GEOLENS

Image geolocation toolkit — EXIF, sun-shadow, OCR, reverse-search

OSINT / SIGINT — open-source intelligence collection and correlation.

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

Watch the walkthrough

A full narrated tour — setup, the tool in action, and every demo scenario:

▶ Watch the walkthrough (MP4)

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ geolens-emit --version
geolens 0.2.0

$ geolens-emit --help
usage: geolens [-h] [--version] [--format {table,json,geojson,stix}]
               {exif,sun,shadow,reverse} ...

GEOLENS — image geolocation toolkit (EXIF, sun/shadow, reverse-search).

positional arguments:
  {exif,sun,shadow,reverse}
    exif                extract EXIF/GPS + reverse-search hints from an image
    sun                 compute sun azimuth/elevation for a location & time
    shadow              estimate latitude from object height & shadow length
    reverse             build reverse-image / keyword search URLs

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

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

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

{
"findings": [
    {
        "id": "1234567890",
        "title": "Suspicious Network Traffic",
        "description": "Unusual network traffic detected from IP 192.168.1.100",
        "mitre_attack_id": ["T1047"],
        "created_at": "2023-02-15T14:30:00Z"
    },
    {
        "id": "2345678901",
        "title": "Malware Detection",
        "description": "Malware detected on host 192.168.1.101",
        "mitre_attack_id": ["T1059"],
        "created_at": "2023-02-15T14:35:00Z"
    }
]
}

Usage — step by step

1. Install (Python 3.9+):

   pip install geolens

2. Extract EXIF/GPS and reverse-search hints from a JPEG:

   geolens exif photo.jpg --url https://example.com/photo.jpg

3. Cross-check the scene geometry: compute the sun's azimuth/elevation for a candidate location and time, or estimate latitude from a shadow:

   geolens sun --lat 38.89 --lon -77.03 --when 2026-06-21T17:00:00Z
   geolens shadow --height 2.0 --shadow 1.4 --when 2026-06-21T17:00:00Z

4. Build reverse-image / keyword search URLs to chase the source:

   geolens reverse --url https://example.com/photo.jpg --keyword "harbor" --keyword "crane"

5. Read the output: tables print flattened key value rows; add --format json (a top-level flag) for piping. geolens exif exits 2 when the image has no EXIF, which lets you branch in a script:

   geolens --format json exif photo.jpg > exif.json || echo "no EXIF present"

6. Export the geolocation for maps / threat-intel platforms — native, zero-dep (note --format is a top-level flag, before the subcommand):

   geolens --format geojson exif photo.jpg > fix.geojson   # Leaflet/Mapbox/QGIS/kepler
   geolens --format stix    exif photo.jpg > fix.json       # STIX 2.1 location bundle for OpenCTI/TIPs

   GeoJSON emits the recovered GPS fix as a point (camera make/model + OSM link as properties); STIX wraps a location + observed-data + note in a report. Try it on the bundled sample: demos/01-basic/sample_geotagged.jpg.

Contents

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

Why geolens?

Image geolocation toolkit — EXIF, sun-shadow, OCR, reverse-search — without standing up heavyweight infrastructure.

geolens 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

• ✅ Extract Exif
• ✅ Gps From Exif
• ✅ Sun Position
• ✅ Shadow Bearing To Azimuth
• ✅ Estimate Latitude From Shadow
• ✅ Reverse Search Urls
• ✅ Analyze Image
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

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Quick start

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

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Example

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

  2 findings · risk score 5 · 38ms

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Architecture

flowchart LR
  IN[image / coordinates] --> P[geolens<br/>extract + geolocate]
  P --> OUT[location estimate]

Loading

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Demos

Five runnable, offline scenarios in demos/ — each for a different audience and built on the real geolens API (no fabricated output). Every scenario reads a bundled sample image or synthesizes real EXIF bytes in memory, then prints narrated results and exits 0.

# Windows: set PYTHONUTF8=1 first (cp1252 console)
python demos/run_all.py                       # all five, end to end
python demos/02_journalist_verification.py    # or just one

#	Scenario	Audience	What it shows
1	01_osint_exif_triage.py	OSINT analysts	EXIF/GPS off the bytes + map link + reverse-image search leads
2	02_journalist_verification.py	Journalists / verification	Test a "place & time" claim against the real solar azimuth/elevation
3	03_le_batch_triage.py	Law enforcement / IR	Mixed seized folder: who is geotagged vs scrubbed, + a STIX bundle
4	04_researcher_shadow_geolocation.py	Researchers	Recover latitude from a stick and its shadow (the "shadow stick")
5	05_geojson_stix_export.py	Platform / SOC engineers	One fix → GeoJSON (maps) + STIX 2.1 (TIP), graceful with no GPS

flowchart LR
  img[JPEG bytes] --> exif[EXIF / GPS parser]
  coords[lat / lon / time] --> sun[solar position]
  obs[height + shadow] --> shadow[shadow geolocation]
  exif --> out[analyze_image]
  out --> fmt[table · json · GeoJSON · STIX 2.1]

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Full writeup: docs/DEMOS.md · architecture: docs/ARCHITECTURE.md.

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Use it from any AI stack

geolens is interoperable with every popular way of using AI:

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

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Related Cognis tools

• personagraph — Identity resolution dossier — username/email/phone cross-platform
• maritimeint — AIS vessel tracking & sanctions-evasion anomaly detection
• corpmap — Corporate structure & beneficial-ownership mapper
• cryptotrace — Free-tier blockchain investigator — ETH/BTC clustering + sanctions xref
• darkmirror — Surface-web mirror of public Tor leak-site index for brand monitoring

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 geolens 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}