A field manual for AI security paranoia

What it does

This is an awesome-list that catalogs hundreds of resources for securing AI systems—frameworks, standards, datasets, tools, and research papers. It gathers NIST and OWASP guidance, red-teaming playbooks, incident-response trackers, and datasets for jailbreaks and deepfakes into one sprawling index. If you need to know which standard to audit against or where to find a deepfake detection dataset, this is your card catalog.

The interesting bit

Instead of dumping URLs by format, the list organizes them by security lifecycle—governance, verification, testing, incident response—which mirrors how actual teams manage risk. It also tracks emerging architecture shifts like agentic AI and MCP server security, suggesting the curators are trying to stay ahead of the tooling curve rather than cataloging last year’s news.

Key highlights

• Governance to operations coverage: NIST AI RMF, ISO 42001, OWASP LLMSVS, red-teaming guides, and DoD tailoring guides.
• Dedicated sections for modern attack surfaces: prompt injection datasets, jailbreak collections, deepfake resources, and agentic-system threats.
• Practical operational aids: incident-response playbooks, supply-chain security references, publicly disclosed vulnerability trackers, and benchmarking lists.
• Curated by AISecHub with visible commercial backing from InnovGuard.

Caveats

• The README is overwhelmingly long; expect to use your browser’s find function or scroll through a massive table of contents.
• A prominent InnovGuard sponsor banner sits at the top, so the curation carries commercial visibility.
• This is strictly an index: no original code, scanners, or runtime tools live here.

Verdict

Security architects, GRC analysts, and red teamers wrestling with LLM or agentic deployments should bookmark this. If you want a single installable scanner or a five-minute quickstart, this is not it—this is a reading list.