Malicious traffic detection system
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Maltrail
Maltrail is a network traffic detection system that identifies communication with known malicious
infrastructure and reports selected traffic anomalies. It matches domains, URLs, IP addresses,
IP:port pairs, and User-Agent values observed on the network against a set of indicators called
trails.
A detection is recorded as a single event containing the source, destination, protocol, matched trail, classification, and trail source:
"2026-08-07 09:14:22.117034" gw 10.13.13.2 57809 1.1.1.1 53 UDP DNS malware.bakewithdavid.com "asyncrat (malware)" (static)
Maltrail is designed for indicator-based network monitoring. Its heuristic detections supplement trail matching, but it is not a replacement for endpoint telemetry or a general-purpose intrusion prevention system.
Features
- A full trail build combining more than 3,000 bundled static files, 42 public-feed integrations, and optional operator-supplied trails.
- A multithreaded Rust sensor using libpcap, with optional Linux
PACKET_FANOUTcapture workers. - A Python server providing the reporting interface, event intake, and HTTP API.
- Plain-text custom trails and whitelists that can be reviewed and version-controlled.
- Heuristics for scanning, DNS exhaustion, DGA-like lookups, suspicious downloads, proxy probes, suspicious User-Agent values, and related network activity.
- Local event logging, remote Maltrail logging, CEF over syslog, and Logstash JSON output.
- Deployment validation with
maltrail-sensor -Tand optional Prometheus metrics.
Contents
- Architecture
- Reporting interface
- Performance
- Installation
- Configuration
- Trails
- Events and API
- Operations
- Documentation
- Contributing
- Project
Architecture
Maltrail consists of two independent processes that may run on the same host or on separate hosts:
┌──────────┐ events (UDP or file) ┌──────────┐
│ sensor │ ───────────────────────► │ server │ ◄── browser
└──────────┘ └──────────┘
Rust Python
libpcap + PACKET_FANOUT reporting UI + API
trail matching + heuristics
The sensor captures traffic, performs trail matching and heuristic analysis, and produces events.
It can write events locally (LOG_DIR), send them to a remote Maltrail server (LOG_SERVER), or do
both. It can also emit CEF over syslog (SYSLOG_SERVER) and JSON to Logstash
(LOGSTASH_SERVER).
The server receives and stores remote events, serves locally available event logs, and provides the web interface and API.
Reporting interface
Maltrail includes a browser-based reporting interface for exploring detected traffic, with live updates, field-aware search, retro hunting, geographic views, triage, saved views and export.
The interface is served by server.py at HTTP_ADDRESS:HTTP_PORT. It is plain JavaScript with a
single third-party runtime dependency (PapaParse, for CSV parsing) and no build step. One day is
viewed at a time, selected with a date picker that doubles as an event-density grid over the
available daily logs. Events are streamed from /events and aggregated in the browser into
threats — one row per distinct (source, trail) — shown in a sortable grid with a detail panel.
| Feature | Notes |
|---|---|
| Live mode | Appended events are pushed over Server-Sent Events (/live) and merged into the current view. Falls back to polling byte ranges of the daily log when SSE is unavailable, or for sessions the stream cannot serve. New high-severity threats can raise a desktop notification and an audible alert; both can be muted |
| Search | Field-scoped tokens (src: dst: port: proto: type: trail: info: family: tag: uid: sev: dir: status:; family:interlock pulls in interlock-1/-2, the shards one feed dump arrives split into) combined with space as AND, - to exclude, * wildcards, CIDR (src:10.0.0.0/8), and numeric ranges and comparisons (port:>1024, count:>=100). Active filters appear as removable chips |
| Retro hunt | Searches all retained daily logs for one indicator (/hunt), not just the day in view. Bounded by a day limit, a wall-clock budget and a sample cap; a day the budget cut short is reported separately from the completed days rather than counted as a finished total. A per-day sidecar index (LOG_DIR/index/, USE_EVENT_INDEX) lets the sweep skip every non-matching line and makes /counts exact |
| World map | Per-country event density for the selected day (/geo), placing the external endpoint of each event. Events that cannot be attributed to an external address are reported as unmapped rather than guessed. Set HOME_LAT / HOME_LON to draw origin arcs |
| Triage | Per-threat status (new / investigating / resolved / false positive), free-text notes, tags, and hiding. Whitelist rules and OSINT pivots are available from the row context menu |
| Saved views | Named filter presets |
| Export | The current filtered view as CSV, JSON, or defanged indicators |
| Appearance | Dark and light themes, and discrete text-size steps |
Triage state, saved views, tags and appearance settings are stored in the browser
(localStorage), not on the server: they are per-browser and per-origin, and are not shared
between analysts.
Sessions restricted with a network filter see only events from their own networks, and that restriction applies to the counts, map and blacklist endpoints as well as to the event list.
Country and ASN enrichment for individual addresses is looked up at stat.ripe.net by the
server, which caches the results and serves them to the interface from its own /ripe
endpoint; the browser talks to nothing but Maltrail. Set DISABLE_RIPE_LOOKUPS to switch the
outbound lookups off entirely. Without them — or on a host with no internet access — flags come
from the local RIR table instead and everything else in the interface works offline.
Performance
Performance depends on processor, traffic composition, trail-set size, capture driver, and network interface. The figures below measure the sensor's packet-processing path in isolation; they are not end-to-end live-capture measurements.
Representative measurements on an AMD Ryzen 7 PRO 4750U with heuristics enabled and a 1.5 million-row trail set:
| Traffic | Time per packet |
|---|---|
| ICMP echo, 58 bytes | 101 ns |
| TCP SYN, 70 bytes | 302 ns |
| Bulk TLS, 1,473 bytes | 402 ns |
| DNS query with a warm cache, 93 bytes | 452 ns |
| Mixed traffic, 866-byte average | 552 ns |
| HTTP request, 169 bytes | 602 ns |
| DNS query with a unique name, 93 bytes | 1,102 ns |
Offline comparison runs using the same generated capture, configuration, and trail set measured a
14–37× lower steady-state per-packet cost than the retired Python sensor across the tested systems.
Those figures separate whole-process time from steady state, because trail loading dominates a
short replay. Detection itself is asserted separately, by the 42-case corpus in
sensor/tests/replay.rs.
Measure it on the target system with:
cargo bench --manifest-path sensor/Cargo.toml --bench hotpath
One capture worker is used by default. Additional workers can increase capture capacity, but Linux
flow hashing divides per-source state between workers and therefore reduces the sensitivity of some
scan heuristics. In the documented test, 91% of single-worker heuristic alerts remained with two
workers, 86% with four, and 65% with eight. Exact trail matching was unchanged. Increase
CAPTURE_FANOUT only when capture-drop metrics show that it is necessary.
Benchmark methodology, hardware results, profiler output, memory measurements, and live fanout
checks are documented in sensor/docs/REPORT.md.
Installation
Installer
The installer is verified on twelve Linux distributions — Debian, Ubuntu, Fedora, Rocky, AlmaLinux,
Arch, openSUSE Leap and Tumbleweed, and Alpine — plus FreeBSD, NetBSD, OpenBSD and macOS, on every
release, with the full result recorded in docs/compat. Raspberry Pi OS and other
64-bit ARM systems use the aarch64 build; 32-bit ARM has no prebuilt sensor and must build it
from source.
curl -fsSL https://raw.githubusercontent.com/stamparm/maltrail/master/install.sh | sudo sh
It installs dependencies, creates a managed checkout under /opt/maltrail, verifies the checksum
of the prebuilt sensor, creates an unprivileged maltrail account, installs systemd units, prepares
the log and state directories, and starts the sensor and server. Re-running the installer upgrades
the managed checkout.
Review the script before running it with elevated privileges. From an existing checkout, the dry run shows the commands without changing the system:
sh install.sh --dry-run
Common installer options:
sh install.sh --role sensor # Install only the sensor
sh install.sh --ref 3.1.2 # Install a release tag instead of master
sh install.sh --no-service # Install without changing systemd
sh install.sh --dry-run # Print commands without applying them
sh install.sh --uninstall # Remove the managed installation; keep logs and state
The dashboard is available at http://127.0.0.1:8338 after installation. Note that the shipped
HTTP_ADDRESS is 0.0.0.0, so it is reachable on every interface, not only loopback — and
the default credentials are admin / changeme!. Change USERS, and set HTTP_ADDRESS to
127.0.0.1 (or put the server behind a reverse proxy with TLS), before the host is on an
untrusted network.
The initial trail build can take several minutes. The sensor does not detect trail matches until a
valid trail set is available. The systemd unit runs the sensor's -T validation before startup so
that missing privileges, an unwritable log directory, or an invalid trail set causes startup to
fail visibly.
The installer test harness covers twelve distributions, and "it installed" is not the assertion: in
each one the server is started and asked for /ping, the sensor is asked to validate itself with
-T, the units are checked for paths that resolve, the installer is re-run to prove an upgrade
keeps operator configuration, and --uninstall is run. Every result is recorded per platform in
docs/compat, and the page there is generated from those rows rather than written
by hand.
Alpine and other musl systems get a -musl sensor build. They used to be told the prebuilt binary
was glibc-linked and to compile their own; the sensor builds and runs on musl natively, so that was
a missing artefact rather than a platform limit.
Building from source
The sensor requires Rust 1.74 or newer, libpcap development headers, and the system's capability tools. The server and trail updater require Python 3.6 or newer.
Install the distribution packages:
# Debian / Ubuntu / Raspberry Pi OS
sudo apt-get install cargo libpcap-dev libcap2-bin python3
# RHEL / Fedora
sudo dnf install cargo libpcap-devel libcap python3
# openSUSE / SLES
sudo zypper install cargo rust libpcap-devel libcap-progs python311
Then build and validate the sensor:
git clone --depth 1 https://github.com/stamparm/maltrail.git
cd maltrail
cargo build --release --manifest-path sensor/Cargo.toml
sudo setcap cap_net_raw,cap_net_admin=eip \
sensor/target/release/maltrail-sensor
sudo install -d -o "$USER" -g "$(id -gn)" -m 750 /var/log/maltrail
sensor/target/release/maltrail-sensor -T
sensor/target/release/maltrail-sensor
Start the server in another terminal or on another host:
python3 server.py
Prebuilt sensor binaries are attached to current releases with SHA-256 checksums: Linux x86_64
and aarch64 against both glibc and musl, macOS on Apple silicon and Intel, FreeBSD amd64, and
Windows x86_64.
The glibc builds link libpcap statically and target glibc 2.28, so the C library is the only thing
they need — nothing to install, on RHEL 8+, Debian 10+, Ubuntu 18.04+ and Leap 15.x alike. The musl
builds are fully static, so Alpine needs nothing at all. The Windows build is 64-bit and needs Windows 10 or later plus
Npcap installed before it will start — wpcap.dll is a load-time dependency,
so without it the loader refuses the executable rather than failing at capture. The archive says so
too. From a checkout, install.ps1 does the rest:
powershell -ExecutionPolicy Bypass -File install.ps1
It refuses to install without Npcap, puts the binary, configuration and support tree under
%ProgramFiles%\Maltrail, keeps logs and the trail set in %ProgramData%\Maltrail, seeds the trail
set from the release, runs the sensor's own -T preflight, and starts it at boot as SYSTEM via a
scheduled task. -Uninstall removes the task and the program directory and keeps everything under
%ProgramData%.
Binaries from 3.1.1 and earlier did not: they linked libpcap dynamically, and asked for it by
the name their AlmaLinux build host uses. Debian and Ubuntu ship the identical library under the
older name libpcap.so.0.8, so those binaries stop before they start —
./maltrail-sensor: error while loading shared libraries: libpcap.so.1: cannot open shared object file
— on a machine that has libpcap installed. install.sh links the missing name for you. By hand:
# adjust the directory for your architecture: aarch64-linux-gnu, or /usr/lib64 on RPM distributions
sudo ln -sf /usr/lib/x86_64-linux-gnu/libpcap.so.0.8 /usr/lib/x86_64-linux-gnu/libpcap.so.1
sudo ldconfig
Systemd
The supplied packaging/systemd/ units run both processes as the
unprivileged maltrail user. Systemd creates /var/log/maltrail and /var/lib/maltrail, restricts
filesystem access, and grants the sensor CAP_NET_RAW and CAP_NET_ADMIN.
The installer configures these units automatically. For an existing source installation, follow
the manual service procedure in sensor/docs/INSTALL.md.
Check service state and logs with:
systemctl status maltrail-sensor maltrail-server
journalctl -u maltrail-sensor -f
Docker
Start the supplied Compose deployment with:
docker compose -f docker/docker-compose.yml up -d
Container configuration, storage, privileges, and health checks are documented in
docker/README.md.
Configuration
Maltrail reads maltrail.conf, which contains separate [Sensor] and [Server] settings. The
installer places the managed configuration at /etc/maltrail.conf.
Frequently used sensor options include:
| Option | Purpose |
|---|---|
MONITOR_INTERFACE |
Capture interface or interfaces; any selects all supported interfaces |
CAPTURE_FILTER |
BPF capture filter |
CAPTURE_FANOUT |
Number of Linux capture sockets; defaults to one |
CAPTURE_WORKERS |
Capture workers, one socket each; defaults to CAPTURE_FANOUT, so one unless either is set |
LOG_DIR |
Local event-log directory |
TRAILS_FILE |
Generated trail database |
LOG_SERVER |
Remote Maltrail event server |
SYSLOG_SERVER |
CEF syslog destination or destinations |
LOGSTASH_SERVER |
Logstash JSON destination or destinations |
STATS_ADDRESS |
Prometheus metrics listener; disabled unless configured |
UPDATE_PERIOD |
Trail refresh interval |
STATIC_TRAILS_URL |
Where the assembled static trail set is fetched from; pin it to a dated release to control when new content lands |
USER_WHITELIST |
Operator-managed indicators that should not alert |
CUSTOM_TRAILS_DIR |
Operator-managed trail directory |
STATIC_TRAILS_DIR |
Optional checkout of the trails repository; only used to show a trail's source citation in the UI |
PROCESS_COUNT applies to the retired Python sensor and to the legacy event-log throttle; it does
not set the Rust sensor's worker count. Configure capture workers with CAPTURE_FANOUT or
CAPTURE_WORKERS instead.
Run the deployment check after changing configuration:
sensor/target/release/maltrail-sensor -T
The check validates configuration, trails, whitelist entries, capture filter, privileges, log storage, update support, and worker settings. A successful check includes positive trail and whitelist counts rather than only confirming that files exist.
Trails
A trail is one indicator — a domain, URL, IP address, IP:port pair, User-Agent, JA3/JA4
fingerprint or certificate hash — together with what it means and where it came from. The updater
merges four sources into TRAILS_FILE, in this order:
| source | where it comes from |
|---|---|
| Feeds | feeds/*.py, fetched directly by your deployment from each publisher |
| Custom | CUSTOM_TRAILS_DIR and CUSTOM_TRAILS_URL, your own indicators |
| Static | the assembled set from stamparm/trails, fetched from STATIC_TRAILS_URL; separately licensed |
| Engine lists | data/mass_scanner*.txt, shipped here because they change rarely |
The static trails live in their own repository. Detection content changes tens of times a
day; the engine does not, and keeping them together meant updating detection required pulling code
and made this repository's history unusable. STATIC_TRAILS_URL points at the newest published
set:
STATIC_TRAILS_URL https://github.com/stamparm/trails/releases/latest/download/trails.csv.gz
Point it at a specific content-YYYYMMDD-HHMM release instead to pin a version, so a bad publish
is not immediately global. The set is cached next to TRAILS_FILE, which is what makes an offline
or air-gapped rebuild work; the published sha256 is checked before downloading, so a deployment
that updates more often than the content changes transfers 65 bytes rather than 11 MB, and a
payload that does not match its digest is refused in favour of the cache.
update_trails() publishes a new TRAILS_FILE atomically and only after a successful build. Feeds
that return nothing are reported by name, so a deployment does not silently depend on a source that
has quietly retired.
Add your own indicators under CUSTOM_TRAILS_DIR, and anything that must never raise an event to
USER_WHITELIST. Keep both outside the installation directory so an upgrade cannot overwrite them.
Static trail contributions go to stamparm/trails; new feeds go here. Either way an indicator needs a classification and a source somebody can check — see Contributing.
Events and API
Maltrail records one whitespace-separated event per detection, using CSV quoting where a value contains spaces:
"<time>" <sensor> <src_ip> <src_port> <dst_ip> <dst_port> <proto> <type> <trail> "<info>" <reference>
The type field identifies what matched, including DNS, IP, IPORT, URL, PATH, HTTP,
UA, PORT, CERT, JA3, and JA4. The info field contains the trail classification, and
reference identifies the static list, feed, custom source, or heuristic that produced it. The
JA3/JA4 types fire on TLS client fingerprints: an implant's TLS stack survives every
address and domain rotation, so its hello hash keeps matching after everything else has burned
(published by the abuse.ch SSLBL JA3 feed).
Indicator lookup
Use /check to query one domain, IP address, or URL:
curl 'http://127.0.0.1:8338/check?q=www.sub.evil.example'
{
"query": "www.sub.evil.example",
"found": true,
"trail": "evil.example",
"info": "asyncrat (malware)",
"reference": "(static)",
"confidence": 100
}
The confidence field (0-100, or null when unavailable) says how strongly the sources back the
listing: 40 for a single feed, +15 per additional feed agreeing independently up to 100, and full
marks for the operator's own custom and static entries. It is computed at trail-update time from
feed agreement into a trails.confidence sidecar next to trails.csv; a server pulling trails
from an UPDATE_SERVER has no provenance to score and reports null. Use it to prioritize
triage - a single-feed listing at 40 deserves a second look before it earns a firewall rule.
A subdomain lookup can match its listed parent. URL lookups check host/path before checking the
host alone. The server reads the memory-mapped trail database and observes trail updates without a
restart.
Public static and feed trails are available without authentication, consistent with the /trails
endpoint used by remote sensors. Custom trails require an authorized session; an unauthorized
custom-only lookup is reported as a miss. Event data remains authenticated.
Operations
Monitoring
Use maltrail-sensor -T as a deployment and configuration gate. The supplied systemd unit runs it
as ExecStartPre.
To confirm that detection itself works — not just that the processes start — run:
python3 server.py --detect-test
It replays a crafted pcap of emulated malicious traffic (trail hits on a DNS query, an IP, an
IP:port, a URL path and a Host header, plus the SQL-injection, traversal, RCE, XSS, proxy-probe,
sinkhole, missing-Host and port/web/infection-scanning heuristics) through the installed sensor
and asserts that every expected detection fires. It needs no root, no interface and no trail set of
its own. A healthy install prints 20/20 detection(s) fired.
When STATS_ADDRESS is configured, monitor at least these Prometheus metrics:
| Metric | Operational meaning |
|---|---|
maltrail_up == 0 |
No capture worker is running |
Increasing maltrail_capture_dropped_total |
The capture ring is dropping packets |
Increasing maltrail_local_log_errors_total |
Events were produced but could not be written locally |
Increasing maltrail_remote_log_errors_total |
Events could not be delivered to a remote sink; with DISABLE_LOCAL_LOG_STORAGE they are lost |
maltrail_trail_generation not advancing |
The active trail set is not being refreshed |
maltrail_log_dir_free_bytes |
Remaining capacity for local event storage |
Increasing maltrail_state_saturations_total |
A heuristic state limit was reached |
Increasing maltrail_throttle_evictions_total |
The event-throttle table is at its cap, so events are aggregated earlier than configured |
State saturation affects the corresponding heuristic; exact trail matching remains active.
Send SIGHUP or use systemctl reload maltrail-sensor to request a trail reload. Trail files
updated by another process are detected automatically and published to workers without restarting
the sensor.
The condensed observable store (USE_CONDENSED_STORAGE, meta.sqlite) supports the server's
novelty and retro-hunt views. The per-day event-log sidecar index (USE_EVENT_INDEX,
LOG_DIR/index/*.sqlite, roughly twice the log size on disk) is what makes /counts exact and
/hunt fast; it is maintained incrementally from the logs themselves and can be rebuilt with
server.py --rebuild-index. Compatibility with the retired sensor is documented in
sensor/docs/COMPATIBILITY.md.
Event retention
Maltrail does not rotate or delete event logs. Operators are responsible for defining retention, archival, and deletion according to storage requirements and organizational policy.
Recommended practices:
- Send the durable event copy to a remote Maltrail server or SIEM with
LOG_SERVER,SYSLOG_SERVER, orLOGSTASH_SERVER. - Alert on
maltrail_log_dir_free_byteswith enough headroom for the expected event rate. - Rotate, archive, or remove local daily logs using external tooling.
- Keep files needed by the reporting interface uncompressed in
LOG_DIR; archive compressed files elsewhere.
When the log filesystem is full, the sensor cannot append events. Event logs may also contain IP addresses and domains that are regulated as personal data in some jurisdictions; retention policy should account for the applicable requirements.
Synthetic traffic
To check that detection and the dashboard both still work, without waiting for real traffic:
python3 server.py --detect-test # assert every detection fires, then exit
python3 server.py --detect-test --keep DIR --serve # ...and keep the events, serving them on :8338
--keep also replays sensor/tests/corpus/ into the same log and prints which of the shapes the
dashboard renders differently have an event behind them, so a missing icon, colour or glyph is
visible rather than assumed. Timestamps are shifted so the newest day is today. A sensor binary is
required (cargo build --release --manifest-path sensor/Cargo.toml).
The public demo's data is regenerated from such a run:
python3 sensor/tools/gen_demo_js.py --from DIR/logs # tops up html/js/demo.js
Documentation
| Document | Contents |
|---|---|
sensor/docs/INSTALL.md |
Installation, privileges, configuration, and troubleshooting |
sensor/docs/ARCHITECTURE.md |
Sensor internals and data flow |
sensor/docs/COMPATIBILITY.md |
Deliberate differences from the retired Python sensor |
sensor/docs/REPORT.md |
Measurements, profiles, and test results |
sensor/docs/ROADMAP.md |
Open sensor work |
SekuriPy Labs |
Engineering notes, benchmarks and write-ups |
Contributing
Trail additions, feed maintenance, bug reports, documentation, and sensor improvements are welcome. Trail submissions should include a reliable source and should use the narrowest appropriate classification.
Run the relevant checks before submitting code. The complete sensor gate is:
bash sensor/tools/check.sh
It runs formatting, Clippy with warnings denied, and the debug and release test suites. Run the Python server suite with:
bash tests/run.sh python3
The Windows build can be exercised from Linux, which is where its bugs have been found:
sh sensor/tools/check_windows.sh
It cross-compiles the sensor with mingw-w64, extracts Npcap's userspace library from its installer
(an NSIS archive, so nothing is installed), and runs the result under Wine — the whole unit suite,
-T against the shipped configuration, the pcap corpus compared byte for byte against the native
binary, and the server answering /ping under a Windows Python. Live capture is the one thing it
cannot cover; that needs Npcap's kernel driver and a real Windows machine. Prerequisites are
gcc-mingw-w64-x86-64, wine, and p7zip-full.
Project
License
TL;DR: Maltrail is MIT-licensed, but the Maltrail Trails dataset has separate terms. Independent IOC lookup/reference is fine; systematic use of Trails as an intelligence source in a commercial product or service requires permission/licensing.
Maltrail is distributed under the MIT License. See LICENSE.
That is the engine. The static trail set is separate work under separate terms: free for internal
defensive use, research and teaching, but a commercial product, service, MSSP or MDR offering, or a
redistributed feed needs a licence. An MIT engine does not make the content free to sell — see
LICENSE.md in
stamparm/trails before shipping it in something you charge
for.
Maintainers
- Miroslav Stampar (@stamparm)
- Mikhail Kasimov (@MikhailKasimov)
Sponsors
Presentations and publications
- 47th TF-CSIRT Meeting, Prague, 2016 (slides)
- Detect attacks on your network with Maltrail, Linux Magazine, 2022 (article)
- Best Cyber Threat Intelligence Feeds, Silent Push, 2022 (review)
- Research on Network Malicious Traffic Detection System Based on Maltrail, Nanotechnology Perceptions, 2024 (paper)
Third-party integrations
- FreeBSD Port
- OPNsense Gateway Plugin
- D4 Project
- BlackArch Linux
- Validin
- Maltrail Add-on for Splunk
- Maltrail decoder and rules for Wazuh
- GScan (trails only)
- MalwareWorld (trails only)
- oisd domain blocklist (trails only)
- NextDNS (trails only)
- NoTracking (trails only)
- OWASP Mobile Audit (trails only)
- Mobile Security Framework MobSF (trails only)
- pfBlockerNG-devel (trails only)
- Sansec eComscan (trails only)
- Palo Alto Networks Cortex XSOAR (trail connector)
Acknowledgements
- Thomas Kristner
- Eduardo Arcusa Les
- James Lay
- Ladislav Baco (@laciKE)
- John Kristoff (@jtkdpu)
- Michael Münz (@mimugmail)
- David Brush
- @Godwottery
- Chris Wild (@briskets)
- Keith Irwin (@ki9us)
- Simon Szustkowski (@simonszu)