DumpsterFire
A modular, menu-driven tool for building time-delayed, distributed security event chains for Red, Blue, and Purple Team exercises.
What is DumpsterFire?
DumpsterFire is a modular, menu-driven tool for building customized, time-delayed, distributed security events. It allows Red, Blue, and Purple Teams to create chains of simulated incidents (called 'DumpsterFires') for drills, sensor testing, decoy operations, and training exercises. The tool generates realistic network and filesystem artifacts to mimic actual attack narratives.
Security professionals including Red Teams (for creating distractions and lures), Blue Teams (for controlled SOC drills and sensor mapping), and Purple Teams (for repeatable event chains to validate defenses).
It provides a scalable, automated way to run realistic security exercises without manual intervention, with extensible modules, time-delayed execution, and detailed logging for post-operation analysis.
Overview
"Security Incidents In A Box!" A modular, menu-driven, cross-platform tool for building customized, time-delayed, distributed security events. Easily create custom event chains for Blue- & Red Team drills and sensor / alert mapping. Red Teams can create decoy incidents, distractions, and lures to support and scale their operations. Build event sequences ("narratives") to simulate realistic scenarios and generate corresponding network and filesystem artifacts.
Use Cases
Best For
- Running automated Red Team decoy incidents to distract SOC analysts during engagements
- Conducting controlled Blue Team 'live fire' drills to test sensor and alert configurations
- Creating repeatable Purple Team event chains for consistent security posture mapping
- Simulating realistic attack narratives (e.g., insider threats, botnet activity) for training
- Generating time-delayed security events across distributed systems or timezones
- Adding customizable, playful 'Shenanigans' to cyber wargames or exercises
Not Ideal For
- Organizations with strict Python 3-only environments or modern security toolchains
- Teams needing real-time, interactive simulation dashboards or GUI-based management
- Projects requiring out-of-the-box integration with commercial SIEMs or ticketing systems
- Scenarios where extensive pre-built attack modules are needed without custom development
Pros & Cons
Pros
You can drop Python scripts into categorized directories under FireModules/, and DumpsterFire auto-detects them at startup, as highlighted in the README's section on extensibility.
Allows configurable time delays between Fire modules to mimic human attack timelines, with the menu guiding you to assign delays for more believable event chains.
The menu-driven dumpsterFireFactory.py script walks users through building, configuring, and igniting scenarios step-by-step, reducing command-line complexity.
Generates auto-generated date-time stamped logs in UTC for global operations and post-engagement analysis, providing accountability and correlation, as described in the Accountability section.
Includes modules like Rickrolling and custom URL openings, adding humor or distractions for wargames, with examples shown in the Shenanigans section of the README.
Cons
Built for Python 2.7.x, which is outdated and may pose security risks or compatibility issues; the README's 2020 update mentions a planned migration to Python3 but lacks confirmation of completion.
The README notes only about 30 more Fire modules in development, so the base toolset might be sparse, requiring custom work for specific or advanced attack simulations.
Relies on CLI and menu-driven interfaces without GUI, web dashboards, or APIs, making it less scalable for large teams or integration with modern security orchestration tools.
Frequently Asked Questions
Related Projects
Atomic Red TeamSmall and highly portable detection tests based on MITRE's ATT&CK.
CalderaAutomated Adversary Emulation Platform
APTSimulatorA toolset to make a system look as if it was the victim of an APT attack
Network Flight Simulator (flightsim)A utility to safely generate malicious network traffic patterns and evaluate controls.
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