{"data":{"slug":"qiuhuachuan-latent-jailbreak","name":"latent-jailbreak","tagline":"latent-jailbreak","github_url":"https://github.com/qiuhuachuan/latent-jailbreak","owner":"qiuhuachuan","repo":"latent-jailbreak","owner_avatar_url":"https://avatars.githubusercontent.com/u/44393231?v=4","primary_language":"Python","stars":39,"forks":2,"topics":[],"archived":false,"github_pushed_at":"2024-05-21T04:23:32+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/qiuhuachuan-latent-jailbreak","markdown_url":"https://www.graphcanon.com/tools/qiuhuachuan-latent-jailbreak.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/qiuhuachuan-latent-jailbreak","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=qiuhuachuan-latent-jailbreak","description":null,"homepage_url":null,"license":"MIT","open_issues":1,"watchers":1,"ai_summary":null,"readme_excerpt":"# Latent Jailbreak\n\n🎉 [Paper](https://arxiv.org/pdf/2307.08487.pdf)\n\nThis repository contains the code and data for the paper **Latent Jailbreak: A Benchmark for Evaluating Text Safety and Output Robustness of Large Language Models**. The paper explores the topic of _latent jailbreak_ and presents a novel approach to evaluate the text safety and output robustness for large language models.\n\n## Data\n\nThe data used in this paper is included in the `data` directory.\n\n## Templates\n\n\nTemplates for latent jailbreak prompts.\n\n## Generate Model Responses\n\n```bash\ncd src\npython BELLE_7B_2M.py\npython ChatGLM2-6B.py\npython ChatGPT.py --api_key 'your key'\n```\n\n## Fine-Tune Model to Perform Automatic Labeling\n\n```bash\npython finetune.py\n```\n\n## Citation\n\nIf you use the code or data in this repository, please cite the following paper.\n\n```\n@misc{qiu2023latent,\n      title={Latent Jailbreak: A Benchmark for Evaluating Text Safety and Output Robustness of Large Language Models},\n      author={Huachuan Qiu and Shuai Zhang and Anqi Li and Hongliang He and Zhenzhong Lan},\n      year={2023},\n      eprint={2307.08487},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL}\n}\n```","github_created_at":"2023-07-17T14:53:20+00:00","created_at":"2026-07-11T23:40:00.073253+00:00","updated_at":"2026-07-11T23:40:03.20916+00:00","categories":[{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"python","name":"python"}],"trust":{"provenance":{"is_fork":false,"github_id":667460790,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T23:40:01.057Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":781,"last_release_at":null},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T23:40:01.523Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-11T23:40:00.807Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-07-11T23:40:00.807Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-07-11T23:40:00.807Z"}}}}