CryptoAILab/Awesome-LM-SSP

• highreadme#1

  Explicitly define 'LM-SSP' in the README introduction

  原因：

  当前

  ## Introduction 
  The resources related to the trustworthiness of large models (LMs) across multiple dimensions (e.g., safety, security, and privacy), with a special focus on multi-modal LMs (e.g., vision-language models and diffusion models).

  复制粘贴的修复

  复制

  ## Introduction 
  This is an awesome list and curated collection of resources related to the trustworthiness of large models (LMs) across multiple dimensions (e.g., safety, security, and privacy - hence 'LM-SSP'), with a special focus on multi-modal LMs (e.g., vision-language models and diffusion models).

  待办完成忽略
• highreadme#2

  Reposition README H1 to include full name and clarify resource type

  原因：

  当前

  # Awesome-LM-SSP

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  复制

  # Awesome-LM-SSP: A Curated List for Large Models Safety, Security, and Privacy

  待办完成忽略
• mediumtopics#3

  Add more specific 'awesome-llm' topics

  原因：

  当前

  adversarial-attacks, awesome-list, diffusion-models, jailbreak, language-model, llm, nlp, privacy, safety, security, vlm

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  adversarial-attacks, awesome-list, awesome-llm-security, awesome-llm-safety, awesome-llm-privacy, diffusion-models, jailbreak, language-model, llm, nlp, privacy, safety, security, vlm

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  Where can I find comprehensive resources on large language model security and privacy issues?

  你：未被推荐
  AI 推荐顺序：

  1. OWASP Top 10 for Large Language Model Applications
  2. NIST AI Risk Management Framework (AI RMF)
  3. Hugging Face Blog and Documentation
  4. Google AI/DeepMind Research Papers and Blog
  5. Microsoft Azure AI Documentation
  6. arXiv
  7. The AI Incident Database (AIID)

  AI 推荐了 7 个替代方案，却始终没点名 CryptoAILab/Awesome-LM-SSP。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  What are the best papers and tools for mitigating LLM adversarial attacks and jailbreaks?

  你：未被推荐
  AI 推荐顺序：

  1. Garak (llm-security/garak)
  2. AdvBench (llm-attacks/llm-attacks)
  3. IBM Adversarial Robustness Toolbox (ART) (Trusted-AI/adversarial-robustness-toolbox)
  4. OpenAI Evals (openai/evals)
  5. Hugging Face Transformers (huggingface/transformers)
  6. NeMo Guardrails (NVIDIA/NeMo-Guardrails)
  7. LangChain (langchain-ai/langchain)

  AI 推荐了 7 个替代方案，却始终没点名 CryptoAILab/Awesome-LM-SSP。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  pass

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of CryptoAILab/Awesome-LM-SSP?

  pass
  ⚠AI 未点名 CryptoAILab/Awesome-LM-SSP —— 很可能在说另一个项目

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts CryptoAILab/Awesome-LM-SSP in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 CryptoAILab/Awesome-LM-SSP

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo CryptoAILab/Awesome-LM-SSP solve, and who is the primary audience?

  pass
  ⚠AI 未点名 CryptoAILab/Awesome-LM-SSP —— 很可能在说另一个项目

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？