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...

DBShield

DBShield Protects your data by inspecting incoming queries from your application server and rejecting abnormal ones. How it works? For example, this is how web server normally interacts with database server: By adding DBShield in front of database server we can protect it against abnormal queries...

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...

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...

WindowsMemPageDelta

Windows Executable Memory Page Delta Reporter A Windows Service to performantly produce telemetry on new or modified Windows memory pages that are now executable every 30 seconds. Released as open source by NCC Group Plc - http://www.nccgroup.com/ Developed by Ollie Whitehouse, ollie dot whitehou...

WhacAMole

WhacAMole WhacAMole is a program that analyzes processes in memory in an integral way, detecting and alerting of anomalies related to malware and presenting and saving in files all the relevant information for verification, correlation or analysis, as well as dumping memory regions, processes and...

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,"...

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...

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|...

Mr.SIP

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

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...

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...

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...

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...

SyntheticSun

SyntheticSun SyntheticSun is a defense-in-depth security automation and monitoring framework which utilizes threat intelligence, machine learning, managed AWS security services and, serverless technologies to continuously prevent, detect and respond to threats. You sleep in fragmented glass With...

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...

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...

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...

home_SOC_suite

Home SOC Suite — Night's Watch A personal Security Operations Center SOC built from scratch during an Anwendungsentwicklung retraining program. This suite monitors a Windows endpoint for network anomalies, resource spikes, process execution, registry changes, Security Event Log activity, schedule...

ai-security-battle

🤖 AI Security Battle System Red Team vs Blue Team: Adversarial ML Combat Simulation A comprehensive adversarial machine learning security simulation where Red Team attackers battle against Blue Team defenders in a 30-minute AI/ML security warfare scenario. 🎯 Project Overview This system simulates...