AI Security Hunt AI Security Hunt publishes practical guides for deploying AI securely and securing AI already in use.
Understand AI security problems in business workflows without needing technical acronyms first.
10 guidesMap AI security problems to control outcomes, frameworks, operating evidence, and evaluation questions.
Featured articles
For Business Leaders
Learn how companies can reduce data, compliance, and security risk when employees use public AI tools and embedded AI copilots.
How can business teams use AI tools without creating avoidable data, compliance, and security risk?
For Business Leaders
Understand how internal AI assistants can expose company data, why access control matters, and what buyers should verify before deployment.
How can internal AI assistants expose sensitive data or make unauthorized information easier to access?
For Business Leaders
Learn what buyers should define before comparing AI security vendors across use case, control surface, control outcomes, enterprise readiness, and evidence.
What should buyers define before speaking with AI security vendors?
For Security Teams
A guide stub for understanding prompt injection, instruction manipulation, and control questions for AI applications.
What is prompt injection, why does it matter, and what controls can reduce the risk?
For Security Teams
A guide stub for mapping sensitive data exposure across AI prompts, outputs, retrieval, embeddings, logs, training, and SaaS tools.
Where can sensitive data leak across prompts, outputs, retrieval, embeddings, logs, training, and SaaS AI tools?
For Security Teams
A guide stub for understanding where runtime AI controls sit, what they inspect, and what evidence buyers should request.
Where do runtime AI controls sit, what can they inspect, and what proof should buyers ask for?
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