ni5arga/sightline: OSINT Search Engine for Infrastructure Mapping

ni5arga/sightline: OSINT Search Engine for Infrastructure Mapping

Developers and security researchers need reliable ways to discover and analyze physical-world assets without proprietary geospatial tools. OpenStreetMap contains vast infrastructure data, but querying it effectively requires specialized knowledge of Overpass QL and OSM tagging schemes. ni5arga/sightline bridges this gap as an open-source OSINT search engine that turns natural language queries into structured infrastructure intelligence. With 501 GitHub stars and an MIT license, this TypeScript-based platform makes geospatial asset discovery accessible through both intuitive search syntax and structured parameters.

What is ni5arga/sightline?

ni5arga/sightline is a geospatial infrastructure intelligence platform maintained by ni5arga. It falls into the category of open-source intelligence (OSINT) tooling specifically designed for discovering and analyzing physical-world assets using OpenStreetMap data.

The project addresses a genuine technical need: OSM's Overpass API is powerful but requires expertise in its query language. Sightline abstracts this complexity through a natural language processing layer and a clean web interface built with Next.js^{↗ Bright Coding Blog}, React^{↗ Bright Coding Blog}, and Leaflet.js. Users can search across 30+ categories covering more than 200 searchable infrastructure types without writing raw Overpass queries.

The repository shows healthy community engagement with 65 forks and active maintenance (last commit dated 2026-05-10). Being MIT-licensed, it allows commercial and research use with minimal restriction. The stack is modern and familiar to frontend developers: TypeScript throughout, with a clear separation between the Next.js frontend and modular backend services handling parsing, geocoding, caching, and OSM query construction.

Sightline's relevance extends across multiple domains. Security researchers use it for infrastructure reconnaissance. Journalists and investigators verify facility locations. Urban planners and data scientists access standardized geospatial datasets. The tool's value proposition is democratizing access to OSM infrastructure data without requiring domain expertise in GIS systems or OSM tagging conventions.

Key Features

Natural Language Query Processing

The platform's standout feature is its NLP engine (parser.ts) that converts plain English into structured OSM queries. Searches like "telecom towers in karnataka" or "power plants near mumbai" are parsed into valid Overpass API calls without user intervention. This dramatically lowers the barrier for non-specialists.

Structured Query Syntax

For precise control, Sightline supports parameterized searches: type:telecom operator:airtel region:karnataka or type:data_center operator:google. Parameters include type, operator, region, country, near, and radius with kilometer values. This dual interface serves both casual exploration and targeted investigation.

Comprehensive Asset Coverage

The tool indexes infrastructure across 30+ categories with 200+ searchable types. Major groupings include:

• Energy & Power: power plants, substations, solar/wind farms, nuclear facilities, battery storage
• Telecommunications: towers, data centers, antennas, satellite dishes, telephone exchanges
• Oil, Gas & Mining: refineries, pipelines, wells, quarries, storage facilities
• Transportation: airports, ports, train stations, metro systems, cable transport
• Government & Military: embassies, military installations, prisons, police/fire stations
• Public Safety: surveillance cameras, emergency infrastructure, border control

Integrated Geocoding & Mapping

Location resolution uses Nominatim for geocoding place names to bounding boxes. Results display on an interactive Leaflet.js map alongside structured result lists. The architecture diagram in the README shows clean separation: frontend components communicate via POST /api/search to a backend that orchestrates parsing, geocoding, Overpass query building, and caching.

In-Memory Caching

A cache layer (cache.ts) reduces redundant API calls to Nominatim and Overpass, improving response times and respecting rate limits.

Use Cases

Critical Infrastructure Assessment

Energy sector analysts can map power generation and distribution assets for grid resilience studies. Queries like type:substation region:texas or type:solar country:india yield geolocated datasets for scenario planning. The tool's coverage of transformers, converters, and power lines supports detailed network analysis.

Telecommunications Research

Researchers studying digital infrastructure gaps can locate cell towers, data centers, and telephone exchanges. The operator: parameter enables competitive analysis—operator:airtel versus operator:jio in specific regions, for example. This supports both academic research and commercial due diligence.

Maritime & Logistics Intelligence

Port authorities and shipping analysts benefit from comprehensive maritime coverage: ports, harbours, shipyards, docks, ferry terminals, and associated infrastructure. Combined with near: proximity searches, this enables corridor analysis for supply chain studies.

Security & Investigative Journalism

Journalists verifying claims about facility locations can cross-reference addresses with OSM data. The surveillance camera and military installation categories support accountability reporting, while the responsible use policy explicitly prohibits illegal surveillance—an ethical guardrail that distinguishes Sightline from unscrupulous tools.

Urban & Regional Planning

Planners accessing standardized datasets for transportation hubs, public utilities, and emergency infrastructure can baseline existing assets before proposing expansions. The natural language interface allows stakeholders without GIS training to participate in data exploration.

Installation & Setup

Sightline requires Node.js 18+ and npm. No environment variables or API keys are needed—the application uses public OpenStreetMap services.

Clone the repository and install dependencies:

git clone https://github.com/ni5arga/sightline.git
cd sightline
npm install

Start the development server:

npm run dev

Open http://localhost:3000 in your browser.

The project structure follows Next.js conventions with clear separation of concerns:

app/
├── page.tsx              # Main application page
├── layout.tsx            # Root layout
├── globals.css           # Global styles
└── api/
    └── search/
        └── route.ts      # Search API endpoint

components/
├── SearchBar.tsx         # Query input
├── Filters.tsx           # Filter sidebar
├── ResultList.tsx        # Results display
├── MapView.tsx           # Leaflet map
├── ShareButton.tsx       # Share functionality
└── ui/
    └── scroll-area.tsx   # UI components

lib/
├── types.ts              # Type definitions
├── parser.ts             # Query parsing and NLP
├── geo.ts                # Nominatim integration
├── overpass.ts           # Overpass API queries
├── cache.ts              # In-memory caching
├── search-index.ts       # Search indexing

For production deployment to Vercel:

npm install -g vercel
vercel

The zero-configuration deployment and lack of required environment variables make this genuinely portable—run it locally, on Vercel, or any Node.js hosting with minimal friction.

Real Code Examples

The README documents the architecture through a Mermaid flowchart showing data flow from frontend components through backend services to external APIs. The actual implementation follows this pattern:

Frontend to Backend Communication

The SearchBar, Filters, ResultList, and MapView components all communicate via a single API endpoint:

POST /api/search

This consolidates all search logic server-side, keeping the frontend thin and enabling caching at the API layer.

Backend Request Handling

The route.ts handler orchestrates multiple services:

// Pseudocode reflecting the architecture diagram:
// route.ts receives POST /api/search
// 1. Delegates to parser.ts for NLP processing
// 2. Delegates to geo.ts for Nominatim geocoding
// 3. Delegates to overpass.ts for OSM query construction
// 4. Reads from / writes to cache.ts for performance

The actual implementation uses TypeScript with typed interfaces defined in lib/types.ts.

Query Parsing Examples

The NLP engine handles both natural language and structured formats. From the README, these are documented working patterns:

Natural language:

telecom towers in karnataka
power plants near mumbai
data centers in california
airports in germany

Structured with parameters:

type:telecom operator:airtel region:karnataka
type:data_center operator:google
type:substation region:texas
type:airport country:france

The parser normalizes these into Overpass QL queries. The type: parameter accepts any of 200+ documented values with aliases—for example, telecom and tower resolve identically, as do datacenter and data_center.

Geocoding Integration

The geo.ts module converts location strings to bounding boxes via Nominatim:

"karnataka" → Nominatim → bounding box coordinates → Overpass query spatial filter

This abstraction means users never manually specify coordinates.

Note: The README does not contain extensive inline code samples. The architecture is primarily documented through the Mermaid diagram and query syntax tables. Developers should examine the source files (lib/parser.ts, lib/overpass.ts) for implementation details.

Advanced Usage & Best Practices

Respecting Rate Limits

Nominatim enforces 1 request/second. Sightline's cache layer mitigates this, but bulk operations should implement client-side throttling. The Overpass API operates on fair-use principles—avoid automated heavy queries that degrade public infrastructure.

Query Precision

Combine parameters for targeted results. type:power_plant country:india returns manageable datasets; unconstrained type:power_plant queries may timeout or exceed memory limits. Use radius: with near: for geographic containment.

Data Quality Awareness

OSM is crowd-sourced. The README explicitly warns that data may be incomplete or inaccurate. Critical decisions require cross-referencing with authoritative sources—Sightline is a discovery tool, not a certified asset register.

Caching Strategy

The in-memory cache (cache.ts) speeds repeat queries but does not persist across deployments. For production instances with high query volume, consider extending to Redis or similar external cache.

Ethical Boundaries

The responsible use section prohibits illegal surveillance and harmful purposes. Researchers should document legitimate use cases and respect the OpenStreetMap tile usage policy, Nominatim usage policy, and Overpass API usage policy.

Comparison with Alternatives

Sightline occupies a distinct niche: accessible physical infrastructure discovery without GIS expertise or proprietary subscriptions. Overpass Turbo offers more power for OSM specialists. QGIS serves professional geospatial workflows. Shodan and Censys solve different problems entirely—digital asset discovery rather than mapped physical facilities.

For teams needing quick infrastructure lookups with minimal tooling investment, Sightline's web-first approach and natural language interface represent genuine efficiency gains. For advanced spatial analysis, export to QGIS or direct Overpass QL remains necessary.

FAQ

Does Sightline require API keys?

No. The application uses public Nominatim and Overpass API instances with no authentication required.

What license covers the project?

MIT License—permissive for commercial and research use with attribution.

Can I deploy this on my own infrastructure?

Yes. Standard Node.js deployment; Vercel is documented but not required.

How accurate is the infrastructure data?

Data comes from crowd-sourced OpenStreetMap. Coverage varies by region and asset type. Always verify critical information through official sources.

Is there a rate limit I should know about?

Nominatim enforces 1 request/second. The cache layer helps, but respect fair use for Overpass API queries.

What frontend frameworks does it use?

Next.js, React, TypeScript, and Leaflet.js for mapping.

Can I contribute new asset types?

The README lists 200+ types with aliases. Check lib/parser.ts and lib/overpass.ts for the mapping logic, then submit a pull request.

Conclusion

ni5arga/sightline solves a specific, real problem: making OpenStreetMap infrastructure data queryable without GIS expertise. Its natural language interface, structured parameter support, and clean TypeScript architecture make it immediately useful for security researchers, journalists, urban planners, and data scientists who need physical asset locations.

The tool is best suited for rapid infrastructure discovery and preliminary analysis rather than authoritative asset verification. Its MIT license and zero-configuration deployment lower adoption barriers significantly. The 501-star community suggests growing recognition, though users should understand OSM data limitations and API rate constraints before production use.

For developers building OSINT workflows, Sightline provides a solid foundation that can be extended or integrated into larger pipelines. The modular backend architecture—parser, geocoder, query builder, cache—invites contribution and customization.

Explore the repository, try the queries documented above, and consider how this fits your geospatial intelligence needs: https://github.com/ni5arga/sightline