CryptoAILab/Awesome-LM-SSP

• highreadme#1

  Explicitly define 'LM-SSP' in the README introduction

  Why:

  CURRENT

  ## 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).

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  ## 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).

  OpenDoneDismiss
• highreadme#2

  Reposition README H1 to include full name and clarify resource type

  Why:

  CURRENT

  # Awesome-LM-SSP

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

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• mediumtopics#3

  Add more specific 'awesome-llm' topics

  Why:

  CURRENT

  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

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Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• CATEGORY QUERY

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

  you: not recommended
  AI recommended (in order):

  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 recommended 7 alternatives but never named CryptoAILab/Awesome-LM-SSP. This is the gap to close.

  Show full AI answer
• CATEGORY QUERY

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

  you: not recommended
  AI recommended (in order):

  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 recommended 7 alternatives but never named CryptoAILab/Awesome-LM-SSP. This is the gap to close.

  Show full AI answer

• 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 did not name CryptoAILab/Awesome-LM-SSP — likely talking about a different project

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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

  pass
  ✓AI named CryptoAILab/Awesome-LM-SSP explicitly

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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

  pass
  ⚠AI did not name CryptoAILab/Awesome-LM-SSP — likely talking about a different project

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?