Open Intelligence Lab is an ethical OSINT research platform focused on public‑security intelligence representation, graph‑based threat modeling, and explainable risk analytics.
It provides a clean, modular environment for researchers, analysts, and engineers who want to explore open‑source intelligence signals without compromising privacy or ethics.
Security intelligence is often opaque, proprietary, and difficult to interpret.
This project aims to change that by offering:
- Transparent intelligence modeling
- Human‑readable explanations
- Graph‑based threat representation
- Ethical OSINT datasets
- Research‑friendly tooling
- Public data only — no private or sensitive information
- Explainability first — every risk score must be interpretable
- Modular architecture — easy to extend or replace
- Research transparency — datasets and logic are fully visible
- Ethical OSINT — aligned with academic and open‑source norms
Below is a high‑level overview of how the system works.
flowchart TD
%% ===========================
%% DATASETS
%% ===========================
subgraph Datasets
TE[threat_entities.json]
AP[attack_patterns.json]
RL[relations.json]
end
%% ===========================
%% CORE ENGINE
%% ===========================
subgraph CoreEngine
GB[graph_builder.py]
RA[risk_analyzer.py]
EX[explainability.py]
end
%% ===========================
%% VISUALIZATION
%% ===========================
subgraph Visualization
GV[graph_visualizer.py]
DB[dashboards]
end
%% ===========================
%% API LAYER
%% ===========================
subgraph API
IA[intelligence/router.py]
end
%% ===========================
%% RESEARCH OUTPUT
%% ===========================
subgraph Research
RD[research_docs/]
end
%% DATA → GRAPH
TE --> GB
AP --> GB
RL --> GB
%% GRAPH → ANALYSIS
GB --> RA
RA --> EX
%% GRAPH → VISUALIZATION
GB --> GV
RA --> GV
EX --> GV
%% ENGINE → API
GB --> IA
RA --> IA
EX --> IA
%% API → RESEARCH
IA --> RD