https://github.com/CryptoAILab/Awesome-LM-SSP
A reading list for large models safety, security, and privacy (including Awesome LLM Security, Safety, etc.).
https://github.com/CryptoAILab/Awesome-LM-SSP
List: Awesome-LM-SSP
adversarial-attacks awesome-list diffusion-models jailbreak language-model llm nlp privacy safety security vlm
Last synced: 10 days ago
JSON representation
A reading list for large models safety, security, and privacy (including Awesome LLM Security, Safety, etc.).
- Host: GitHub
- URL: https://github.com/CryptoAILab/Awesome-LM-SSP
- Owner: CryptoAILab
- License: apache-2.0
- Created: 2024-01-09T04:17:50.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2026-01-01T05:25:31.000Z (27 days ago)
- Last Synced: 2026-01-05T23:49:44.876Z (23 days ago)
- Topics: adversarial-attacks, awesome-list, diffusion-models, jailbreak, language-model, llm, nlp, privacy, safety, security, vlm
- Homepage: https://github.com/CryptoAILab/Awesome-LM-SSP
- Size: 2.67 MB
- Stars: 1,817
- Watchers: 26
- Forks: 115
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-aisecurity - Awesome LM SSP
README
# Awesome-LM-SSP
[](https://awesome.re)
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## 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).
- This repo is in progress :seedling: (manually collected).
- Badges:
- Model:
- -589cf4)
- -c7688b)
- -39c5bb)
- 
- Comment:        ...
- Venue:     ...
- ๐ฅ๐ฅ๐ฅ Help us update the list! ๐ฅ๐ฅ๐ฅ
- First, check papers through our database: [Metadata of LM-SSP](https://docs.google.com/spreadsheets/d/1i2IfQJiAdFJueoy7sTv7snn__ZJx11GfiJx8rhDyfc0/edit?usp=sharing).
- If you want to update the information of a paper (e.g., an arXiv paper has been accepted by a venue), search the paper title in our [metadata table](https://docs.google.com/spreadsheets/d/1i2IfQJiAdFJueoy7sTv7snn__ZJx11GfiJx8rhDyfc0/edit?usp=sharing) and then leave a message in the corresponding cell of the table.
- If you would like to add some paper, please fill in the following table through `ISSUE`:
| Title | Link | Code | Venue | Classification | Model | Comment |
| ---- |---- |---- |---- |---- |----|----|
| This is a title | paper.com | github | bb'23 | A1. Jailbreak | LLM | Agent |
## News
- [2025.01.09] ๐ Happy 1st Birthday to Awesome-LM-SSP! Keep Going! ๐ช
- [2024.01.09] ๐ LM-SSP is released!
## Collections
- [Book](collection/book.md) (3)
- [Competition](collection/competition.md) (5)
- [Leaderboard](collection/leaderboard.md) (5)
- [Toolkit](collection/toolkit.md) (14)
- [Survey](collection/survey.md) (40)
- Paper (2352)
- A. Safety (1183)
- [A0. General](collection/paper/safety/general.md) (30)
- [A1. Jailbreak](collection/paper/safety/jailbreak.md) (530)
- [A2. Alignment](collection/paper/safety/alignment.md) (145)
- [A3. Deepfake](collection/paper/safety/deepfake.md) (94)
- [A4. Ethics](collection/paper/safety/ethics.md) (8)
- [A5. Fairness](collection/paper/safety/fairness.md) (60)
- [A6. Hallucination](collection/paper/safety/hallucination.md) (116)
- [A7. Prompt Injection](collection/paper/safety/prompt_injection.md) (114)
- [A8. Toxicity](collection/paper/safety/toxicity.md) (86)
- B. Security (457)
- [B0. General](collection/paper/security/general.md) (16)
- [B1. Adversarial Examples](collection/paper/security/adversarial_examples.md) (105)
- [B2. Agent](collection/paper/security/agent.md) (132)
- [B3. Poison & Backdoor](collection/paper/security/poison_&_backdoor.md) (178)
- [B4. Side-Channel](collection/paper/security/side-channel.md) (2)
- [B5. System](collection/paper/security/system.md) (24)
- C. Privacy (712)
- [C0. General](collection/paper/privacy/general.md) (54)
- [C1. Contamination](collection/paper/privacy/contamination.md) (17)
- [C2. Data Reconstruction](collection/paper/privacy/data_reconstruction.md) (63)
- [C3. Membership Inference Attacks](collection/paper/privacy/membership_inference_attacks.md) (65)
- [C4. Model Extraction](collection/paper/privacy/model_extraction.md) (14)
- [C5. Privacy-Preserving Computation](collection/paper/privacy/privacy-preserving_computation.md) (131)
- [C6. Property Inference Attacks](collection/paper/privacy/property_inference_attacks.md) (8)
- [C7. Side-Channel](collection/paper/privacy/side-channel.md) (10)
- [C8. Unlearning](collection/paper/privacy/unlearning.md) (70)
- [C9. Watermark & Copyright](collection/paper/privacy/watermark_&_copyright.md) (280)
## Big love to the community โ thank you! ๐
[](https://star-history.com/#CryptoAILab/Awesome-LM-SSP&Date)
## Acknowledgement
- Organizers: [Tianshuo Cong (ไธๅคฉ็ก)](https://tianshuocong.github.io/), [Xinlei He (ไฝๆฐ็ฃ)](https://xinleihe.github.io/), [Zhengyu Zhao (่ตตๆญฃๅฎ)](https://zhengyuzhao.github.io/), [Yugeng Liu (ๅ็ฆนๆด)](https://liu.ai/), [Delong Ran (ๅๅพท้พ)](https://github.com/eggry)
- This project is inspired by [LLM Security](https://llmsecurity.net/), [Awesome LLM Security](https://github.com/corca-ai/awesome-llm-security), [LLM Security & Privacy](https://github.com/chawins/llm-sp), [UR2-LLMs](https://github.com/jxzhangjhu/Awesome-LLM-Uncertainty-Reliability-Robustness), [PLMpapers](https://github.com/thunlp/PLMpapers), [EvaluationPapers4ChatGPT](https://github.com/THU-KEG/EvaluationPapers4ChatGPT)
