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CMU > SEI > CERT
- Pittsburgh, PA US
- https://insights.sei.cmu.edu/authors/dustin-updyke/
- https://orcid.org/0009-0000-9573-6093
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Baseline localization and classification models for the xView 2 challenge.
A small security playground implementation of GHOSTS User Simulation framework with an Active Directory deployment and Elastic.
Valkyrie Framework is an open source suite of tools that enable hunt teams to locate and identify hidden cybersecurity threats lurking in network traffic.
Python Mattermost Driver for APIv4
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
Range and simulation tools for executing realistic training and exercise events
DNS Tunneling using powershell to download and execute a payload. Works in CLM.
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
GHOSTS is a realistic user simulation framework for cyber experimentation, simulation, training, and exercise
President's Cup Cybersecurity Competition Challenges
PowerShell - Endpoint Analysis Solution Your Windows Intranet Needs
A virtual appliance for building cyber labs, challenges and competitions
SEER is a platform for assessing the performance of cybersecurity training and exercise participants.
Beacon Kibana Executable Report. Aggregates Sysmon Network Events With Elasticsearch and Kibana
Real Intelligence Threat Analytics (RITA) is a framework for detecting command and control communication through network traffic analysis.
Passive service locator, a python sniffer that identifies servers, clients, names and much more
GHOSTS Animator is a library and API for generating realistic NPCs for training and exercise.
© Copyright Header is a utility to manipulate software licenses on source code.
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
Repository for the Tetrad Project, www.phil.cmu.edu/tetrad.
A python-based chatbot for Mattermost (http://www.mattermost.org).
Adversarial Threat Landscape for AI Systems
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
🚨ATTENTION🚨 The NIST 800-53 mappings have migrated to the Center’s Mappings Explorer project. See README below. This repository is kept here as an archive.
This program generates cyber attack scenarios for use in cyber training exercises, red team planning, blue team planning, automated attack execution, and cybersecurity policy analysis.
SPECTRE enables GHOSTS clients to have and build individual preferences over time.