K2-CLI

Khao2 ██╗ ██╗ ██████╗ ██║ ██╔╝ ╚════██╗ █████╔╝ █████╔╝ ██╔═██╗ ██╔═══╝ ██║ ██╗ ███████╗ ╚═╝ ╚═╝ ╚══════╝ Every single bit. Easy to use, informative and comprehensive steganalysis suite. This is a CLI tool for my SaaS sidehustle khao2.com for steganalysis. FAQs But what really is Khao2/K2? K2 is ...

Pegasus-Malware-Scan

pegasus-malware-scan Description Pegasus Malware Scan is a comprehensive cybersecurity solution designed for advanced threat detection and malware analysis. Built with Python, this powerful tool employs multi-layered detection techniques to identify and neutralize a wide range of malicious...

pulsar

PULSAR Protocol Learning, Simulation and Stateful Fuzzer Pulsar is a network fuzzer with automatic protocol learning and simulation capabilites. The tool allows to model a protocol through machine learning techniques, such as clustering, and Markov models. These models can be used to simulate...

SharpML

SharpML SharpML is a proof of concept file share data mining tool using Machine Learning in Python and C. The tool is discussed in more detail on our blog here, but is summarised below also: SharpML is C and Python based tool that performs a number of operations with a view to mining file shares,...

guardd

Guardd Behavioral anomaly detection for Linux, powered by eBPF and machine learning. Guardd learns how a Linux host normally behaves and flags activity that differs from that baseline. Kernel sensors collect process executions and outbound TCP connection attempts; an Isolation Forest scores the...

batea

Batea A batea is a large shallow pan of wood or iron traditionally used by gold prospectors for washing sand and gravel to recover gold nuggets. Batea is a context-driven network device ranking framework based on the anomaly detection family of machine learning algorithms. The goal of Batea is to...

hexora

hexora Hexora is a static analysis tool designed to detect malicious and harmful patterns in Python code. It combines a rule-based static analysis engine with a machine-learned model that scores entire source files to classify them as malicious or benign. It can be used to: Audit project...

columbo

Columbo Columbo is a computer forensic analysis tool used to simplify and identify specific patterns in compromised datasets. It breaks down data to small sections and uses pattern recognition and machine learning models to identify adversaries behaviour and their possible locations in compromise...

anomaly-flow

Anomaly-Flow Framework for implementing Intrusion Detection Systems NIDS aimed at identifying anomalies in network flows using Machine Learning models. Reference paper: Anomaly-Flow: A Multi-domain Federated Generative Adversarial Network for Distributed Denial-of-Service Detection Create the...

network-threats-taxonomy

Network Threats And Tools Taxonomy Machine Learning based Intrusion Detection Systems are difficult to evaluate due to a shortage of datasets representing accurately network traffic and their associated threats. In this project we attempt at solving this problem by presenting two taxonomies "A...

deep-pwning

Deep-pwning is a lightweight framework for experimenting with machine learning models with the goal of evaluating their robustness against a motivated adversary. Note that deep-pwning in its current state is no where close to maturity or completion. It is meant to be experimented with, expanded...

machine_learning_security

Machine Learning and Security Source codes about machine learning and security. Line up. Cyber security and Machine Learning course The elementary training course of Machine learning for security engineer. Vulnerabilities of Machine Learning Summary of Machine Learning vulnerability. Analytics...

network-attack-detection

Network Attack Detection using Machine Learning Description This project leverages machine learning techniques to classify network attacks such as Port Scanning, Denial of Service DoS, and malware. The input data is in the Netflow V9 format, which is a standard format used by Cisco. The...

OMLASP

OMLASP | | | | | | || | | || | | | | | | | | OMLASP - Open Machine Learning Application Security Project is intended to become a standard for auditing Machine Learning algorithms. It will not only focus on the security of the algorithms but also on their biases. Typically, when applications that...

secretflow

简体中文｜English SecretFlow is a unified framework for privacy-preserving data intelligence and machine learning. To achieve this goal, it provides: An abstract device layer consists of plain devices and secret devices which encapsulate various cryptographic protocols. A device flow layer modeling...

twebit

Bitcoin analysis with machine learning How it works? 1- Get tweets from twitter 2- Filter tweets 3- Tweet classification with naive bayes algorithm Positive,negative and neut Installation git clone https://github.com/omergunal/twebit cd twebit pip3 install -r requirements.txt Update your api keys...

DroidDetective

🕵️ A machine learning malware analysis framework for Android apps. ☢️ DroidDetective is a Python tool for analysing Android applications APKs for potential malware related behaviour and configurations. When provided with a path to an application APK file Droid Detective will make a prediction using...

Apkx-Hunter

APKX-Hunter v3.0.0 -- Debian Package APKX-Hunter at Black Hat Arsenal Europe 2026 View APKX-Hunter on Black Hat Europe Arsenal APKX-Hunter is an open-source Android Static Analysis Framework written entirely in C , purpose-built for Android security assessments, reverse engineering, malware...

pcfg_cracker

PCFG = Probabilistic Context Free Grammar PCFG = Pretty Cool Fuzzy Guesser In short: A collection of tools to perform research into how humans generate passwords. These can be used to crack password hashes, but also create synthetic passwords honeywords, or help develop better password strength...

SecML

SecML: A library for Secure and Explainable Machine Learning SecML is an open-source Python library for the security evaluation of Machine Learning ML algorithms. It comes with a set of powerful features: Wide range of supported ML algorithms. All supervised learning algorithms supported by...