What specific technical methods do OSINT practitioners use to extract and correlate information?

The four main technical OSINT methods are metadata extraction, reverse image search, username correlation across platforms, and automated scraping tools.

Metadata extraction with EXIF data. Every photo contains hidden metadata. EXIF data can include GPS coordinates pinpointing exactly where the photo was taken, timestamps revealing when, camera model identifying the device, and even lens settings. A single vacation photo can tell an analyst your exact location, the time of day, and what phone you use.

Reverse image search. Services such as Google Images (and comparable tools like TinEye) find every place on the internet where a specific image appears. Upload someone's profile picture and you might discover accounts on platforms they thought were separate from their main identity. This technique is surprisingly effective because most people reuse the same photos across platforms.

Username correlation. Many people use the same username everywhere. Finding "alex_security" on Twitter often leads to the same handle on GitHub, Reddit, Steam, and countless other platforms. Each platform reveals different aspects of someone's interests, activities, and social connections.

Automated scraping with dedicated OSINT software. Purpose-built tools automate the collection and visualization of relationships between data points. A well-known example is Maltego, which transforms manual OSINT into systematic intelligence gathering, creating visual graphs that show how people, organizations, domains, and accounts are connected.

Go deeper:

• Exif (Wikipedia) — how photo metadata (incl. GPS) leaks location.
• Maltego — OSINT & link-analysis platform — the relationship-graphing tool.