Honeyurl

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

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ honeyurl-emit --version
honeyurl 0.1.0

$ honeyurl-emit --help
usage: honeyurl [-h] [--version] [--format {table,json}] {mint,scan} ...

Generate canary URLs/tokens and match trip events (defensive).

positional arguments:
  {mint,scan}
    mint                mint canary token(s)
    scan                match access records against registry

options:
  -h, --help            show this help message and exit
  --version             show program's version number and exit
  --format {table,json}

Blocks above are real honeyurl output — reproduce them from a clone.

Sample result format (illustrative values — run on your own data for real findings):

{
"timestamp": "2023-02-16T14:30:00Z",
"actor": {
"name": "John Doe"
},
"object": {
"type": "url",
"value": "https://example.com/vulnerable-page"
},
"finding": {
"id": "1234567890abcdef",
"category": "vulnerability",
"severity": "high",
"description": "A high-severity vulnerability was found on the webpage."
}
}

Usage — step by step

Defensive canary tokens.

1. Install:

   pip install honeyurl
   

2. Mint canary token(s) into a registry — the registry stores the HMAC secret and minted canaries:

   honeyurl mint --registry canaries.json \
     --base-url https://canary.example.net/t \
     --kind url --label "staging-readme" --count 1
   

   The secret can also come from --secret or $HONEYURL_SECRET; if no registry is given a random secret is printed to store safely.

3. Place the minted URL/token in the resource you want to watch (a doc, a config, a page), then collect your access log.

4. Scan access records (JSONL or plain log lines) against the registry for trips:

   honeyurl scan --registry canaries.json --records access.log
   

5. Alerting / CI — emit JSON and rely on the exit code (1 when critical/high trips are found, 0 otherwise):

   honeyurl --format json scan --registry canaries.json --records access.log | jq '.findings'
   

Contents

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

Why honeyurl?

one-shot canaries

honeyurl 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.

Features

• ✅ Mint Canary
• ✅ Verify Token
• ✅ Load Registry
• ✅ Save Registry
• ✅ Match Events
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

Quick start

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

Example

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

  2 findings · risk score 5 · 38ms

Architecture

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

Use it from any AI stack

honeyurl is interoperable with every popular way of using AI:

• MCP server — honeyurl mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)
• OpenAI-compatible / JSON — pipe honeyurl 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

How it compares

	Cognis honeyurl	canarytokens
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 canarytokens, re-framed the Cognis way. Missing a credit? Open a PR.

Integrations

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

Install — every way, every platform

pip install "git+https://github.com/cognis-digital/honeyurl.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/honeyurl.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/honeyurl.git" # uv
pip install cognis-honeyurl                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/honeyurl:latest --help        # Docker
brew install cognis-digital/tap/honeyurl                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/honeyurl/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/honeyurl	DEPLOY.md (AWS/Azure/GCP/k8s)

Related Cognis tools

• portfan — Summarize and diff nmap XML into prioritized, attackable findings
• subhunt — Aggregate & dedupe subdomain enumeration from multiple sources
• dirsight — Analyze web content-discovery output (ffuf/gobuster) into ranked endpoints
• jwtinspect — Decode JWTs and lint for alg=none, weak secrets, and missing claims
• corsaudit — Detect permissive/misconfigured CORS from headers or a config
• headerscan — Grade HTTP security headers (CSP/HSTS/XFO) A-F from a response dump

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

Contributing

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

⭐ If honeyurl 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 ([email protected]). See LICENSE.

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