Ttphunt

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

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ ttphunt-emit --version
ttphunt 0.1.0

$ ttphunt-emit --help
usage: ttphunt [-h] [--version] {hunt,rules} ...

Hunt MITRE ATT&CK techniques across logs with a rule pack.

positional arguments:
  {hunt,rules}
    hunt        Scan a log file for ATT&CK techniques.
    rules       List rules in the active pack.

options:
  -h, --help    show this help message and exit
  --version     show program's version number and exit

$ ttphunt-emit rules
ttphunt: 12 rule(s)
  [HIGH    ] T1059.001    ttp-powershell-encoded           PowerShell Encoded Command
  [HIGH    ] T1059.001    ttp-powershell-download-cradle   PowerShell Download Cradle
  [HIGH    ] T1105        ttp-certutil-download            Certutil Used to Download/Decode
  [MEDIUM  ] T1047        ttp-wmic-process-call            WMIC Remote/Local Process Creation
  [CRITICAL] T1490        ttp-bcdedit-recovery-disable     Inhibit System Recovery (bcdedit/vssadmin/wbadmin)
  [MEDIUM  ] T1547.001    ttp-registry-run-key             Run Key Persistence via reg.exe
  [MEDIUM  ] T1053.005    ttp-scheduled-task-create        Scheduled Task Creation
  [HIGH    ] T1218.005    ttp-mshta-execution              Mshta Remote Script Execution
  [MEDIUM  ] T1218.011    ttp-rundll32-suspicious          Rundll32 Proxy Execution
  [HIGH    ] T1070.001    ttp-clear-event-logs             Windows Event Log Cleared
  [MEDIUM  ] T1136.001    ttp-net-user-add                 Local Account Created via net user
  [LOW     ] T1110        ttp-failed-logon-burst           Failed Logon (Brute Force Candidate)

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

Usage — step by step

1. Install (Python 3.9+):

   pip install ttphunt
   

2. Hunt ATT&CK techniques in a log file (JSON array or JSONL) using the built-in rule pack:

   ttphunt hunt auth.jsonl
   

3. Tune the hunt. Raise the floor with --min-severity, scope to specific techniques, or supply your own rule pack:

   ttphunt hunt auth.jsonl --min-severity high -t T1110 -t T1078 -r my_rules.json
   

4. Read or export the output. Emit JSON for tooling, or write an HTML report to a file:

   ttphunt hunt auth.jsonl --format json -o findings.json
   ttphunt hunt auth.jsonl --format html -o report.html
   

5. Inspect the rules in CI. List the active rule pack to verify coverage as part of a pipeline:

   ttphunt rules --format json | jq '.[].technique'
   

Contents

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

Why ttphunt?

Hunt MITRE ATT&CK techniques across logs with a rule pack — without standing up heavyweight infrastructure.

ttphunt 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

• ✅ Load Events
• ✅ Load Events From Text
• ✅ Load Rules
• ✅ Hunt
• ✅ Summarize
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

Quick start

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

Example

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

  2 findings · risk score 5 · 38ms

Architecture

flowchart LR
  IN[input] --> P[ttphunt<br/>analyze + score]
  P --> OUT[report]

Use it from any AI stack

ttphunt is interoperable with every popular way of using AI:

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

Integrations

Pipes into your stack: SARIF for code-scanning, JSON for anything, an MCP server (ttphunt 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/ttphunt.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/ttphunt.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/ttphunt.git" # uv
pip install cognis-ttphunt                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/ttphunt:latest --help        # Docker
brew install cognis-digital/tap/ttphunt                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/ttphunt/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/ttphunt	DEPLOY.md (AWS/Azure/GCP/k8s)

Related Cognis tools

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 ttphunt 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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