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latent-jailbreak

qiuhuachuan/latent-jailbreak

Repository for evaluating text safety and output robustness of large language models

GraphCanon updated 3w · GitHub synced 3w

39 stars2 forksLast push 2y Python MIT

Decision brief

Evaluation & Observability tool for assessing latent jailbreak phenomena in large language models

Good fit when

  • When conducting detailed safety assessments of text generation from LLMs like BELLE, ChatGLM2, and ChatGPT
  • For research on improving automatic labeling through model fine-tuning to enhance output robustness

Avoid when

  • If quick performance testing without in-depth safety analysis is the priority
  • When working exclusively with smaller or less complex models that do not exhibit latent jailbreak behavior

Observed Jul 16, 2026 · Source: enrich:decision_facts

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Maintenance and security

Full trust report
Maintenance
Dormant (805d since push)
As of 3w
Provenance
Not a fork · Personal account
As of 3w
Security (OSV)
No lockfile
As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install latent-jailbreak
PyPI

Similar tools

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

Provides code and data to assess the latent jailbreak phenomenon in large language models, enabling researchers to measure model safety and robustness.

Capability facts

Languages
python

Source: github.language · Aug 5, 2026

Categories

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Aug 5, 2026)

python BELLE_7B_2M.py
Source link
Works with ChatGPTChatGPT

Source: README excerpt (regex_v1, Aug 5, 2026)

python ChatGPT.py --api_key 'your key'
Source link

Tags

README

Latent Jailbreak

🎉 Paper

This 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.

Data

The data used in this paper is included in the data directory.

Templates

Templates for latent jailbreak prompts.

Generate Model Responses

cd src
python BELLE_7B_2M.py
python ChatGLM2-6B.py
python ChatGPT.py --api_key 'your key'

Fine-Tune Model to Perform Automatic Labeling

python finetune.py

Citation

If you use the code or data in this repository, please cite the following paper.

@misc{qiu2023latent,
      title={Latent Jailbreak: A Benchmark for Evaluating Text Safety and Output Robustness of Large Language Models},
      author={Huachuan Qiu and Shuai Zhang and Anqi Li and Hongliang He and Zhenzhong Lan},
      year={2023},
      eprint={2307.08487},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

For agents

This page has a .md twin and JSON over the API.

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