Alibaba-AAIG / OysterLinks
The Oyster series is a set of safety models developed in-house by Alibaba-AAIG, devoted to building a responsible AI ecosystem. | Oyster 系列是 Alibaba-AAIG 自研的安全模型,致力于构建负责任的 AI 生态。
☆31Updated last week
Alternatives and similar repositories for Oyster
Users that are interested in Oyster are comparing it to the libraries listed below
Sorting:
- ☆50Updated last year
- ☆102Updated last year
- ☆47Updated 9 months ago
- [ECCV'24 Oral] The official GitHub page for ''Images are Achilles' Heel of Alignment: Exploiting Visual Vulnerabilities for Jailbreaking …☆28Updated 10 months ago
- AnyDoor: Test-Time Backdoor Attacks on Multimodal Large Language Models☆57Updated last year
- ☆37Updated last year
- This is an official repository of ``VLAttack: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models'' (NeurIPS 2…☆57Updated 5 months ago
- Emoji Attack [ICML 2025]☆28Updated 2 months ago
- Implementation of BadCLIP https://arxiv.org/pdf/2311.16194.pdf☆21Updated last year
- [CCS-LAMPS'24] LLM IP Protection Against Model Merging☆15Updated 11 months ago
- Code for ACM MM2024 paper: White-box Multimodal Jailbreaks Against Large Vision-Language Models☆30Updated 8 months ago
- Code for "When LLM Meets DRL: Advancing Jailbreaking Efficiency via DRL-guided Search" (NeurIPS 2024)☆11Updated 10 months ago
- [ICLR 2024] Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images☆39Updated last year
- [ICLR 2024 Spotlight 🔥 ] - [ Best Paper Award SoCal NLP 2023 🏆] - Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal…☆68Updated last year
- Code for Neurips 2024 paper "Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models"☆53Updated 8 months ago
- ☆48Updated last year
- [ICLR 2024] Towards Elminating Hard Label Constraints in Gradient Inverision Attacks☆13Updated last year
- [NeurIPS 2024] Fight Back Against Jailbreaking via Prompt Adversarial Tuning☆10Updated 10 months ago
- Code for the paper "Jailbreak Large Vision-Language Models Through Multi-Modal Linkage"☆16Updated 9 months ago
- ☆35Updated 3 months ago
- One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models☆51Updated 8 months ago
- ☆61Updated 5 months ago
- ☆23Updated last year
- [COLM 2024] JailBreakV-28K: A comprehensive benchmark designed to evaluate the transferability of LLM jailbreak attacks to MLLMs, and fur…☆74Updated 4 months ago
- A package that achieves 95%+ transfer attack success rate against GPT-4☆23Updated 10 months ago
- Code for NeurIPS 2024 Paper "Fight Back Against Jailbreaking via Prompt Adversarial Tuning"☆17Updated 4 months ago
- ☆23Updated 9 months ago
- Repository for the Paper: Refusing Safe Prompts for Multi-modal Large Language Models☆18Updated 11 months ago
- [ICML 2024] Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models.☆74Updated 7 months ago
- [ACL 2024] CodeAttack: Revealing Safety Generalization Challenges of Large Language Models via Code Completion☆52Updated 10 months ago