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Source channel @githubtrending · Post #15068 · Aug 17

#python#artificial_intelligence#cybersecurity#generative_ai#llm#pentesting Cybersecurity AI (CAI) is an open-source, lightweight framework that helps you build AI agents to find and fix security vulnerabilities efficiently. It supports many AI models and tools, works on multiple operating systems, and allows human control during tasks. CAI automates complex security testing steps like scanning, exploiting, and validating bugs, making bug bounty hunting easier and faster. It also logs detailed traces for better analysis and supports teamwork among AI agents. Using CAI can boost your cybersecurity skills, save time, and improve your ability to protect systems from attacks by combining AI power with your expertise. https://github.com/aliasrobotics/cai

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djangoproject

@djangoproject · Post #274 · 03/18/2017, 01:48 AM

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https://github.com/riga/tfdeploy Google's TensorFlow framework is taking off big-time now that it's at a full 1.0 release. One common question about it: How can I make use of the models I train in TensorFlow without using TensorFlow itself? #Tfdeploy is a partial answer to that question. It exports a trained TensorFlow model to "a simple #NumPy-based callable," meaning the model can be used in Python with Tfdeploy and the the NumPy math-and-stats library as the only dependencies. Most of the operations you can perform in TensorFlow can also be performed in Tfdeploy, and you can extend the behaviors of the library by way of standard Python metaphors (such as overloading a class). Now the bad news: Tfdeploy doesn't support GPU acceleration, if only because NumPy doesn't do that. Tfdeploy's creator suggests using the gNumPy project as a possible replacement. #Machine_learning

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