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jiaxiaojunQAQ
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<img src="assets/home.png" alt="OmniSafeBench-MM"/>
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<img src="assets/home.png" alt="OmniSafeBench-MM"/>
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</p>
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## 📰 News 📰
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* ***[2024/02/06] 🚀 [Initial release of OmniSafeBench-MM with 13 attack methods and 15 defense strategies]()*** 🚀
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@@ -32,42 +34,42 @@ OmniSafeBench-MM is a unified benchmark and open-source toolbox for evaluating m
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The benchmark unifies multi-modal jailbreak attack–defense evaluation, 13 attack and 15 defense methods, and a three-dimensional scoring protocol measuring harmfulness, alignment, and detail.
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## 🗡️ Integrated Attack Methods
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| Name | Title | Paper | Code | Classification |
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|------|-----------------------------------------------------------------------------------------------------------------------------|-------|------|----------------|
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| FigStep / FigStep-Pro | FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts | [link](https://arxiv.org/abs/2311.05608) | [link](https://github.com/ThuCCSLab/FigStep) | Black-box — Structured visual carriers |
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| QR-Attack (MM-SafetyBench) | MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models | [link](https://arxiv.org/abs/2311.17600) | [link](https://github.com/isXinLiu/MM-SafetyBench) | Black-box — Structured visual carriers |
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| MML | Jailbreak Large Vision-Language Models Through Multi-Modal Linkage | [link](https://aclanthology.org/2025.acl-long.74/) | [link](https://github.com/wangyu-ovo/MML) | Black-box — Structured visual carriers |
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| CS-DJ | Distraction is All You Need for Multimodal Large Language Model Jailbreaking | [link](https://arxiv.org/abs/2502.10794) | [link](https://github.com/TeamPigeonLab/CS-DJ) | Black-box — OOD (attention / distribution manipulation) |
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| SI-Attack | Jailbreaking Multimodal Large Language Models via Shuffle Inconsistency | [link](https://arxiv.org/abs/2501.04931) | [link](https://github.com/zhaoshiji123/SI-Attack) | Black-box — OOD (shuffle / attention inconsistency) |
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| JOOD | Playing the Fool: Jailbreaking LLMs and Multimodal LLMs with Out-of-Distribution Strategy | [link](https://arxiv.org/abs/2503.20823) | [link](https://github.com/naver-ai/JOOD) | Black-box — OOD (OOD strategy) |
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| HIMRD | Heuristic-Induced Multimodal Risk Distribution (HIMRD) Jailbreak Attack | [link](https://arxiv.org/abs/2412.05934) | [link](https://github.com/MaTengSYSU/HIMRD-jailbreak) | Black-box — OOD / risk distribution |
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| HADES | Images are Achilles’ Heel of Alignment: Exploiting Visual Vulnerabilities for Jailbreaking Multimodal Large Language Models | [link](https://arxiv.org/abs/2403.09792) | [link](https://github.com/AoiDragon/HADES) | Black-box — Structured visual carriers |
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| BAP | Jailbreak Vision Language Models via Bi-Modal Adversarial Prompt (BAP) | [link](https://arxiv.org/abs/2406.04031) | [link](https://github.com/NY1024/BAP-Jailbreak-Vision-Language-Models-via-Bi-Modal-Adversarial-Prompt) | White-box — Cross-modal |
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| visual_adv | Visual Adversarial Examples Jailbreak Aligned Large Language Models | [link](https://ojs.aaai.org/index.php/AAAI/article/view/30150) | [link](https://github.com/Unispac/Visual-Adversarial-Examples-Jailbreak-Large-Language-Models) | White-box — Single-modal |
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| VisCRA | VisCRA: A Visual Chain Reasoning Attack for Jailbreaking Multimodal Large Language Models | [link](https://arxiv.org/abs/2505.19684) | [link](https://github.com/DyMessi/VisCRA) | Black-box — Structured visual carriers |
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| UMK | White-box Multimodal Jailbreaks Against Large Vision-Language Models (Universal Master Key, UMK) | [link](https://arxiv.org/abs/2405.17894) | [link](https://github.com/roywang021/UMK) | White-box — Cross-modal |
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| PBI-Attack | Prior-Guided Bimodal Interactive Black-Box Jailbreak Attack for Toxicity Maximization (PBI-Attack) | [link](https://aclanthology.org/2025.emnlp-main.32.pdf) | [link](https://github.com/Rosy0912/PBI-Attack) | Black-box — Query optimization & transfer |
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| ImgJP / DeltaJP | Jailbreaking Attack against Multimodal Large Language Model (imgJP / deltaJP) | [link](https://arxiv.org/abs/2402.02309) | [link](https://github.com/abc03570128/Jailbreaking-Attack-against-Multimodal-Large-Language-Model) | White-box — Single-modal |
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| JPS | JPS: Jailbreak Multimodal Large Language Models with Collaborative Visual Perturbation and Textual Steering | [link](https://arxiv.org/abs/2508.05087) | [link](https://github.com/thu-coai/JPS) | White-box — Cross-modal |
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| Name | Title | Paper | Code | Classification |
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|:----------------------------:|:-----------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------:|
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| FigStep / FigStep-Pro | FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts | [link](https://arxiv.org/abs/2311.05608) | [link](https://github.com/ThuCCSLab/FigStep) | Black-box — Structured visual carriers |
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| QR-Attack (MM-SafetyBench) | MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models | [link](https://arxiv.org/abs/2311.17600) | [link](https://github.com/isXinLiu/MM-SafetyBench) | Black-box — Structured visual carriers |
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| MML | Jailbreak Large Vision-Language Models Through Multi-Modal Linkage | [link](https://aclanthology.org/2025.acl-long.74/) | [link](https://github.com/wangyu-ovo/MML) | Black-box — Structured visual carriers |
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| CS-DJ | Distraction is All You Need for Multimodal Large Language Model Jailbreaking | [link](https://arxiv.org/abs/2502.10794) | [link](https://github.com/TeamPigeonLab/CS-DJ) | Black-box — OOD (attention / distribution manipulation) |
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| SI-Attack | Jailbreaking Multimodal Large Language Models via Shuffle Inconsistency | [link](https://arxiv.org/abs/2501.04931) | [link](https://github.com/zhaoshiji123/SI-Attack) | Black-box — OOD (shuffle / attention inconsistency) |
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| JOOD | Playing the Fool: Jailbreaking LLMs and Multimodal LLMs with Out-of-Distribution Strategy | [link](https://arxiv.org/abs/2503.20823) | [link](https://github.com/naver-ai/JOOD) | Black-box — OOD (OOD strategy) |
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| HIMRD | Heuristic-Induced Multimodal Risk Distribution (HIMRD) Jailbreak Attack | [link](https://arxiv.org/abs/2412.05934) | [link](https://github.com/MaTengSYSU/HIMRD-jailbreak) | Black-box — OOD / risk distribution |
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| HADES | Images are Achilles’ Heel of Alignment: Exploiting Visual Vulnerabilities for Jailbreaking Multimodal Large Language Models | [link](https://arxiv.org/abs/2403.09792) | [link](https://github.com/AoiDragon/HADES) | Black-box — Structured visual carriers |
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| BAP | Jailbreak Vision Language Models via Bi-Modal Adversarial Prompt (BAP) | [link](https://arxiv.org/abs/2406.04031) | [link](https://github.com/NY1024/BAP-Jailbreak-Vision-Language-Models-via-Bi-Modal-Adversarial-Prompt) | White-box — Cross-modal |
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| visual_adv | Visual Adversarial Examples Jailbreak Aligned Large Language Models | [link](https://ojs.aaai.org/index.php/AAAI/article/view/30150) | [link](https://github.com/Unispac/Visual-Adversarial-Examples-Jailbreak-Large-Language-Models) | White-box — Single-modal |
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| VisCRA | VisCRA: A Visual Chain Reasoning Attack for Jailbreaking Multimodal Large Language Models | [link](https://arxiv.org/abs/2505.19684) | [link](https://github.com/DyMessi/VisCRA) | Black-box — Structured visual carriers |
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| UMK | White-box Multimodal Jailbreaks Against Large Vision-Language Models (Universal Master Key, UMK) | [link](https://arxiv.org/abs/2405.17894) | [link](https://github.com/roywang021/UMK) | White-box — Cross-modal |
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| PBI-Attack | Prior-Guided Bimodal Interactive Black-Box Jailbreak Attack for Toxicity Maximization (PBI-Attack) | [link](https://aclanthology.org/2025.emnlp-main.32.pdf) | [link](https://github.com/Rosy0912/PBI-Attack) | Black-box — Query optimization & transfer |
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| ImgJP / DeltaJP | Jailbreaking Attack against Multimodal Large Language Model (imgJP / deltaJP) | [link](https://arxiv.org/abs/2402.02309) | [link](https://github.com/abc03570128/Jailbreaking-Attack-against-Multimodal-Large-Language-Model) | White-box — Single-modal |
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| JPS | JPS: Jailbreak Multimodal Large Language Models with Collaborative Visual Perturbation and Textual Steering | [link](https://arxiv.org/abs/2508.05087) | [link](https://github.com/thu-coai/JPS) | White-box — Cross-modal |
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## 🛡️Integrated Defense Methods
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| Name | Title | Venue | Paper | Code |
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|---|--------------------------------------------------------------------------------------------------------------------|---|---|---|
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| JailGuard | JailGuard: A Universal Detection Framework for Prompt-based Attacks on LLM Systems | TOSEM2025 | [link](https://arxiv.org/abs/2312.10766) | [link](https://github.com/shiningrain/JailGuard) |
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| MLLM-Protector | MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance | EMNLP2024 | [link](https://arxiv.org/abs/2401.02906) | [link](https://github.com/pipilurj/MLLM-protector) |
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| ECSO | Eyes Closed, Safety On: Protecting Multimodal LLMs via Image-to-Text Transformation | ECCV2024 | [link](https://arxiv.org/abs/2403.09572) | [link](https://gyhdog99.github.io/projects/ecso/) |
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| ShieldLM | ShieldLM: Empowering LLMs as Aligned, Customizable and Explainable Safety Detectors | EMNLP2024 | [link](https://arxiv.org/abs/2402.16444) | [link](https://github.com/thu-coai/ShieldLM) |
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| AdaShield | AdaShield: Safeguarding Multimodal Large Language Models from Structure-based Attack via Adaptive Shield Prompting | ECCV2024 | [link](https://arxiv.org/abs/2403.09513) | [link](https://github.com/rain305f/AdaShield) |
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| Uniguard | UNIGUARD: Towards Universal Safety Guardrails for Jailbreak Attacks on Multimodal Large Language Models | ECCV2024 | [link](https://arxiv.org/abs/2411.01703) | [link](https://anonymous.4open.science/r/UniGuard/README.md) |
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| DPS | Defending LVLMs Against Vision Attacks Through Partial-Perception Supervision | ICML2025 | [link](https://arxiv.org/abs/2412.12722) | [link](https://github.com/tools-only/DPS) |
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| CIDER | Cross-modality Information Check for Detecting Jailbreaking in Multimodal Large Language Models | EMNLP2024 | [link](https://arxiv.org/abs/2407.21659) | [link](https://github.com/PandragonXIII/CIDER) |
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| GuardReasoner-VL | GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning | ICML2025 | [link](https://arxiv.org/abs/2505.11049) | [link](https://github.com/yueliu1999/GuardReasoner-VL) |
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| Llama-Guard-4 | Llama Guard 4 | Model Card | [link](https://www.llama.com/docs/model-cards-and-prompt-formats/llama-guard-4/) | [link](https://huggingface.co/meta-llama/Llama-Guard-4-12B) |
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| QGuard | QGuard: Question-based Zero-shot Guard for Multi-modal LLM Safety | arXiv | [link](https://arxiv.org/abs/2506.12299) | [link](https://github.com/taegyeong-lee/QGuard-Question-based-Zero-shot-Guard-for-Multi-modal-LLM-Safety) |
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| LlavaGuard | LlavaGuard: An Open VLM-based Framework for Safeguarding Vision Datasets and Models | ICML2025 | [link](https://arxiv.org/abs/2406.05113) | [link](https://github.com/ml-research/LlavaGuard) |
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| Llama-Guard-3 | Llama Guard 3 | Model Card | [link](https://www.llama.com/docs/model-cards-and-prompt-formats/llama-guard-3/) | [link](https://huggingface.co/meta-llama/Llama-Guard-3-8B) |
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| HiddenDetect | HiddenDetect: Detecting Jailbreak Attacks against Multimodal Large Language Models via Monitoring Hidden States | ACL2025 | [link](https://arxiv.org/abs/2502.14744) | [link](https://github.com/leigest519/HiddenDetect) |
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| CoCA | CoCA: Regaining Safety-awareness of Multimodal Large Language Models with Constitutional Calibration | COLM2024 | [link](https://arxiv.org/abs/2409.11365) | Null |
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| VLGuard | Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models | ICML2024 | [link](https://arxiv.org/abs/2402.02207) | [link](https://github.com/ys-zong/VLGuard) |
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| Name | Title | Venue | Paper | Code |
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|:-----------------:|:--------------------------------------------------------------------------------------------------------------------:|:----------:|:---------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|
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| JailGuard | JailGuard: A Universal Detection Framework for Prompt-based Attacks on LLM Systems | TOSEM2025 | [link](https://arxiv.org/abs/2312.10766) | [link](https://github.com/shiningrain/JailGuard) |
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| MLLM-Protector | MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance | EMNLP2024 | [link](https://arxiv.org/abs/2401.02906) | [link](https://github.com/pipilurj/MLLM-protector) |
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| ECSO | Eyes Closed, Safety On: Protecting Multimodal LLMs via Image-to-Text Transformation | ECCV2024 | [link](https://arxiv.org/abs/2403.09572) | [link](https://gyhdog99.github.io/projects/ecso/) |
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| ShieldLM | ShieldLM: Empowering LLMs as Aligned, Customizable and Explainable Safety Detectors | EMNLP2024 | [link](https://arxiv.org/abs/2402.16444) | [link](https://github.com/thu-coai/ShieldLM) |
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| AdaShield | AdaShield: Safeguarding Multimodal Large Language Models from Structure-based Attack via Adaptive Shield Prompting | ECCV2024 | [link](https://arxiv.org/abs/2403.09513) | [link](https://github.com/rain305f/AdaShield) |
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| Uniguard | UNIGUARD: Towards Universal Safety Guardrails for Jailbreak Attacks on Multimodal Large Language Models | ECCV2024 | [link](https://arxiv.org/abs/2411.01703) | [link](https://anonymous.4open.science/r/UniGuard/README.md) |
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| DPS | Defending LVLMs Against Vision Attacks Through Partial-Perception Supervision | ICML2025 | [link](https://arxiv.org/abs/2412.12722) | [link](https://github.com/tools-only/DPS) |
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| CIDER | Cross-modality Information Check for Detecting Jailbreaking in Multimodal Large Language Models | EMNLP2024 | [link](https://arxiv.org/abs/2407.21659) | [link](https://github.com/PandragonXIII/CIDER) |
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| GuardReasoner-VL | GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning | ICML2025 | [link](https://arxiv.org/abs/2505.11049) | [link](https://github.com/yueliu1999/GuardReasoner-VL) |
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| Llama-Guard-4 | Llama Guard 4 | Model Card | [link](https://www.llama.com/docs/model-cards-and-prompt-formats/llama-guard-4/) | [link](https://huggingface.co/meta-llama/Llama-Guard-4-12B) |
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| QGuard | QGuard: Question-based Zero-shot Guard for Multi-modal LLM Safety | ArXiv | [link](https://arxiv.org/abs/2506.12299) | [link](https://github.com/taegyeong-lee/QGuard-Question-based-Zero-shot-Guard-for-Multi-modal-LLM-Safety) |
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| LlavaGuard | LlavaGuard: An Open VLM-based Framework for Safeguarding Vision Datasets and Models | ICML2025 | [link](https://arxiv.org/abs/2406.05113) | [link](https://github.com/ml-research/LlavaGuard) |
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| Llama-Guard-3 | Llama Guard 3 | Model Card | [link](https://www.llama.com/docs/model-cards-and-prompt-formats/llama-guard-3/) | [link](https://huggingface.co/meta-llama/Llama-Guard-3-8B) |
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| HiddenDetect | HiddenDetect: Detecting Jailbreak Attacks against Multimodal Large Language Models via Monitoring Hidden States | ACL2025 | [link](https://arxiv.org/abs/2502.14744) | [link](https://github.com/leigest519/HiddenDetect) |
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| CoCA | CoCA: Regaining Safety-awareness of Multimodal Large Language Models with Constitutional Calibration | COLM2024 | [link](https://arxiv.org/abs/2409.11365) | - |
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| VLGuard | Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models | ICML2024 | [link](https://arxiv.org/abs/2402.02207) | [link](https://github.com/ys-zong/VLGuard) |
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> More methods are coming soon!!
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