An easy-to-use Python framework to generate adversarial jailbreak prompts.
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Updated
Sep 1, 2026 - Python
An easy-to-use Python framework to generate adversarial jailbreak prompts.
Official repository for the paper "ALERT: A Comprehensive Benchmark for Assessing Large Language Models’ Safety through Red Teaming"
[ICLR 2025] Official implementation for "SafeWatch: An Efficient Safety-Policy Following Video Guardrail Model with Transparent Explanations"
Restore safety in fine-tuned language models through task arithmetic
SEALGuard: Safeguarding the Multilingual Conversations in Southeast Asian Languages for LLM Software Systems
LiveSecBench,面向中文场景的大模型安全评测基准。框架结合动态题库、模型对战与客观评分流程,可在伦理、合法性、事实性、隐私、对抗鲁棒与推理安全等核心维度持续追踪模型表现。
Policy-conformance harness for money-touching AI agents — catches over-promises against refund policy, with mechanically verified evidence (Python-derived labels, span-verified judge citations, frozen agent under test).
Red-team framework for discovering alignment failures in frontier language models.
Quantsafe Certifier for testing whether quantized models are prone to be jailbroken and generate unsafe outputs.
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