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EIA: ENVIRONMENTAL INJECTION ATTACK ON GENERALIST WEB AGENTS FOR PRIVACY LEAKAGE

This is the official repo of EIA (https://arxiv.org/abs/2409.11295). If you find it helpful, please kindly 🌟star🌟 it and cite our paper 📜.

EIA_overview

EIA is a form of indirect prompt injection, but specifically designed to manipulate the environment where state-changing actions occur, with a particular focus on exploiting the web environment to target generalist web agents.

Specifically, it injects web elements along with malicious (yet seemingly benign, see figure) instructions into the HTML of the benign website. The injected elements and the instructions are both set to be invisible on the website. This manipulation misleads the web agent into entering private information into the injected elements, thus causing the leakage of the user’s private data.

Overall, EIA achieves up to 70% ASR to steal user specific PII and 16% ASR to leak the full user request. We also demonstrate that EIA can not be detected by traditional web malware detection tool, VirusTotal, and won't affect the agent's next step towards completing the user tasks (ASR_pt). Additionally, an extra defensive system prompt can not mitigate the risks of EIA.

Environmental Setup

Our experimental environment mainly follows the setup of SeeAct. Specifically, we utilized the version of commit 472be0434c54896e2ee0a009d71169a4884da677 which you can assess at here, and upgrade the version of openai to 1.33.0.

Dataset

In our work, we deditecately select tasks from Mind2Web and manually adapt the corresponding realistic website from the provided raw dump file (such as populating the necessary information). After filtering out instances with low quality, we ultimately finalize a set of 177 action steps containing PII and their corresponding webpages.

Download

You can download the webpages with injection directly via the Globus as well. For more information and overview of Globus , please refer to here and here.

You can access the data.zip folder under the link below:

Data Download: https://app.globus.org/file-manager?origin_id=6e0b9952-da25-4b74-a4f9-7450f0bb96b9&origin_path=%2F

After download the data.zip, unzip the file and place it under the repo folder. The folder should look like:

data
├── webpages_filtered
├──── <annotation_id>
├────── <action_id>
├── target_element_HTML.json
├── all_instances.jsonl

where the webpages_filtered folder contains the webpages for web agent to operate. all_instances.jsonl contains the overview of the tasks encompassing the user private information. target_element_HTML.json contains the html content of the target element for each instances. It is used to help us locate the $P_0$ position (reference point) of the target element and further inject the malicious elements into different positions according to the reference point.

EIA

The injection folder contains code for injecting various EIA attacks into benign webpages. As detailed in our paper, this includes different types of injections targeting either the action grounding stage or the action generation stage, each serving different purposes.

To perform the injection, simply run the following command:

./run_injection.sh

Website Deployment

To setup the website and make them accessible by SeeAct via HTTP connection, run the code:

cd web/
uvicorn main:app --reload --port 8000

where you can customize your own port number.

You can test if the connection is established by running:

python web_request_test.py

which will print out the status code. 200 means you setup successfully.

Run SeeAct over the webpage

We cover all the experiments we have in the SeeAct/EIA_run.sh with comments. You can also read the NAME.md file to better know how the arguments map to the setting in our paper.

Evaluation results over three LMMs.

We also provide the evaluation results from the same link above with the name eval_results.zip.

Note

to replicate the results within the eval_results_w_defensive_system_prompt folder, please uncomment the lines here.

Evaluation

Please refer to eval_run.sh to get the ASR, ASR_o and ASR_pt results.

Citation

If you find the paper and any resources here helpful, pls kindly cite our paper:

@article{liao2024eia,
  title={EIA: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage},
  author={Liao, Zeyi and Mo, Lingbo and Xu, Chejian and Kang, Mintong and Zhang, Jiawei and Xiao, Chaowei and Tian, Yuan and Li, Bo and Sun, Huan},
  journal={arXiv preprint arXiv:2409.11295},
  year={2024}
}