Open Source Mac Security Software

Save time by asking Buster to solve captchas for you. Buster is a Firefox extension which helps you to solve difficult captchas by completing reCAPTCHA audio challenges using speech recognition. Challenges are solved by clicking on the extension button at the bottom of the reCAPTCHA widget. It is not guaranteed that challenges are always solved, the limitations of the technology need to be considered. The continued development of Buster is made possible thanks to the support of awesome backers. If you'd like to join them, please consider contributing with Patreon, PayPal or Bitcoin. The success rate of the extension can be improved by simulating user interactions with the help of a client app. Follow the instructions from the extension's options to download and install the client app on Windows, Linux and macOS, or get the app from this repository.

Fully automated decryption/decoding/cracking tool using natural language processing & artificial intelligence, along with some common sense. You don't know, you just know it's possibly encrypted. Ciphey will figure it out for you. Ciphey can solve most things in 3 seconds or less. Ciphey aims to be a tool to automate a lot of decryptions & decodings such as multiple base encodings, classical ciphers, hashes or more advanced cryptography. If you don't know much about cryptography, or you want to quickly check the ciphertext before working on it yourself, Ciphey is for you. The technical part. Ciphey uses a custom-built artificial intelligence module (AuSearch) with a Cipher Detection Interface to approximate what something is encrypted with. And then a custom-built, customizable natural language processing Language Checker Interface, which can detect when the given text becomes plaintext.

garak checks if an LLM can be made to fail in a way we don't want. garak probes for hallucination, data leakage, prompt injection, misinformation, toxicity generation, jailbreaks, and many other weaknesses. garak's a free tool, we love developing it and are always interested in adding functionality to support applications. garak is a command-line tool, it's developed in Linux and OSX. Just grab it from PyPI and you should be good to go. The standard pip version of garak is updated periodically. garak has its own dependencies, you can to install garak in its own Conda environment. garak needs to know what model to scan, and by default, it'll try all the probes it knows on that model, using the vulnerability detectors recommended by each probe. For each probe loaded, garak will print a progress bar as it generates. Once the generation is complete, a row evaluating the probe's results on each detector is given.

The claude-code-security-review repository implements a GitHub Action that uses Claude (via the Anthropic API) to perform semantic security audits of code changes in pull requests. Rather than relying purely on pattern matching or static analysis, this action feeds diffs and surrounding context to Claude to reason about potential vulnerabilities (e.g. injection, misconfigurations, secrets exposure, etc). When a PR is opened, the action analyzes only the changed files (diff-aware scanning), generates findings (with explanations, severity, and remediation suggestions), filters false positives using custom prompt logic, and posts comments directly on the PR. It supports configuration inputs (which files/directories to skip, model timeout, whether to comment on the PR, etc). The tool is language-agnostic (it doesn’t need language-specific parsers), uses contextual understanding rather than simplistic rules, and aims to reduce noise with smarter filtering.

ANts P2P realizes a third generation P2P net. It protects your privacy while you are connected and makes you not trackable, hiding your identity (ip) and crypting everything you are sending/receiving from others.

The idea is to enhance and develop the national border crossing process by the integration of automated vehicle recognition while crossing country borders. i'm going to use Automatic number plate recognition (ANPR): a system that recognizes the numbers of the vehicle plates by using OCR (optical character recognition) technology and Infrared cameras. This is going to be achieved by taking the license plate image from the camera and processing it using the software I’m going to develop together with an open source OCR system. The output is going to be a text version of the plate number. Then it is going to retrieve that number from a database and get the information of the vehicle owner. Note: Please note that you need emgucv installed. you also need to move the project files to: C:\Emgu\emgucv-windows-x86XXX\Emgu.CV.Example\ Please note: that the project was created using visual studio 2003, on windows xp. and it might not run fluently on newer versions. please try to update it.

This project provides a java implementation of the Captcha project ( see http://www.captcha.net ). A CAPTCHA is a program that can generate and grade tests that: -Most humans can pass. -Current computer programs can't pass.

An extremely versatile neural net. Hopefully.

A.I. security app. Development ceased.

Just carved a bunch of bytes and have no idea what they could be? Maybe ANNFiD can help. ANNFiD uses neural network to identify byte patterns. It can be trained and has a GUI to help in the process. The tool is still on a very early stage, but could improve exponentially with the help of the developer community

It moves by itself inside networks like virus infection & plagues, it is being written to solve computer virus problem drastically and responsibly. It is legal, free and open for public domain to improve W3 ICT Security.

Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras. Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams. Amid the ongoing COVID-19 pandemic, there are no efficient face mask detection applications which are now in high demand for transportation means, densely populated areas, residential districts, large-scale manufacturers and other enterprises to ensure safety. The absence of large datasets of ‘with_mask’ images has made this task cumbersome and challenging. Our face mask detector doesn't use any morphed masked images dataset and the model is accurate. Owing to the use of MobileNetV2 architecture, it is computationally efficient, thus making it easier to deploy the model to embedded systems (Raspberry Pi, Google Coral, etc.).

InSecT - Invincible Security Technology - an intelligent firewall and intrusion detection system

Security is a subject of major concern in mobile agents. This project provides a security framework that allows the protection of mobile agents from third parties. A self-protected approach, where the agents themselves manage the process, is used.

Java implementation of Sudoku. Visually attractive, interactive version with intelligent and brute force solving strategies.

K is a C++ library featuring Genetic Programming, cryptography, 64 bits arithmetic, cross-platform macros and unicode conversion routines. It compiles on NewtonOS, Mac < X, Unix and Windows and it makes little use of C++ templates.

The all-built-in-one, automatic, ready-to-go out-of-box, easy-to-use state-of-the-art, and really awesome NASH OS! Over 25,000+ flexible features and controls and all scalable!! The most powerful solution ever built to instantly deliver new heights of online ecommerce enterprise to you.

PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as outlier detection or anomaly detection. PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural network-based models, e.g., AutoEncoders, which are implemented in both PyTorch and Tensorflow. PyOD contains multiple models that also exist in scikit-learn. It is possible to train and predict with a large number of detection models in PyOD by leveraging SUOD framework. A benchmark is supplied for select algorithms to provide an overview of the implemented models. In total, 17 benchmark datasets are used for comparison, which can be downloaded at ODDS.

Computer chess engine written using Qt4, which works under Knights, Jose, Arena and other chess board GUI games. Uses bitboard game representation and alpha beta brute-force search to analyse chess positions.

This software uses a genetic algorithm to "evolve" reactor designs for Schema's space-simulation game, Star-Made (http://star-made.org/). One of the more unique aspects of the game is that ship power management is not as simple as filling a cube with power generation blocks. This mechanism leads to difficulties in getting maximal power generation out of such reactors. This program rectifies this issue by using a self-organizing variant of brute force search. Much of the search space is pruned early on by a user-selectable fitness function. Within a few epochs, reactor output quickly converges to several sub-optimal, yet high-output reactors. Given enough time, the idea is that the optimal reactor configuration will be yielded.

The Secure Mobile Agents (SeMoA) platform constitutes a secure runtime environment for Java-based mobile software agents.

The purpose of SNX is to have a modular series of components that report back to a central repository and 'AI' for pattern recognition and anomoly detection. This is to help with IDS systems, and to move to the next generation of security.

A packet dissector driven by machine learning algorithms. You train it to recognize specific types of packets by showing it examples and counterexamples of some packet type, and it will figure out which bits in the packet define it as the type you seek.

TACS (Trust Ant Colony System) is a Trust model for P2P, Ad-hoc and Wireless Sensor networks (also valid for multi-agent systems) based on the bio-inspired algorithm ACS (Ant Colony System).

TURing human IDentification, a textual highly accessible alternative to image CAPTCHAs involving the usage of simple phrases and based on the language recognition features of the user, supposedly human.