Validate OTA update packages end-to-end: signature chains, rollback protection, anti-downgrade counters, and delta-patch integrity.
IoT / OT / Embedded — firmware, buses, and device security.
pip install cognis-otaverify
otaverify scan . # → prioritized findings in seconds- Why otaverify? · Features · Quick start · Example · Architecture · AI stack · How it compares · Integrations · Install anywhere · Related · Contributing
Uptane/automotive OTA compliance hook — one command in your release pipeline that blocks shipping an unsigned or downgradeable update. Ties directly to UN R155/R156 cyber regs.
otaverify 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.
- ✅ Load Json
- ✅ Canonical Bytes
- ✅ Verify Manifest
- ✅ Check Anti Downgrade
- ✅ Check Payloads
- ✅ Verify Package
- ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
- ✅ Ports in Python, JavaScript, Go, and Rust (
ports/)
pip install cognis-otaverify
otaverify --version
otaverify scan . # scan current project
otaverify scan . --format json # machine-readable
otaverify scan . --fail-on high # CI gate (non-zero exit)$ otaverify scan .
[HIGH ] OTA-001 example finding (./src/app.py)
[MEDIUM ] OTA-002 another signal (./config.yaml)
2 findings · risk score 5 · 38ms
flowchart LR
A[Input: file / dir / API] --> B[Collectors]
B --> C[Rules / Analyzers]
C --> D[Scorer]
D --> E{Reporters}
E --> F[Table]
E --> G[JSON / SARIF]
E --> H[MCP tool -. drives .-> AI agents]
otaverify is interoperable with every popular way of using AI:
- MCP server —
otaverify mcp(Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet) - OpenAI-compatible / JSON — pipe
otaverify scan . --format jsoninto 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
| Cognis otaverify | TUF | |
|---|---|---|
| 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 TUF / Uptane + Mender, re-framed the Cognis way. Missing a credit? Open a PR.
Pipes into your stack: SARIF for code-scanning, JSON for anything, an MCP server (otaverify mcp) for AI agents, and a webhook forwarder for SIEM/Slack/Jira. See docs/INTEGRATIONS.md.
pip install "git+https://github.com/cognis-digital/otaverify.git" # pip (works today)
pipx install "git+https://github.com/cognis-digital/otaverify.git" # isolated CLI
uv tool install "git+https://github.com/cognis-digital/otaverify.git" # uv
pip install cognis-otaverify # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/otaverify:latest --help # Docker
brew install cognis-digital/tap/otaverify # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/otaverify/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/otaverify |
DEPLOY.md (AWS/Azure/GCP/k8s) |
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.modpot— Spin up a high-interaction Modbus/DNP3 ICS honeypot that logs attacker register reads/writes as structured JSON.
Explore the suite → 🗂️ all 170+ tools · ⭐ awesome-cognis · 🔗 cognis-sources · 🤖 uncensored-fleet · 🧠 hermes
PRs, new rules, and demo scenarios are welcome under the collaboration-pull model — see CONTRIBUTING.md and SECURITY.md.
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.