dfrws2005-challenge

evild3ad/memprocfs-analyzer555

Memory analyzer

Automated tool for forensic analysis of Windows memory dumps

ftramer/steal-ml344

Model extractor

A tool for extracting machine learning models from cloud-based services using prediction APIs

securityjoes/forensicminer149

Evidence collector

Automates evidence collection and analysis from Windows machines using PowerShell.

teamdfir/sift494

Forensics setup

A suite of tools and images for building and managing digital forensics environments on AWS

shanek2/invtero.net281

Memory analyzer

Analyzes and validates physical memory from various systems to extract process information and hypervisor details

travisfoley/dfirtriage335

Windows forensic tool

A digital forensic tool designed to gather and analyze data from Windows-based systems in incident response scenarios.

idiom/pftriage77

Malware analyzer

Tool to analyze files during malware analysis and triage by extracting properties and detecting malicious indicators.

nccgroup/windowsmempagedelta28

Memory anomaly detector

Software designed to monitor Windows executable memory page changes to detect anomalies in system behavior

mdecrevoisier/microsoft-eventlog-mindmap1K

Audit maps

Provides detailed mindmaps on Microsoft auditing capacities and event logs for security and monitoring

codeyourweb/fastfinder234

File scanner

Tools for detecting suspicious files and directories on Windows and Linux endpoints.

zhangtp1996/openfe_reproduce4

Fraud Detection Reproducibles

Reproduce experiments and results from a research paper on fraud detection using machine learning algorithms.

iamgroot42/mimir126

Model memorization analysis

A Python package for measuring memorization in Large Language Models.

rek7/mxtract582

Memory scanner

Analyzes and dumps memory to extract sensitive information from running processes

ksreenivasan/ood_federated_learning66

Federated Learning vulnerability research

Researchers investigate vulnerabilities in Federated Learning systems by introducing new backdoor attacks and exploring methods to defend against them.

lhfowl/robbing_the_fed23

Model inversion attack

This implementation allows an attacker to directly obtain user data from federated learning gradient updates by modifying the shared model architecture.