversight. It is not a replacement for engineering judgment, authorized testing, or incident response process.

Topics

Short guides on how models fail, how they leak data, and how to use them defensively. Each card opens a full note.

Foundations

AI Security Fundamentals

What changes when software can generate text, code, and decisions — and which controls still apply.

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Attacks & defenses

Prompt Injection

How untrusted text can steer a model — and how to limit what that steering can do.

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Data risk

AI Data Leakage

How prompts, logs, and connected tools can expose information that was never meant to leave a session.

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Data risk

AI Privacy

Minimizing personal data in prompts, understanding retention, and keeping processing agreements in view.

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Practice

AI-Assisted Cybersecurity

Where models help with detection, analysis, and drafting — and where they must stay behind a human review.

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Practice

Responsible AI

Oversight, authorized use, and the limits of generated advice in a security context.

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Practice

AI Security Checklist

Practical defensive checks for teams that call models or ship AI-assisted features.

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