About AI Sec Digest

Curated AI security news, from primary sources.

What this site covers

AI Sec Digest explains AI security frameworks, risks and detection, with every claim linked to its source. Each article links to the standard, advisory, paper or vendor post it draws on, so it can be checked against the original rather than taken on trust.

• AI security frameworks and standards
• LLM application risks
• Detection guidance: AI phishing, AI-written email and adversarial inputs
• Annual retrospectives and reading guides

9 articles are published so far. New ones are announced on the RSS feed.

Start here

The feed runs newest-first, which is the wrong order for a first visit. These are the standing reference pieces:

• AI security frameworks compared — How NIST AI RMF, MITRE ATLAS, the OWASP LLM Top 10, ISO/IEC 42001 and the EU AI Act divide the work.
• The OWASP Top 10 for LLM Applications — A category-by-category walkthrough of the 2025 list.
• Telling if an email was written by AI — Where AI-detector scores help, where they mislead, and which manual checks still hold.
• Adversarial examples in machine learning — How evasion attacks work, why they transfer between models, and the defenses that hold up.
• Detecting AI-generated phishing — What replaced bad grammar as a signal, and which checks still hold.
• Building an AI security weekly digest — Which categories to track, which primary sources to read, and on what cadence.

To read this site on a cadence and topic set of your own choosing rather than in publication order, the digest builder re-orders the same coverage against a role lens and a source-trust floor.

How these articles are produced

Articles here are researched from primary sources: vendor and project documentation, published standards and specifications, research papers and preprints, and measurements published by whoever took them. Drafts are produced with AI assistance and then edited against those cited sources before anything is published.

No article on this site is based on first-hand testing in a private lab, and nothing here should be read as a measurement report of its own. Where a number appears, it comes from a source that is named, so you can check the original instead of taking this site's word for it.

Everything is published under a single editorial byline. That byline is a publishing identity for the site, not a claim about a named individual, and it does not carry professional credentials.

Corrections

Corrections are welcome. If something here is wrong, out of date, or attributed to the wrong source, email hello@aisecdigest.com with the page address and what it should say. Substantive corrections are made in the article itself rather than quietly dropped.

How this site is funded

This site currently runs no affiliate links, sponsored posts, display advertising or paid placements. If that changes, the disclosure page will say so.

Contact

Email: hello@aisecdigest.com
Site: aisecdigest.com
Published by: AI Sec Digest Editorial

See also the privacy policy, the terms of use, and the editorial disclosure.