Alternatives and similar repositories for SafeBench

Users that are interested in SafeBench are comparing it to the libraries listed below

• Alibaba-AAIG / Oyster
  The Oyster series is a set of safety models developed in-house by Alibaba-AAIG, devoted to building a responsible AI ecosystem. | Oyster …
  ☆57Updated 2 months ago
• AI45Lab / CodeAttack
  [ACL 2024] CodeAttack: Revealing Safety Generalization Challenges of Large Language Models via Code Completion
  ☆55Updated 2 months ago
• thunxxx / MLLM-Jailbreak-evaluation-MMJ-Bench
  ☆66Updated 8 months ago
• thu-ml / STAIR
  Official codebase for "STAIR: Improving Safety Alignment with Introspective Reasoning"
  ☆87Updated 9 months ago
• MurrayTom / SG-Bench
  SG-Bench: Evaluating LLM Safety Generalization Across Diverse Tasks and Prompt Types
  ☆23Updated last year
• SaFoLab-WISC / JailBreakV_28K
  [COLM 2024] JailBreakV-28K: A comprehensive benchmark designed to evaluate the transferability of LLM jailbreak attacks to MLLMs, and fur…
  ☆82Updated 6 months ago
• sail-sg / I-FSJ
  Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses (NeurIPS 2024)
  ☆65Updated 10 months ago
• akumar2709 / OVERTHINK_public
  ☆42Updated 3 weeks ago
• zihao-ai / unthinking_vulnerability
  To Think or Not to Think: Exploring the Unthinking Vulnerability in Large Reasoning Models
  ☆32Updated 6 months ago
• AI45Lab / ActorAttack
  ☆112Updated 10 months ago
• wonderNefelibata / Awesome-LRM-Safety
  Awesome Large Reasoning Model(LRM) Safety.This repository is used to collect security-related research on large reasoning models such as …
  ☆78Updated this week
• shiningrain / JailGuard
  ☆24Updated 8 months ago
• ys-zong / VLGuard
  [ICML 2024] Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models.
  ☆80Updated 10 months ago
• WangCheng0116 / Awesome-LRMs-Safety
  Official repository for "Safety in Large Reasoning Models: A Survey" - Exploring safety risks, attacks, and defenses for Large Reasoning …
  ☆82Updated 3 months ago
• isXinLiu / MM-SafetyBench
  Accepted by ECCV 2024
  ☆176Updated last year
• salman-lui / x-teaming
  ☆47Updated 6 months ago
• NY1024 / BAP-Jailbreak-Vision-Language-Models-via-Bi-Modal-Adversarial-Prompt
  ☆53Updated last year
• thu-ml / MMTrustEval
  A toolbox for benchmarking trustworthiness of multimodal large language models (MultiTrust, NeurIPS 2024 Track Datasets and Benchmarks)
  ☆170Updated 5 months ago
• AISG-Technology-Team / GCSS-Track-1A-Submission-Guide
  Submission Guide + Discussion Board for AI Singapore Global Challenge for Safe and Secure LLMs (Track 1A).
  ☆16Updated last year
• lancopku / agent-backdoor-attacks
  Code&Data for the paper "Watch Out for Your Agents! Investigating Backdoor Threats to LLM-Based Agents" [NeurIPS 2024]
  ☆102Updated last year
• ydyjya / SafetyHeadAttribution
  ☆58Updated 6 months ago
• HKUST-KnowComp / LLM-Multistep-Jailbreak
  Code for Findings-EMNLP 2023 paper: Multi-step Jailbreaking Privacy Attacks on ChatGPT
  ☆35Updated 2 years ago
• gyhdog99 / ECSO
  ECSO (Make MLLM safe without neither training nor any external models!) (https://arxiv.org/abs/2403.09572)
  ☆34Updated last year
• ChenWu98 / agent-attack
  [ICLR 2025] Dissecting adversarial robustness of multimodal language model agents
  ☆119Updated 9 months ago
• umd-huang-lab / VLM-Poisoning
  Code for Neurips 2024 paper "Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models"
  ☆57Updated 10 months ago
• git-disl / Vaccine
  This is the official code for the paper "Vaccine: Perturbation-aware Alignment for Large Language Models" (NeurIPS2024)
  ☆48Updated last year
• YancyKahn / CoA
  Chain of Attack: a Semantic-Driven Contextual Multi-Turn attacker for LLM
  ☆38Updated 10 months ago
• tmllab / 2025_ICLR_PiF
  ☆37Updated 6 months ago
• UCSC-VLAA / vllm-safety-benchmark
  [ECCV 2024] Official PyTorch Implementation of "How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs"
  ☆84Updated 2 years ago
• sail-sg / closer-look-LLM-unlearning
  [ICLR 2025] A Closer Look at Machine Unlearning for Large Language Models
  ☆41Updated last year