HackThisAI
plexiglass
| HackThisAI | plexiglass | |
|---|---|---|
| 6 | 3 | |
| 82 | 98 | |
| - | - | |
| 6.8 | 9.0 | |
| about 2 months ago | 4 months ago | |
| Jupyter Notebook | Python | |
| GNU General Public License v3.0 only | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
HackThisAI
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Is it possible to combine Data Science with hacking / IT-security?
1) Use data science for infosec. Plenty of infused products are data science under the hood and most big companies have product data scientists. 2) Bring security to data science. This is a younger field, but the topic of my side project: https://github.com/JosephTLucas/HackThisAI
- [P] HackThisAI: Adversarial Machine Learning CTF Challenges
- CTF challenge: HackThisAI
- Adversarial Machine Learning CTF challenges
- CTF Challenges for Adversarial Machine Learning
- Show HN: CTF Challenges for Adversarial Machine Learning
plexiglass
- Looking for contributors to an AI security project
- [P] Plexiglass: a toolbox for testing against adversarial attacks in DNNs and LLMs.
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Plexiglass: A toolbox for testing against adversarial attacks in DNNs and LLMs
Hi everyone, my name is Enoch and I am a researcher studying deep generative models.
I've started this project called Plexiglass a while back, which started off as a torch toolbox for adversarial research in DCNNs. I am now rebooting it as a toolbox for testing against adversarial attacks in both DNNs and LLMs.
Idea is to test your DCNNs against adversarial attacks such as fast gradient sign method and toxic prompts in LLMs.
I would very much appreciate contributions, I need more devs as I'm too busy to do this all by myself .
Repo is here: https://github.com/kortex-labs/plexiglass
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