MODPOT

Spin up a high-interaction Modbus/DNP3 ICS honeypot that logs attacker register reads/writes as structured JSON.

IoT / OT / Embedded — firmware, buses, and device security.

pip install cognis-modpot
modpot scan .            # → prioritized findings in seconds

Usage — step by step

modpot is a standard-library Modbus TCP honeypot that decodes and classifies attacker register reads/writes as JSON threat events. Console script: modpot.

1. Install:

   pipx install modpot     # or: pip install modpot

2. Analyze a captured hex log of Modbus frames and print a classified threat table (the --format flag is global, before the subcommand):

   modpot analyze capture.hexlog
   cat capture.hexlog | modpot analyze -        # read frames from stdin

   Exit 1 = at least one high-severity event (write/control/recon), 0 = none.
3. Filter to serious events and emit JSON for a SIEM:

   modpot --format json analyze capture.hexlog --min-severity high | jq '.[].reasons'

4. Run a live honeypot listener (no root needed on a high port); every request is logged as a JSON event on stdout:

   modpot serve --host 0.0.0.0 --port 5020

5. Use it as a CI / alerting gate over a capture — fail when control-plane writes appear:

   modpot analyze capture.hexlog --min-severity high || echo "high-severity Modbus activity — alerting"

Contents

• Why modpot? · Features · Quick start · Example · Architecture · AI stack · How it compares · Integrations · Install anywhere · Related · Contributing

Why modpot?

OT threat-intel content engine — drop it on a VPS, share the 'someone tried to open my fake water-treatment valve' logs. ICS honeypot captures get major infosec-Twitter traction.

modpot is single-purpose, scriptable, and self-hostable: point it at a target, get prioritized results in the format your workflow already speaks (table · JSON · SARIF), gate CI on it, and let agents drive it over MCP.

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Features

• ✅ Parse Frame
• ✅ Build Response
• ✅ Classify Event
• ✅ Frame To Event
• ✅ Iter Frames From Hexlog
• ✅ Analyze Capture
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

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Quick start

pip install cognis-modpot
modpot --version
modpot scan .                       # scan current project
modpot scan . --format json         # machine-readable
modpot scan . --fail-on high        # CI gate (non-zero exit)

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Example

$ modpot scan .
  [HIGH    ] MOD-001  example finding             (./src/app.py)
  [MEDIUM  ] MOD-002  another signal              (./config.yaml)

  2 findings · risk score 5 · 38ms

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Architecture

flowchart LR
  IN[attacker traffic] --> P[modpot<br/>capture]
  P --> OUT[alerts + indicators]

Loading

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Use it from any AI stack

modpot is interoperable with every popular way of using AI:

• MCP server — modpot mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)
• OpenAI-compatible / JSON — pipe modpot scan . --format json into any agent or LLM
• LangChain · CrewAI · AutoGen · LlamaIndex — wrap the CLI/JSON as a tool in one line
• CI / scripts — exit codes + SARIF for non-AI pipelines

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How it compares

	Cognis modpot	conpot
Self-hostable, no account	✅	varies
Single command, zero config	✅	⚠️
JSON + SARIF for CI	✅	varies
MCP-native (AI agents)	✅	❌
Polyglot ports (JS/Go/Rust)	✅	❌
Open license	✅ COCL	varies

Built in the spirit of conpot, re-framed the Cognis way. Missing a credit? Open a PR.

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Integrations

Pipes into your stack: SARIF for code-scanning, JSON for anything, an MCP server (modpot mcp) for AI agents, and a webhook forwarder for SIEM/Slack/Jira. See docs/INTEGRATIONS.md.

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Install — every way, every platform

pip install "git+https://github.com/cognis-digital/modpot.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/modpot.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/modpot.git" # uv
pip install cognis-modpot                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/modpot:latest --help        # Docker
brew install cognis-digital/tap/modpot                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/modpot/main/install.sh | sh

Linux	macOS	Windows	Docker	Cloud
scripts/setup-linux.sh	scripts/setup-macos.sh	scripts/setup-windows.ps1	docker run ghcr.io/cognis-digital/modpot	DEPLOY.md (AWS/Azure/GCP/k8s)

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Related Cognis tools

• fwxray — Diff two firmware images and surface exactly what changed: new binaries, flipped config flags, added certs, and shifted entropy regions.
• canzap — Replay, fuzz, and assert on CAN bus traffic from a .pcap or SocketCAN interface with a tiny YAML DSL.
• sbomb — Generate a CycloneDX SBOM directly from an unpacked firmware root filesystem and flag components with known CVEs and EOL kernels.
• mqttspy — Passively map an MQTT broker: enumerate topics, detect unauthenticated writes, spot PII/secrets in payloads, and emit a risk report.
• uefiscan — Audit UEFI firmware dumps for missing Secure Boot keys, unsigned modules, S3 boot-script vulns, and known SMM threats.
• keyhunt — Scan firmware blobs and filesystem dumps for hardcoded private keys, API tokens, default creds, and weak RSA/ECC material.

Explore the suite → 🗂️ all 170+ tools · ⭐ awesome-cognis · 🔗 cognis-sources · 🤖 uncensored-fleet · 🧠 engram

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Contributing

PRs, new rules, and demo scenarios are welcome under the collaboration-pull model — see CONTRIBUTING.md and SECURITY.md.

⭐ If modpot saved you time, star it — it genuinely helps others find it.

Interoperability

{} composes with the 300+ tool Cognis suite — JSON in/out and a shared OpenAI-compatible /v1 backbone. See INTEROP.md for the suite map, composition patterns, and reference stacks.

License

Source-available under the Cognis Open Collaboration License (COCL) v1.0 — free for personal, internal-evaluation, research, and educational use; commercial / production use requires a license (licensing@cognis.digital). See LICENSE.

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