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AI Security

What are the main generative AI security risks?

NIST names 12 generative AI risks and OWASP ranks 10 for LLM apps. Here is how the two lists overlap and which ones engineers should handle first.

Oct 18, 20264 min read
AI Security

What challenges does generative AI bring to application security teams?

GenAI adds new app risks, such as prompt injection and excessive agency, plus AI written code to review. Map them to OWASP and NIST, then set clear rules.

Oct 18, 20264 min read
AI Security

How do you build a security roadmap for frontier AI use?

Build a frontier AI security roadmap on NIST's four functions, with an inventory first and OWASP risks as a test list. Here is a sequence to start now.

Oct 18, 20265 min read
AI Security

What should a security checklist for frontier AI models include?

A practical checklist for teams adopting highly capable AI models: data, access, agents, supply chain, testing and monitoring, drawn from NIST and OWASP.

Oct 18, 20264 min read
AI Security

What is federated learning and does it protect privacy?

Federated learning trains a shared model without moving raw data to one place. It reduces exposure but does not guarantee privacy. See what else you need.

Oct 18, 20264 min read
AI Security

What is explainable AI and where does it matter in practice?

Explainable AI means a system can give reasons for its outputs that people can understand and trust. NIST's four principles show how to test that claim.

Oct 18, 20264 min read
AI Security

What Is Explainable AI and How Do You Test an Explanation?

NIST frames explainable AI with four principles: explanation, meaningful, accuracy and knowledge limits. Learn how to test whether your system meets them.

Oct 18, 20264 min read
AI Security

How do you evaluate an AI coding assistant for security?

Judge an AI coding assistant by where code and secrets go, what it may run and how you can audit it. A test plan for data flow, permissions and output.

Oct 18, 20264 min read
AI Security

How to evaluate AI security claims from vendors: an engineer's checklist

Vendor AI security claims are easy to make and hard to verify. Ask for tests you can run, scope in writing, failure examples and evidence behind numbers.

Oct 18, 20264 min read

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