Malware – Page 2 – Baker Street Forensics

Enhancing Malware Analysis with REMnux and AI

Those familiar with my work know that I’m a big fan of the REMnux Linux distribution for malware analysis. When I developed MalChela, I included a custom configuration that can be invoked that not only includes the MalChela tool suite but also integrates many of the CLI tools installed in REMnux, providing an easy-to-use GUI.

Recently, a new REMnux release was released on Ubuntu 24.04. This was a welcome upgrade because REMnux was previously locked to 20.04, which was becoming outdated. As soon as I noticed the release announcement, I downloaded the latest version and installed the MalChela suite. Everything ran smoothly, and the GUI interface even appeared slightly sharper without any changes on my part.

While reviewing the release notes for the new version, I discovered that REMnux now includes integration with Opencode AI. In REMnux, several models are preconfigured to recognize the tools included in the distribution and their capabilities and syntax. You can use natural language prompts, and the system will interpret the request, execute the appropriate tools against the file, and provide a summary of the results. As mentioned in the documentation:

The AI uses the REMnux MCP server to run the appropriate REMnux tools automatically. The MCP server offers guidance regarding the tools that the AI should consider, but it’s up to the AI agent to decide on the analysis workflow. And, of course, your interactions, requests, and observations can also direct the AI regarding the analysis steps.

Key capabilities available to AI assistants through the REMnux MCP server:

Analyze files based on detected type (PE, PDF, Office docs, scripts, ELF, etc.)

Get tool recommendations for a specific file without running them

Run specific REMnux tools directly, including piped commands

Extract indicators of compromise (IOCs) from text

Get usage help for any installed REMnux tool

I experimented with a few of the usual suspects in my corpus and provided pretty generic prompts like “analyze (file-xyz)” and “what are the IOCs?” The results were very positive – but I’ve only scratched the surface in testing.

Then I decided to see how adaptive this AI was and how easy it would be to make it aware of new tools and syntax. I provided the following:


MalChela tool suite is  installed in /home/remnux/Tools/MalChela
All are rust based tools so cd to the MalChela directory, and then ./target/release/fileanalyzer (path to executable) would be the syntax. 
The 4 tools below are the primary tools for static analysis.
  File Analyzer       |  Get the hash, entropy, packing, PE info, YARA and VT match status for a file  
  mStrings            |  Analyzes files with Sigma rules (YAML), extracts strings, matches ReGex. 
  NSRL Hash Lookup    |  Query an MD5 or SHA1 hash against NSRL
  Malware Hash Lookup |  Query a hash value against VirusTotal & Malware Bazaar

Immediately it began running the tools in MalChela against the malware file I was previously analyzing and provided a summary of the different tool results.

I plan to do a lot more testing but so far things are looking very promising.

So what do you think? Are you using AI in your malware analysis workflows? What capabilities of AI do you think are most useful when it comes to malware analysis? Let me know in the comments.

2025 Year in Review: Open Source DFIR Tools and Malware Analysis Projects

DFIR, Forensics, Mac, Malware, MITRE ATT&CK, PowerShell, Python, Raspberry Pi, Rust, SIgma, Triage, USB, yara

As 2025 draws to a close, I’m taking a moment to reflect on what turned out to be one of my most productive years in code. From major releases to entirely new projects, this year saw significant evolution across my DFIR toolkit—driven by real-world incident response needs, classroom teaching experiences, and late-night tinkering sessions fueled by good bourbon and better puzzles.

What started as continuing work on CyberPipe evolved into a year of substantial innovation: creating MalChela for YARA and malware analysis, building a portable Raspberry Pi forensics platform, developing automated timeline generation workflows, and crafting specialized utilities that solve specific problems I encountered in the field. Each tool represents not just lines of code, but practical solutions to challenges that digital forensics and incident response professionals face daily.

Whether you’re a seasoned forensic analyst, an incident responder building your toolkit, or a student just getting started in DFIR, my hope is that these open-source projects make your work a little easier and a lot more efficient. All tools remain freely available on GitHub, because I believe the best way to advance our field is to share knowledge and capabilities openly.

Here’s what kept me busy in 2025:

MalChela – YARA & Malware Analysis Toolkit (Rust)

My flagship project that evolved significantly throughout 2025:

March: Initial release – Combined 10 programs into one Rust workspace for YARA and malware analysis
May: v2.1 – Added smoother workflows, better third-party tool integration, and enhanced argument handling
May: v2.2 “REMnux Release” – Native support for REMnux, integrations with Volatility3, Tshark, YARA-X
June: v3.0 – Major update introducing Case Management system, FileMiner (replacing MismatchMiner), and tool suggestion capabilities based on file characteristics
July: v3.0.1 – Refinements to mStrings, improved MITRE mappings, “Select All” functionality, optimizations for running on Toby
August: v3.0.2 – Enhanced threat hunting with MITRE ATT&CK technique lookup

MalChela at a Glance

Rust-based malware analysis toolkit combining YARA scanning, file analysis, hash generation, string extraction with MITRE ATT&CK mapping, and automated malware sample extraction from password-protected archives
Multiple specialized utilities including mzhash/xmzhash for corpus generation, file type mismatch detection, entropy analysis, PE structure examination, and fuzzy hashing capabilities
Integrated threat intelligence with VirusTotal and Malware Bazaar API support, NSRL database queries for known-good file filtering, and Sigma rule application for IOC identification
Case management system (v3.0) featuring unified tracking of files, tools, and notes in case.yaml format with auto-saved outputs, tagging, search functionality, and VS Code integration
Extensible architecture supporting custom tool integration via tools.yamlconfiguration, enhanced support for Volatility 3, TShark, and YARA-X, with both GUI and CLI modes (WSL2-compatible on Windows)
Complete documentation embedded as PDF or online

MalChela v3.0: Case Management, FileMiner, and Smarter Triage

https://github.com/dwmetz/MalChela

CyberPipe – Incident Response Collection Tool (PowerShell)

Continued evolution of the enterprise digital evidence collection script:

May: v5.1 – Streamlined profiles with better flexibility, customizable collection profiles
October: v5.2 – Improved collection methods with dual disk space validation, SHA-256 hashing of artifacts, single-file reporting, network collection simplification
November: v5.3 – Critical PowerShell 5.1 compatibility fixes, dual validation logic, enhanced reliability across all PowerShell environments

CyberPipe v5.3: Enhanced PowerShell Compatibility and Reliability

https://github.com/dwmetz/CyberPipe

CyberPipe-Timeliner ✱New✱ (PowerShell)

November: CyberPipe-Timeliner – New companion project to CyberPipe that automates the workflow from Magnet Response collections to unified forensic timelines using Eric Zimmerman’s EZ Tools and ForensicTimeliner

CyberPipe-Timeliner: From Collection to Timeline in One Script

https://github.com/dwmetz/CyberPipe-Timeliner

Toby – Portable Raspberry Pi Forensics Toolkit

July: Released Toby – A compact forensics toolkit built on Raspberry Pi Zero 2 W running customized Kali Linux, designed for headless operation via SSH/VNC, perfect for field analysis and malware triage

Portable Forensics with Toby: A Raspberry Pi Toolkit

Toby-Find

July: Toby-Find – Terminal-based command-line helper tool for discovering CLI forensics tools in KALI and REMnux environments, created initially for university teaching

Toby-Find: Simplifying Command-Line Forensics Tools

https://github.com/dwmetz/Toby

Crabwise – USB Device Benchmark Utility (Rust)

August: Released Crabwise – A lightweight USB benchmarking tool that measures true read/write speeds of USB devices for forensic workflows. Tests write throughput with pseudo-random data and read performance under uncached conditions. Includes logging functionality to track performance across different cables, hubs, and connection paths, helping forensic investigators optimize their hardware setups.

Is your USB device slowing down your forensic investigation?

https://github.com/dwmetz/Crabwise

Toolbox Utilities – Specialized Python and Bash Scripts

Standalone tools maintained in the Toolbox repository:

October: CoreBreaker.py – Breaks large yara-rules-core files into smaller .yar files for tool ingestion
October: EtTu.py – Caesar cipher brute force decoder (created for Murdle puzzle solving); After all, All work and no play makes Jack a dull boy.
November: cloudtrail_timeline.py – Parses AWS CloudTrail JSON logs and outputs CSV format for Timeline Explorer
November: mac_triage_timeline.sh – Processes Mac-Triage ZIP files and generates timeline for Timeline Explorer
November: uac_timeline.sh – Processes UAC tar.gz files and generates timeline for Timeline Explorer (Linux/macOS)

https://github.com/dwmetz/Toolbox

All projects are available on my GitHub at github.com/dwmetz, with detailed documentation on bakerstreetforensics.com. My goal is making DFIR and malware analysis more accessible, automated, and efficient for incident responders and forensic analysts.

Enhance Threat Hunting with MITRE Lookup in MalChela 3.0.2

DFIR, Forensics, Malware, MITRE ATT&CK, Rust

Understanding adversary behavior is core to modern forensics and threat hunting. With the release of MalChela 3.0.2, I’ve added a new tool to your investigative belt: MITRE Lookup — a fast, offline way to search the MITRE ATT&CK framework directly from your MalChela workspace.

Whether you’re triaging suspicious strings, analyzing IOCs, or pivoting off YARA hits, MalChela can now help you decode tactics, techniques, and procedures without ever leaving your terminal or GUI. MITRE Lookup is powered by a local JSON snapshot of the ATT&CK framework (Enterprise Matrix), parsed at runtime with support for fuzzy searching and clean terminal formatting. No internet required.

What It Does

The MITRE_lookup tool lets you:

Search by Technique ID (e.g., T1027, T1566.001)
Search by topic or keyword (e.g., ‘RDP’, ‘Wizard Spider’)
Get tactic category, platforms, and detection guidance
Optionally include expanded content with the –full flag
Use from the CLI, MalChela launcher, or GUI modal

Example:

$ ./target/release/MITRE_lookup -- T1059.003

T1059.003 - Windows Command Shell

Tactic(s): execution

Platforms: Windows

Detection: Usage of the Windows command shell may be common on administrator, developer, or power user systems depending on job function. If scripting is restricted for normal users, then any attempt to enable scripts running on a system would be considered suspicious. If scripts are not commonly used on a system, but enabled, scripts running out of cycle from patching or other administrator functions are suspicious. Scripts should be captured from the file system when possible to determine their actions and intent...

GUI Integration

Select MITRE Lookup in the left-hand Toolbox menu
Use the input field at the top of the modal to enter a keyword or technique ID (e.g., `T1059` or `registry`)
Use the “Full” checkbox for un-truncated output
“Save to Case” option

Saving for Later

You can save MITRE Lookup results directly from the GUI, either as a standalone markdown file to a designated folder, or into the active Case Notes panel for later reference. This makes it easy to preserve investigative context, cite specific TTPs in reports, or build a threat narrative across multiple tools. The saved output uses clean Markdown formatting — readable in any editor or compatible with case management platforms. This feature is already live in v3.0.2 and will evolve further with upcoming case linkage support.

*Markdown view of a **MITRE_lookup** report*

Why MITRE ATT&CK in MalChela?

MalChela already focuses on contextual forensics — understanding not just what an artifact is, but why it matters. By embedding MITRE ATT&CK into your daily toolchain:

You reduce pivot fatigue from switching between tools/web tabs
You boost investigation speed during triage and reporting
You enable a more threat-informed analysis process

Whether you’re tagging findings, crafting YARA rules, or writing case notes, the MITRE integration helps turn technical output into meaningful insight — all from within the MalChela environment.

Toby-Find: Simplifying Command-Line Forensics Tools

DFIR, Forensics, Malware, Memory Analysis, Raspberry Pi, Triage

In digital forensics, we often take a toolbox approach — success hinges on having the right tool for the job. Some tools offer broad functionality, while others are deeply specialized. Distributions like KALI and REMnux do a fantastic job bundling a wide range of forensic and security tools, but keeping track of what’s actually installed can be a challenge.

If you’re using a graphical interface, browsing through available packages is fairly intuitive. But when you’re living in the terminal — as many analysts do — that discoverability disappears. There’s no built-in index of command-line tools or how to invoke them.

The first version of Toby-Find was born out of necessity. I teach a Network Forensics course at the university, using a custom VM loaded with tools like Zeek, Tshark, Suricata, and more. I wanted students to have an easy, searchable way to see what CLI tools were available and how to run them — without needing to memorize commands or dig through man pages.

Later, when I built Toby (a forensic-focused Raspberry Pi rig running a customized KALI install), I updated Toby-Find to include the complete CLI toolset geared toward forensics and malware analysis from the KALI ecosystem.

And because I can’t leave well enough alone, I decided to build a REMnux-compatible version too.

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Once installed, you can launch Toby-Find (via tf, toby-find, or tf-help) from any terminal and instantly search for tools, descriptions, examples, and more.

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📦 Installation

1. Clone the repository:

git clone https://github.com/dwmetz/Toby.git

2. Make the install script executable:

cd Toby
chmod +x install.sh

3. Run the installer:

./install.sh

4. Follow the prompt to choose your environment (KALI or REMnux)
5. Open a new terminal or run:

source ~/.bashrc   # or ~/.zshrc depending on shell

🚀 Usage

tf [keyword]

Examples:

tf yara
tf volatility
tf hash

To view the full list:

tf-help

Whether you’re working from a custom VM, a rugged Pi, or a hardened REMnux box, Toby-Find gives you a fast, terminal-friendly way to surface the tools at your disposal — without breaking focus. It’s lightweight, portable, and easy to extend for your own lab or classroom.

You can grab the full installer from GitHub, and contributions are always welcome. If you find it helpful — or build on it — I’d love to hear about it.