Stridetastic is an open-source monitoring and observability framework for Meshtastic® LoRa mesh networks. Born to fill the gap between hobbyist tooling and more professional-grade monitoring, it aims to help operators and administrators capture, inject, and visualize everything happening in their meshes. STRIDEtastic started as an undergraduate research project at Pontificia Universidad Católica de Chile as part of the IPre Program, under the supervision and guidance of Prof. Miguel Gutiérrez Gaitán from the IoT-UC Research Lab.

• Meshtastic networks offer inexpensive, long-range connectivity but lack centralized observability. Existing tools expose either basic maps, message logs, or limited stats, leaving analysts blind to topology, latency, channel usage, or security anomalies. STRIDEtastic aims to fill this gap.

For a complete, user-perspective inventory of shipped features, see docs/FEATURES.md.

STRIDEtastic combines passive mesh traffic observability with controlled active measurements. You can ingest Meshtastic traffic from multiple sources, investigate topology/links/nodes from a web dashboard, capture PCAP-NG for Wireshark analysis, and run one-shot/reactive/periodic publishing jobs for reachability and path measurements.

• Ingest from multiple interfaces: MQTT, serial radios, and TCP-connected nodes.
• Parse MeshPackets and decode common Meshtastic payload types (e.g., NodeInfo, Position, Telemetry, NeighborInfo, Routing).
• Optional decryption when keys are available: channel PSKs (AES) and PKI direct messages.

• Overview KPIs and activity for quick triage.
• Topology graph + geographic map for exploration and pivoting.
• Logical links view (bidirectional vs unidirectional, last activity, basic grouping).

• UI-driven capture sessions stored as PCAP-NG with per-frame annotations.
• Download captures and inspect them in Wireshark using the bundled Lua dissector.

• One-shot publishing: text, node identity, position, telemetry, traceroute, reachability probes.
• Reactive publishing based on configurable port/app triggers with safety limits.
• Periodic jobs (Celery Beat + workers) for recurring traceroutes/probes with status tracking.

Shipped dashboards in grafana/dashboards/:

• A1-network-health-kpi.json
• A3-geographic-coverage.json
• B4-node_telemetry.json
• B5-node_key_health.json
• C1-cve-2025-53627-dm-downgrade-attempts.json

• Django-Ninja REST API with JWT auth exposes nodes, channels, links, captures, interfaces, metrics, graph data, and publisher endpoints.
• Celery workers manage long-running sniffers, capture writers, and publishing jobs; Redis acts as the broker/cache.
• Comprehensive documentation (CLAUDE.md, strategy decks, SQL cookbooks) plus pytest suites covering services, controllers, crypto, packet parsing, and seeds.
• Docker Compose stack wires TimescaleDB, API, Redis, Celery worker/beat, Next.js, and Grafana with optional serial device passthrough.

compose.yaml
├── timescale_stridetastic     # PostgreSQL 17 + TimescaleDB
├── api_stridetastic           # Django API, Celery config, admin
├── redis_stridetastic         # Celery broker / caching layer
├── celery_stridetastic        # Worker (sniffer/publisher tasks)
├── celery_beat_stridetastic   # Scheduler for periodic jobs
├── web_stridetastic           # Next.js dashboard (pnpm build)
└── grafana_stridetastic       # Pre-provisioned dashboards

• Capture Layer – MQTT, Serial, TCP, and WebSocket interfaces feed the dispatcher.
• Service Layer – Sniffer, Publisher, Capture, PKI, and Virtual Node services coordinated by a singleton ServiceManager.
• Data Layer – TimescaleDB hypertables for packets/nodes/links + PCAP files on disk.
• Presentation Layer – Next.js dashboard for operations, Grafana for analytics, Django admin for power users, Wireshark for forensic drills.

api_stridetastic/       Django project, services, ingest pipeline, Celery tasks, tests
web_stridetastic/       Next.js 15 frontend (pnpm, React 19, Tailwind)
grafana/                Dashboards + provisioning configs
claude_docs/            Strategy, quick start, recommendations, SQL cookbook, checklist
docs/                   Academic report (`InformeIpreFinal1.pdf`) and related material
wireshark/              Custom Lua dissector for Meshtastic frames
timescale_stridetastic/ Host-mounted database volume
CLAUDE.md               Full-stack architecture digest for AI copilots
.env.template           Example .env file

Pre-built Docker images are available on GitHub Container Registry:

# Pull the API image
docker pull ghcr.io/0wulf/stridetastic-api:latest

# Pull the Web dashboard image
docker pull ghcr.io/0wulf/stridetastic-web:latest

Images are automatically built and published on every push to main and for version tags (v*).

1. Create your environment file:

   cp .env.template .env
   vim .env

2. Bring up TimescaleDB first:

   docker compose up -d timescale_stridetastic

3. Apply migrations and create an admin user:

   docker compose run --rm api_stridetastic python /app/manage.py migrate
   docker compose run --rm api_stridetastic python /app/manage.py createsuperuser

4. (Optional) Seed default nodes/channels/interfaces:

   docker compose up -d timescale_stridetastic
   docker compose run --rm api_stridetastic python /app/manage.py seeds

5. Launch the full stack:

   docker compose up -d

6. Visit the services:
   • Dashboard: http://localhost:3000
   • API & Swagger: http://localhost:8000 / http://localhost:8000/api/docs
   • Django admin: http://localhost:8000/admin
   • Grafana: http://localhost:3001 (default creds admin:admin)

1. Onboard Interfaces – Create MQTT, Serial, and/or TCP interfaces in the dashboard, enable them, and watch packets stream into TimescaleDB.
2. Start Captures – If you need to view the packets in Wireshark: Launch PCAP sessions from the UI for forensic investigations; download artifacts when complete and open them in Wireshark.
3. Instrument Publishing – For legitimate packet injection: configure virtual nodes and either fire single packets, enable reactive publishing (port-based), or schedule periodic traceroutes to profile paths.
4. Explore Dashboards – Use the Next.js console for operations and the Grafana pack for historical analysis, network topology graph, anomaly detection, SLA monitoring, and optimization insights.

• Ethics – Stridetastic is intended for authorized research, defensive testing, and academic experimentation. Obtain explicit permission before interacting with third-party meshes, respect local RF regulations, and follow responsible disclosure practices.
• Academic Reference – If you use this framework in publications, please cite the IPre report “STRIDEtastic: Framework de Observabilidad para Redes Meshtastic” (Pontificia Universidad Católica de Chile, 2025) and reference this repository.

• Academic guidance – Huge thanks to Prof. Miguel Gutiérrez Gaitán (PUC Chile) for supporting the original STRIDEtastic research vision, and to Maximiliano Militzer (Dyotson) for introducing me to the Meshtastic ecosystem.
• Community inspiration – The Meshtastic community and projects such as pdxlocations/Meshtastic-Python-Examples and cdanis/meshtastic-wireshark informed the capture tooling, publishing experiments, and dissector work included here.

• Start with CONTRIBUTING.md for workflows (local dev, testing, branching, PR expectations).
• Install and enable the pre-commit hooks before contributing: pip install pre-commit (inside your virtualenv), then run pre-commit install at the repo root. Run checks with pre-commit run --all-files.
• Our community standards live in CODE_OF_CONDUCT.md.
• Security reports should follow SECURITY.md.
• Architecture and deep dives: see CLAUDE.md and the claude_docs/ quick-start and strategy guides.

If you open a PR, keep it scoped, include tests for behavior changes, and attach screenshots for UI updates. Thank you for helping improve STRIDEtastic!

Stridetastic is distributed under the GNU General Public License v3.0. See LICENSE for details.

Keywords: Meshtastic, Observability, Latency, Security, STRIDE