https://github.com/dmis-lab/asguard
https://github.com/dmis-lab/asguard
Last synced: 19 days ago
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- Host: GitHub
- URL: https://github.com/dmis-lab/asguard
- Owner: dmis-lab
- Created: 2025-09-29T13:27:38.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-09-30T09:20:27.000Z (10 months ago)
- Last Synced: 2025-10-29T02:57:16.815Z (9 months ago)
- Language: Python
- Size: 5.88 MB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ASGuard: Activation-Scaling Guard to Mitigate Targeted Jailbreaking Attack
## Overview
Large language models (LLMs) often display brittle refusal behaviors that can be bypassed by simple linguistic variations, such as tense jailbreaking. ASGuard (Activation-Scaling Guard) introduces a mechanistically-informed framework to address this vulnerability with precision and interpretability.
(1) Circuit Analysis: Identifies attention heads causally linked to tense-based jailbreaking.
(2) Activation Scaling: Learns channel-wise scaling vectors to recalibrate vulnerable heads.
(3) Preventative Fine-Tuning: Reinforces robust refusal mechanisms while preserving model utility.
Evaluated across multiple LLMs, ASGuard achieves a Pareto-optimal tradeoff between safety and general capabilities, effectively reducing attack success rates while minimizing over-refusal. This work highlights how mechanistic insights can be translated into practical, efficient, and targeted safety interventions, advancing reliable and interpretable AI alignment.
## Installation
To ensure compatibiliity with other libraries, we recommend using the folliwng versions. You can adjust it based on your environments:
- Python >= 3.10.14
- CUDA 12.2
Follow the order of installation.
1. Clone the repository:
```bash
git clone https://github.com/dmis-lab/ASGuard.git
cd ASGuard
```
2. Install dependencies:
```bash
pip install -r requirements.txt
```
## Implementation
### Step 1: Circuit Analysis
⚠️ Currently we do not support circuit construction. Please wait for an update.
### Step 2: Activation Scaling
```bash
bash run_scaling.sh
```
### Step 3: Preventative Fine-Tuning
```bash
bash run_prevent.sh
```
## Evaluation
⚠️ Currently we do not support evaluation. Please wait for an update.
### Contact
For any questions or issues, feel free to reach out to [522yein (at) korea.ac.kr].