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How to build an AI security reading list from the ai folder with Hacker

Collect AI security, LLM engineering, and AI-assisted incident response references in one list.

Authorization notice. Hacker is dual-use. Only use it on software, sites and systems you own or have explicit permission to test.

Who it is forA security engineer or AI product owner who needs to review LLM risks before shipping a feature.

The problemAI security material is spread across many sources, which makes a focused review slow and uneven.

The outcomeA reading list grouped by AI security, LLM engineering, incident response automation, and AI governance.

What you need first

  • A web browser to open the GitHub repository
  • Git, if you want a local copy of the files
  • A clear learning goal, such as a domain, a certification, or an AI security topic
  • Authorized environments only for any hands-on offensive security material

Steps

  1. Open the ai folder in https://github.com/TaroYamada08/Hacker.
  2. Read the top-level files to see how AI security, LLM engineering, and incident response automation are organized.
  3. Open the AI ethics, privacy, and governance resources and list the items that match your review.
  4. Group the chosen items into the four topics and add a one-line note for each.
  5. Share the grouped list with your team as the starting point for an AI risk review. (inferred, check the README)

Prompt for your agent

Using the repository TaroYamada08/Hacker, read the ai folder and produce a grouped reading list with four topics: AI security, LLM engineering, AI-assisted incident response, and AI ethics, privacy, and governance. Output three items per topic with file paths. Verify that each path exists in the repository.

Caveat. The README describes the ai folder only at a high level, so check each resource's content and date before citing it in a review.

Use this in your AI agent

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Using the Deduped MCP, get the setup steps for TaroYamada08/Hacker and "Build an AI security reading list from the ai folder"

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claude mcp add --transport http deduped https://dedupedai.com/mcp

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Third-party repos we don't own. AI-written use cases can be wrong. Disclaimer