sentrygrid

SentryGrid ML-driven threat detection and continuous monitoring platform built for federal zero-trust architectures. OSCAL-native, FedRAMP Moderate-aligned, hash-chained audit, three-model anomaly ensemble. Quick start make setup install bun + python deps make dev-up bring up the local stack via...

ALYCON-Threat-Landscape

ALYCON: Advanced Threat Landscape Analysis Multi-Domain Threat Detection using Information-Theoretic Phase Space Analysis Overview ALYCON phase space visualization showing multi-domain threat detection and anomaly classification. Framework: Training-free, universal anomaly detection using Shannon...

deep-loglizer

Deep-loglizer Deep-loglizer is a deep learning-based log analysis toolkit for automated anomaly detection. If you use deep-loglizer in your research for publication, please kindly cite the following paper: Zhuangbin Chen, Jinyang Liu, Wenwei Gu, Yuxin Su, and Michael R. Lyu. Experience Report: De...

DeepTraffic

Deep Learning models for network traffic classification For more information please read our papers. 🎓Wei Wang's Google Scholar Homepage Wei Wang, Xuewen Zeng, Xiaozhou Ye, Yiqiang Sheng and Ming Zhu,"Malware Traffic Classification Using Convolutional Neural Networks for Representation Learning,"...

SecurityClaw

SecurityClaw — Autonomous SOC Agentic Framework A modular, skill-based autonomous Security Operations Center SOC agent that monitors OpenSearch/Elasticsearch data, builds RAG-based behavioral memory, and validates real-time anomalies using LLMs. Features Skill Modularity — Capabilities as isolate...

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...

pyod

.. image:: https://raw.githubusercontent.com/yzhao062/pyod/master/brand/pyod-icon.svg :target: https://pyod.dev :alt: PyOD Ecosystem :width: 84px Python Outlier Detection PyOD 3 PyOD 3: Agentic Anomaly Detection At Scale |badgewebsite| |badgepypi| |badgeanaconda| |badgedocs| |badgestars|...

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...

RTA

Red Team Arsenal Red Team Arsenal is a inhouse framework created by flipkart security team which monitors the external attack surface of the company's online assets and provide an holistic security view of any security anomalies. It's a closely linked collection of various security engines and...

logdata-anomaly-miner

logdata-anomaly-miner This tool parses log data and allows to define analysis pipelines for anomaly detection. It was designed to run the analysis with limited resources and lowest possible permissions to make it suitable for production server use. Requirements In order to install...

PortEx

PortEx Welcome to PortEx PortEx is a Java library for static malware analysis of Portable Executable files. Its focus is on PE malformation robustness, and anomaly detection. PortEx is written in Java and Scala, and targeted at Java applications. Features Reading header information from: MSDOS...

PortDog

PortDog PortDog is a network anomaly detector aimed to detect port scanning techniques. It is entirely written in python and has easy-to-use interface. It was tested on Ubuntu 15. Please note that, it is not working on Windows OS due to suffering from capturing RAW packets.I am working on to writ...

Mr.SIP

SIP Security, Attack and Audit Framework Mr.SIP is...

In0ri

In0ri is an automated, AI-powered website defacement detection system. Introduction In0ri acts as an intelligent watchdog for your web applications. Instead of relying on traditional source code monitoring, it simulates real-user behavior by periodically taking screenshots of your target websites...

burp-ResponseClusterer

ResponseClusterer This extension clusters similar responses together, and shows a summary with one request/response per cluster. This allows the tester to get an overview of the tested website's responses from all Burp Suite tools. This is powerful, because it adds an additional vulnerability...

Insider-Threat

Insider Threat Graph Models R5.2 & R6.2 This repository contains data preparation, feature extraction, and graph-based models GCN-NN, GCN-BiLSTM, and GCN-BiLSTM+Attention for implicit+explicit signals for insider-threat detection using the CMU CERT Insider Threat Test Dataset R5.2, R6.2. Reposito...

hunting-rules

Suricata Hunting Rules a.k.a. TGI HUNT Suricata rules to assist network anomaly detection. These rules are not performance focused and may perform poorly on high throughput networks. Requires Suricata version 7.0.3 or above. Feedback and suggestions are welcomed here. email blog...

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...

Detection-struts-cve-2017-5638-detector

🚨 Real-Time Anomaly Detection for Apache Struts CVE-2017-5638 Zero-Day Exploit Detection Based on Streaming Analytics & Probabilistic Data Structures 📌 Project Description This project is a real-time anomaly detection system designed to detect RCE Remote Code Execution exploits on Apache Struts...

msnm-sensor

Description MSNM-S Multivariate Statistical Network Monitoring-Sensor shows the practical suitability of the approaches found in PCA-MSNM and in Hierarchical PCA-MSNM works. The first one present the MSNM approach and new multivariate statistical methodology for network anomaly detection while th...