5 Essential Tools in OSINT Investigations

OSINT investigations involve collecting and analyzing publicly available information to support decision-making, verify claims, and detect fraud.

OSINT investigations rely on information that is legally accessible to the public, including:

• Government records
• Social media content
• Business filings
• News archives
• Public datasets

The volume of available data is significant. As of 2025, approximately 5.24 billion people worldwide use social media, representing roughly 64% of the global population. That digital activity creates an enormous amount of publicly available information. When properly analyzed, that information becomes actionable intelligence.

Mining Public Records and Government Databases

Public records are often the foundation of strong OSINT investigations. Government agencies maintain extensive databases that include:

• Property tax records
• Court filings
• Business registrations
• Building permits
• Fire and incident reports

These records help establish timelines, ownership, prior activity, and connections between individuals or entities.

For example:

• Building permits may reveal renovations before a fire loss.
• Court records may show prior similar claims or litigation history.
• Corporate filings may uncover ownership relationships or undisclosed partnerships.

Artificial intelligence tools now assist in sorting and analyzing large volumes of records quickly. However, technology does not replace judgment. Effective OSINT work depends on understanding which records matter and how they connect.

Deep Web and Dark Web

The deep web and dark web are often treated as the same concept, but they are different.

The deep web accounts for about 90% of the internet. It includes content that is not indexed by search engines like Google. Examples include:

• Online court dockets
• Property tax and assessor databases
• Business registration searches
• Professional license verification systems
• Secure government portals
• Academic research databases

This information is not hidden or illegal. It simply requires searching within specific platforms rather than through a general search engine.

On the other hand, the dark web is a small portion of the deep web that requires specialized software to access. It is encrypted and designed to preserve anonymity.

While the dark web is associated with illicit marketplaces, it is also used for privacy-focused communication and journalism in restrictive environments. Access and monitoring require strict legal protocols and specialized expertise.

In most claims-related OSINT investigations, the deep web provides far more relevant information than the dark web.

Metadata in OSINT Investigations

Metadata is data about data. It does not display the content itself but reveals technical details about that content. For images, metadata, often called EXIF data (Exchangeable Image File Format), can include:

• Date and time the image was captured
• GPS coordinates
• Device type
• Camera settings
• File creation and modification timestamps
• Edit history

Metadata analysis can confirm or contradict the context of submitted evidence. For example, metadata could reveal that a photo presented as recent storm damage was taken 6 months ago or in another state.

Modern systems increasingly integrate AI to analyze metadata automatically. Instead of relying solely on manual review, software can flag inconsistencies in real time by comparing timestamps, location data, and edit history against claim details.

Web Scraping in OSINT Investigations

Web scraping is the automated collection of publicly available website data using defined parameters. Modern tools can:

• Pull specific pieces of information from large websites
• Move through pages that load as someone scrolls or clicks
• Organize scattered website content into usable data
• Operate in ways that resemble normal user activity

Web scraping is commonly used to:

• Compare medical provider listings with billed services
• Compile public crime statistics
• Gather large datasets for pattern analysis

Web scraping converts dispersed information into structured datasets that can be analyzed systematically within a digital investigation.

Geolocation and Geospatial Analysis

Geolocation connects digital signals to physical locations. Sources may include:

• GPS metadata embedded in images
• IP address location data
• Social media check-ins
• Device location records

Geospatial analysis builds on this by layering additional data such as:

• Satellite imagery
• Street-level mapping
• Traffic patterns
• Weather history
• Flood and environmental risk mapping

For example, GPS metadata attached to a social media post may confirm whether a device was near a reported accident scene. Historical weather data may confirm whether storm conditions were consistent with reported damage.

Location intelligence is becoming more dynamic. Modern mapping systems incorporate real-time and continuously updated data, allowing investigators to evaluate environmental and geographic conditions as they change.

Why OSINT Investigations Matter

OSINT investigations are central to modern fraud detection and claims verification.

Fraud costs the United States $308.6 billion annually, according to the Coalition Against Insurance Fraud. Publicly available data often reveals inconsistencies that traditional investigative methods may not immediately detect.

Additionally, digital activity continues to expand. Public records, online behavior, and location data collectively create a persistent digital footprint. Effective OSINT investigations turn that footprint into evidence.

Want to explore OSINT investigations in greater depth? Register for our OSINT CE course today.

Check out our sources:

Coalition Against Insurance Fraud. “Fraud Stats.” InsuranceFraud.org, https://insurancefraud.org/fraud-stats/.

Data & Marketing Association (DISA). 2025 Social Network Usage and Growth Statistics. DISA, 2025, https://disa.org/2025-social-network-usage-and-growth-statistics/.

Fraud.net. “Deep Web.” Fraud.net Glossary, https://www.fraud.net/glossary/deep-web#what-is-deep-web.