Silinosic-X v11.2.0
Theme: Ember
OSINT orchestration, media intelligence, and Reporter-grade artifacts for profile, surface, fusion, and OCR-led investigations.
Silinosic-X is a Python intelligence framework for authorized OSINT work. It combines profile reconnaissance, domain-surface analysis, fusion scoring, public-media reconnaissance, and OCR image scanning into one runtime with plugins, filters, engine policies, and categorized artifacts.
What v11.2.0 includes
- Reporter is now the primary reporting layer for HTML and CLI summaries.
- Media reconnaissance and OCR image scanning are first-class lanes instead of side notes.
- HTML artifacts are organized as case views with graphs, categorized sections, extension drill-downs, vulnerability context, and a closing
Reporter Brief. - The docs tree and website are aligned to the current runtime instead of old release-planning notes.
Recent runtime additions
- Platform intelligence now loads from an expanded manifest with
91validated platforms, including major high-value public OSINT surfaces. - Profile scanning can emit live pipeline events as platforms resolve, allowing downstream enrichment to start before the full scan ends.
- Live enrichment now hunts contact and credential signals from
FOUNDprofile rows during the scan itself. - A persistent SQLite knowledge base tracks targets, found profiles, contact signals, fingerprints, and risk indicators across runs.
silinosic-x doctornow reports engine health, knowledge-base status, and Docker runtime status.- Docker is now a first-class execution path through
--docker, with runtime detection, image build support, and mounted output persistence. - Tor runtime management now has a higher-level setup layer that can deploy
torrc, check readiness, and coordinate startup.
Core workflows
profilescans usernames and public profiles across platform manifests.surfaceanalyzes domain exposure, transport posture, and surface intelligence.fusioncorrelates profile and surface evidence into scored intelligence.orchestrateruns the policy-led orchestration pipeline directly.ocrruns dedicated OCR image scanning across local paths and remote URLs.- media plugins add public image/video/post-text reconnaissance and stego-style triage.
Install, run, import
pip install silinosic-x
silinosic-x
silinosic-x doctor
import silinosic_x
print(silinosic_x.__version__)
Note: the Python-PIP package is not available right now cause changing repo name...
From source:
git clone https://github.com/voltsparx/Silinosic-X.git
cd Silinosic-X
pip install -e .
silinosic-x --help
Optional extras:
pip install ".[reports]"
pip install ".[ocr]"
pytesseract is a Python wrapper, but OCR still depends on a reachable tesseract binary. Silinosic-X now reports which OCR/image backends were actually available during the run, and silinosic-x doctor gives a quick local diagnostic pass for OCR, Tor, Reporter backends, output settings, and runtime inventory.
Docker runtime:
silinosic-x --docker
silinosic-x prompt --docker
silinosic-x profile alice --docker
silinosic-x surface example.com --docker
silinosic-x prompt --docker --tor
On first use, Silinosic-X can check Docker, install it when supported and approved, build the image, and then launch the requested command inside the container.
Quick examples
silinosic-x profile alice --html
silinosic-x surface example.com --html
silinosic-x fusion alice example.com --html
silinosic-x ocr ./captures/poster.png --url https://example.com/image.png --html
silinosic-x profile alice --plugin media_recon_engine --plugin post_signal_intel --plugin stego_signal_probe --html
silinosic-x prompt
silinosic-x prompt --docker
silinosic-x doctor
Reporter outputs
Silinosic-X writes artifacts under output/ and can emit:
- CLI summaries
- JSON payloads
- CSV exports plus companion CSV slices
- HTML Reporter case views
- SQLite case stores
- DOCX case documents
- PDF case documents
- run logs and framework logs
Reporter is designed to make the result easier to triage by grouping identity findings, reliability issues, correlation, vulnerabilities, plugin/filter signals, OCR/media lanes, and the final Reporter Brief.
Recent report/runtime improvements also include:
- live enrichment sections in HTML output when profile pipeline signals are captured
- relationship and graph-backed sections for fusion-style analysis
- persistent knowledge-base storage at
output/silinosic_x_kb.db - richer
doctorvisibility for OCR, Tor, Docker, engines, and output/runtime state
In prompt mode, attachables can be configured as session defaults with commands like:
enable plugin threat_conductor
enable filter contact_canonicalizer
enable module source-pack-01-module-1
config
Documentation
- Docs Index
- Operator Guide
- Architecture
- Extensions
- Media Intelligence
- Reporter
- Development
- Docker Guide
- Website
Website and Pages
Primary Pages URL:
https://voltsparx.github.io/Silinosic-X/
If that direct URL shows GitHub's "site not found" page, the usual cause is not the website files themselves. It usually means GitHub Pages is not currently serving the project site yet. For this repository, Pages must be enabled with GitHub Actions as the source, and the Silinosic-X Pages workflow must complete successfully on main or master.
Safety
- Legal and authorized use only
- Respect platform terms, privacy, and local law
- Do not use Silinosic-X for stalking, harassment, or unauthorized surveillance
Developer notes
Useful local checks:
python -m pytest -q
python -m ruff check .
python -m mypy
python -m compileall -q core filters modules plugins tests silinosic-x.py
python scripts/smoke_suite.py
silinosic-x doctor
silinosic-x --help
Core package naming:
- package install name:
silinosic-x - CLI entrypoint:
silinosic-x - Python import path:
silinosic_x
Author
- Author: voltsparx
- Contact: voltsparx@gmail.com
- Repository: https://github.com/voltsparx/Silinosic-X
Metadata
Release files for silinosic-x 11.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| silinosic_x-11.2.0.tar.gz | 523.8 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| silinosic_x-11.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.2 MB
Release files / silinosic_x-11.2.0.tar.gz
| Download URL | silinosic_x-11.2.0.tar.gz |
|---|---|
| Size | 523.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.7
|
Release files / silinosic_x-11.2.0-py3-none-any.whl
| Download URL | silinosic_x-11.2.0-py3-none-any.whl |
|---|---|
| Size | 654.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.7
|
Security for silinosic-x 11.2.0
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