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Introduction:
Memory forensics is a cornerstone of incident response, allowing investigators to uncover stealthy malware, rootkits, and in‑memory artifacts that evade traditional disk‑based analysis. However, Linux memory forensics has long been hampered by the need for kernel debug symbols (vmlinux) that match the exact target system – a requirement that often proves impossible in heterogeneous production environments. Trail of Bits has unveiled mquire, a groundbreaking tool that performs Linux memory analysis without any external dependencies, using an SQL‑based query engine reminiscent of OSquery. This article dives into mquire’s capabilities, provides step‑by‑step installation and usage guides, and explores how it can transform digital forensics and incident response (DFIR) workflows.
Learning Objectives:
- Understand the traditional challenges of Linux memory forensics and how mquire overcomes them.
- Learn to install, configure, and use mquire for memory acquisition and analysis.
- Master SQL queries to extract forensic artifacts such as processes, network connections, and kernel modules.
- Compare mquire with established tools like Volatility.
- Apply mquire in real‑world incident response scenarios to detect advanced threats.
You Should Know:
- The Challenge of Linux Memory Forensics and How Mquire Solves It
Traditional Linux memory analysis, most notably with Volatility, relies on “profiles” – essentially a database of kernel data structures and debug symbols. These profiles must be built from the exact kernel version and configuration of the target system, requiring access to the original vmlinux file or at least the System.map. In practice, incident responders often encounter systems where these symbols are missing, outdated, or the kernel is custom‑compiled, rendering Volatility ineffective.
Mquire bypasses this limitation entirely. It employs a novel technique to reconstruct kernel objects directly from the memory dump without needing any external symbol files. Moreover, it exposes the extracted data through an SQL interface, allowing investigators to run structured queries – much like OSquery does for live systems – but on a static memory image. This approach not only removes the symbol dependency but also makes memory analysis accessible to anyone comfortable with SQL.
Step‑by‑step guide – Understanding the concept:
- No symbol dependency: Mquire parses memory by walking kernel data structures using heuristics and known offsets that are resilient across kernel versions.
- SQL abstraction: After parsing, mquire populates virtual tables (e.g.,
processes,network_connections,kernel_modules) that can be queried with standard SQL. - Forensic soundness: Mquire works on raw memory dumps (e.g., from LiME, /dev/mem, or VM snapshots) without altering the evidence.
2. Installing Mquire on Linux
Mquire is distributed as open source via GitHub. The installation process is straightforward and requires a standard Linux development environment.
Step‑by‑step guide:
1. Clone the repository:
git clone https://github.com/trailofbits/mquire.git cd mquire
2. Build the tool:
Mquire is written in Rust for performance and safety. Ensure you have Rust and Cargo installed (or use the provided Makefile):
make
This compiles the binary and places it in the `target/release/` directory.
3. Install system‑wide (optional):
sudo make install
4. Verify installation:
mquire --version
You should see the version number, confirming a successful build.
Alternative installation: If you prefer Docker, a pre‑built image may be available:
docker pull trailofbits/mquire:latest
3. Capturing Memory Dumps with Mquire
Before analysis, you need a memory image. Mquire can capture memory directly using its built‑in acquisition module, or you can feed it dumps from other tools.
Step‑by‑step guide – Using mquire capture:
1. Acquire memory from a live Linux system:
sudo mquire capture --output /evidence/memory.lime
This uses the LiME kernel module (automatically loaded) to dump RAM. Options include `–compress` (gzip compression) and `–hash sha256` to generate an integrity hash.
2. If you already have a memory dump (e.g., from a hypervisor or forensic tool), simply note its path. Mquire supports raw, LiME, and ELF coredump formats.
3. Verify the dump:
mquire info /evidence/memory.lime
This command displays metadata such as the architecture, kernel version, and the presence of essential data structures.
4. Analyzing Memory Dumps with SQL Queries
Once a memory image is loaded, mquire provides an interactive SQL shell. This is where the power of the tool becomes apparent.
Step‑by‑step guide – Basic queries:
1. Launch the mquire shell:
mquire shell /evidence/memory.lime
You’ll be greeted by a SQLite‑like prompt.
2. List available tables:
.tables
Common tables include processes, network_connections, kernel_modules, files, `registry_keys` (for Windows‑like artifacts), and bash_history.
3. Query all running processes:
SELECT pid, name, parent_pid, start_time, path FROM processes;
This returns a list of processes extracted from the kernel’s task list.
4. Find suspicious network connections:
SELECT FROM network_connections WHERE state = 'LISTEN' AND port > 1024;
Reveals listening ports that might indicate backdoors.
5. Enumerate loaded kernel modules:
SELECT name, size, refcount FROM kernel_modules;
Helps identify rootkits that hide modules.
5. Advanced Queries for Incident Response
Real incident response often requires correlating multiple artifacts. Mquire’s SQL engine supports joins, subqueries, and aggregations.
Step‑by‑step guide – Complex investigations:
- Join processes with network connections to find processes with established outbound connections:
SELECT p.name, p.pid, n.remote_ip, n.remote_port, n.local_port FROM processes p JOIN network_connections n ON p.pid = n.pid WHERE n.state = 'ESTABLISHED';
- Search for processes with a known malicious name pattern:
SELECT FROM processes WHERE name LIKE '%xmr%' OR name LIKE '%minerd%';
- Timeline analysis – sort processes by start time:
SELECT pid, name, start_time FROM processes ORDER BY start_time DESC;
This can reveal a malware process that launched shortly after a user logged in.
4. Extract bash commands from shell history:
SELECT command, time FROM bash_history WHERE command LIKE '%wget%' OR command LIKE '%curl%';
5. Export results to JSON for further processing:
mquire query /evidence/memory.lime "SELECT FROM processes WHERE name = 'sshd'" --format json > sshd_procs.json
6. Comparing Mquire with Volatility and Other Tools
Volatility has been the gold standard for memory forensics for years, but mquire offers distinct advantages in certain scenarios.
| Feature | Volatility | Mquire |
||-||
| Symbol dependency | Requires exact kernel profile | No symbols needed – works out‑of‑the‑box |
| Query language | Plugins with limited output formatting | Full SQL (SELECT, JOIN, WHERE, etc.) |
| Learning curve | Steep; need to understand memory structures | Accessible to anyone with SQL knowledge |
| Kernel coverage | Wide, but profile‑dependent | Newer, but aims for broad compatibility |
| Extensibility | Custom plugins in Python | Custom tables can be added in Rust |
Step‑by‑step – Converting a Volatility command to mquire:
Volatility: `volatility -f mem.dump –profile=LinuxUbuntu_5_4_0-26-generic_x64 linux_pslist`
Mquire: `mquire query mem.dump “SELECT FROM processes”`
While Volatility remains indispensable for deep dive analysis of specific structures, mquire excels in rapid triage and environments where profile generation is impractical.
7. Integrating Mquire into Your DFIR Workflow
To maximize efficiency, mquire should be part of a broader forensic toolkit. Here’s how to incorporate it into common workflows.
Step‑by‑step guide – Automation and integration:
1. Automate triage with a script:
!/bin/bash DUMP=$1 OUTPUT_DIR=/cases/$(basename $DUMP .lime) mkdir -p $OUTPUT_DIR mquire query $DUMP "SELECT FROM processes" --format json > $OUTPUT_DIR/processes.json mquire query $DUMP "SELECT FROM network_connections" --format json > $OUTPUT_DIR/network.json mquire query $DUMP "SELECT FROM kernel_modules" --format json > $OUTPUT_DIR/modules.json
2. Feed results into a SIEM or threat intelligence platform:
Convert JSON to a format compatible with your tools (e.g., Splunk, ELK).
3. Use alongside disk forensics:
Cross‑reference process paths with files carved from disk using The Sleuth Kit.
4. Create YARA rules for memory scanning:
While mquire doesn’t natively support YARA, you can export memory regions and scan them externally.
What Undercode Say:
- Key Takeaway 1: Mquire shatters the biggest barrier in Linux memory forensics – the need for kernel debug symbols – enabling analysis on any system without prior preparation.
- Key Takeaway 2: By adopting an SQL query model, mquire dramatically lowers the technical barrier, allowing incident responders to focus on hunting threats rather than wrestling with memory internals.
- Analysis: This tool is a game‑changer for DFIR teams. In a breach scenario, every minute counts. Mquire’s ability to work across diverse kernels without building profiles can cut investigation time from hours to minutes. The SQL interface also opens the door to automated analysis pipelines and integration with security orchestration platforms. However, as a young tool, its artifact coverage may not yet match Volatility’s depth. Community adoption and validation will be key to its maturation. Nonetheless, its approach points to a future where memory analysis is as routine and accessible as log analysis.
Prediction:
Mquire’s innovative approach will likely catalyze a new generation of memory forensics tools. We can expect to see cloud‑based memory analysis services that accept raw dumps and return SQL‑queryable results, integration with EDR agents for live memory interrogation, and the eventual incorporation of similar symbol‑free techniques into mainstream tools like Volatility. As fileless attacks and in‑memory malware become the norm, the ability to rapidly analyze memory without prior kernel knowledge will shift from a luxury to a necessity. Mquire may well set the standard for how we perform memory forensics in the coming decade.
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