reds-lab / BEEARLinks
This is the official Gtihub repo for our paper: "BEEAR: Embedding-based Adversarial Removal of Safety Backdoors in Instruction-tuned Language Models".
☆18Updated last year
Alternatives and similar repositories for BEEAR
Users that are interested in BEEAR are comparing it to the libraries listed below
Sorting:
- Benchmark evaluation code for "SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal" (ICLR 2025)☆68Updated 8 months ago
- The official implementation of our pre-print paper "Automatic and Universal Prompt Injection Attacks against Large Language Models".☆61Updated last year
- Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses (NeurIPS 2024)☆65Updated 10 months ago
- Code&Data for the paper "Watch Out for Your Agents! Investigating Backdoor Threats to LLM-Based Agents" [NeurIPS 2024]☆98Updated last year
- An unofficial implementation of AutoDAN attack on LLMs (arXiv:2310.15140)☆44Updated last year
- [NeurIPS 2024] Accelerating Greedy Coordinate Gradient and General Prompt Optimization via Probe Sampling☆31Updated last year
- Official implementation of AdvPrompter https//arxiv.org/abs/2404.16873☆170Updated last year
- ☆46Updated last year
- Official implementation of ICLR'24 paper, "Curiosity-driven Red Teaming for Large Language Models" (https://openreview.net/pdf?id=4KqkizX…☆84Updated last year
- Code for paper "Universal Jailbreak Backdoors from Poisoned Human Feedback"☆62Updated last year
- [ICML 2024] Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications☆86Updated 7 months ago
- Fingerprint large language models☆43Updated last year
- Official Repository for The Paper: Safety Alignment Should Be Made More Than Just a Few Tokens Deep☆163Updated 6 months ago
- ☆36Updated last year
- This is the official code for the paper "Safety Tax: Safety Alignment Makes Your Large Reasoning Models Less Reasonable".☆25Updated 8 months ago
- Code repo of our paper Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis (https://arxiv.org/abs/2406.10794…☆22Updated last year
- ICLR2024 Paper. Showing properties of safety tuning and exaggerated safety.☆89Updated last year
- This is the starter kit for the Trojan Detection Challenge 2023 (LLM Edition), a NeurIPS 2023 competition.☆89Updated last year
- [ICML 2024] COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability☆169Updated 11 months ago
- [ACL 2024] CodeAttack: Revealing Safety Generalization Challenges of Large Language Models via Code Completion☆54Updated last month
- Official repository for "Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks"☆59Updated last year
- This repo is for the safety topic, including attacks, defenses and studies related to reasoning and RL☆52Updated 2 months ago
- AmpleGCG: Learning a Universal and Transferable Generator of Adversarial Attacks on Both Open and Closed LLM☆75Updated last year
- ☆30Updated 8 months ago
- Fine-tuning base models to build robust task-specific models☆34Updated last year
- ☆24Updated 2 months ago
- [CIKM 2024] Trojan Activation Attack: Attack Large Language Models using Activation Steering for Safety-Alignment.☆28Updated last year
- ☆111Updated 9 months ago
- This is the official code for the paper "Lazy Safety Alignment for Large Language Models against Harmful Fine-tuning" (NeurIPS2024)☆24Updated last year
- ☆23Updated 10 months ago