TRACKBLOCK

Family phone stalkerware audit — MVT-class iOS/Android forensics

Privacy / Personal — put individuals back in control of their data.

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

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ trackblock-emit --version
trackblock 0.1.0

$ trackblock-emit --help
usage: trackblock [-h] [--version] [--format {table,json}] {audit} ...

Family phone stalkerware audit (MVT-class forensics). Scans an offline
evidence dump for spyware indicators.

positional arguments:
  {audit}
    audit               audit an evidence directory for stalkerware

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

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

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

{
"findings": [
    {
        "id": "123456",
        "title": "Suspicious Network Traffic",
        "description": "Potential malicious activity detected on port 443.",
        "created_at": "2023-02-15T14:30:00Z",
        "updated_at": "2023-02-15T14:30:01Z"
    },
    {
        "id": "789012",
        "title": "Unusual File Access",
        "description": "User accessed a file with suspicious permissions.",
        "created_at": "2023-02-16T10:45:00Z",
        "updated_at": "2023-02-16T10:45:01Z"
    }
]
}

Usage — step by step

1. Install the CLI (console script trackblock):

   pip install cognis-trackblock

2. Audit an evidence directory — point audit at an extracted (offline) phone evidence dump; it scans for stalkerware IOCs and prints a verdict + risk score:

   trackblock audit ./evidence_dump

3. Emit JSON for archival or downstream tooling:

   trackblock audit ./evidence_dump --format json > report.json

4. Read the result — the report carries verdict (clean/review/suspicious/compromised), risk_score (0–100) and a sorted detections list; the command exits 0 only when the verdict is clean (1 otherwise, 2 on a bad evidence dir):

   trackblock audit ./evidence_dump --format json | jq '.verdict, .risk_score'

5. Automate as a gate — run it in a scheduled audit and act on the exit code:

   trackblock audit ./evidence_dump || echo "device NOT clean — investigate"

Contents

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

Why trackblock?

Family phone stalkerware audit — MVT-class iOS/Android forensics — without standing up heavyweight infrastructure.

trackblock 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

• ✅ Load Evidence
• ✅ Audit Records
• ✅ Audit Directory
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

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Quick start

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

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Example

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

  2 findings · risk score 5 · 38ms

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Architecture

flowchart LR
  IN[disk / memory artifact] --> P[trackblock<br/>parse]
  P --> OUT[timeline + IOCs]

Loading

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Use it from any AI stack

trackblock is interoperable with every popular way of using AI:

• MCP server — trackblock mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)
• OpenAI-compatible / JSON — pipe trackblock 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 trackblock	mvt-project
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 mvt-project/mvt, 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 (trackblock 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/trackblock.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/trackblock.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/trackblock.git" # uv
pip install cognis-trackblock                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/trackblock:latest --help        # Docker
brew install cognis-digital/tap/trackblock                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/trackblock/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/trackblock	DEPLOY.md (AWS/Azure/GCP/k8s)

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Related Cognis tools

• recall — Privacy-first local RAG over personal data — encrypted, audit-logged
• optout — Automated data-broker opt-out engine — top 50 brokers, CCPA/GDPR letters
• vaultmap — Personal asset & account inventory — estate-planning-grade encrypted
• breachwatch — Personal breach aggregator — HIBP + DeHashed + stealer-log triage
• piicomb — Local PII discovery in your own files — SSN/CC/passport/DL/email/phone/DOB
• privacyshell — Hardened browser profile generator — Firefox / LibreWolf / Brave

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 trackblock 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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_{Cognis Digital · one of 170+ tools in the Cognis Neural Suite · Making Tomorrow Better Today}