Open Source Intelligence Techniques (OSINT) for Fraud Prevention

A fraud analyst almost always starts with fragments: an email address, a phone number, an IP, and a nagging question about who is really behind them. Open Source Intelligence (OSINT) is the practice of gathering publicly available data, from social media and search engines to public records and traditional media, to turn those fragments into a clear picture.

This guide walks through the core principles of OSINT, the techniques analysts rely on and practical, tried-and-tested tips for using it to fight fraud. OSINT reaches across many fields, from law enforcement to national security and everyday business intelligence, but our focus here is fraud prevention and detection.

What Is OSINT?

Open Source Intelligence means gathering publicly available data from the internet, social media and traditional sources such as TV, newspapers and journals, in order to assess a case or a situation.

The acquired information can range from text to images, videos and profiles. Once gathered, it needs to be processed, assessed and stored according to the analyst’s end goal, whether that is fighting fraud, preventing chargebacks or segmenting website visitors for marketing and security.

At SEON, we leverage the power of 350+ OSINT sources to gauge the true intentions of the people who engage with our customers. As the CIA’s website puts it, “Information does not have to be secret to be valuable.”

How Does OSINT Work?

OSINT tools collect and aggregate information from a range of publicly available sources to give a more detailed overview of a particular user or company. Most public sources qualify, including:

• blogs
• forums
• social media sites
• traditional media (TV, radio, publications)
• research papers
• government records
• academic journals

In fraud detection, using OSINT means gathering information on a customer or case to determine who they are, their intentions, or what has happened. The most common scenario is verifying whether the user and the cardholder are the same person.

OSINT also comes into play in more complex cases where entities need to be analyzed, such as suspicious users or affiliate fraudsters. These are commonly called persons or points of interest (POI), a term originally coined by the CIA.

Who Uses OSINT?

OSINT is used by a variety of providers to find more information on specific people or topics where further intelligence is needed. It is common across these fields:

• law enforcement
• risk and fraud management
• human resources
• cybersecurity
• military operations

From businesses handling pay-in and pay-out systems to law enforcement, OSINT can support almost any type of investigation.

OSINT & Financial Fraud

In financial crime, and especially financial fraud, OSINT is a valuable ally. Because so much fraud relies on social engineering, confidence scams and fake identities, an investigation that starts with the little we know for certain can reveal a great deal.

A likeness, a social media profile picture or a commonly used email address can shed light on who someone really is. SEON’s data enrichment solution, for example, starts with an email address, phone number or IP and builds a full profile from the person’s digital footprint, which is near-impossible to fake.

That profile can include an IP fraud score, flagging risky connections such as proxies, VPNs or Tor exit nodes before any manual investigation begins.

Why Is OSINT Important?

Reasons why using OSINT is important are closely connected to the purpose of its usage. As examples, some of these can be:

• identifying data breaches 
• customer due diligence (CDD)
• uncovering vulnerabilities
• backing up decision making processes
• keeping up to date with news 

Advantages of OSINT

OSINT adds a layer of security and deepens your knowledge of a user without requiring anything from their side, so it does not disrupt the user journey. That extra layer improves decision-making at a lower cost, since many tools are available for free.

Another key upside for risk analysis is freshness: because public information is constantly added online, the data can be live or frequently updated. We have collected a range of options in our post on the best tools for OSINT.

Disadvantages of OSINT

Because you are essentially searching the internet’s public library, filtering through the noise can be strenuous. Without specialized tools, a team can spend hours sifting through thousands of results with no clear direction.

Few plug-and-play tools support the analysis itself, and without the support of AI, OSINT demands a lot of human input to verify what is collected. The point cannot be overstated: OSINT has to be validated. Sources need to be scrutinized, or you risk analyzing false or useless information.

Are OSINT Investigations Legal?

OSINT is publicly produced and publicly available data that can be collected and shared without breaking laws, needing a warrant, or engaging in what would be considered shady practices. In the context of fraud investigations it is perfectly legal, provided the gathered and stored information is handled compliantly.

There are firm boundaries, though. Public data used for fraud checks must not be repurposed to make credit or employment decisions, which fall under regimes such as the Fair Credit Reporting Act (FCRA) and dedicated screening rules. Practitioners draw a hard line here: enrichment can inform a fraud risk decision, but it cannot become a background check by the back door.

Handling matters too. Test and investigation data should be gathered with a lawful basis, stored securely, often in encrypted files, and access-controlled. In recent years OSINT has also gained notoriety through “doxxing,” combining public information to unmask anonymous users, which can be illegal depending on intent and local law.

What Are OSINT Techniques?

OSINT techniques are the methodology of acquiring information: knowing where to search and what tools to use. This matters because although most sites have a search box, they treat data such as emails and phone numbers as sensitive, so you need to know where to look for a search to return results.

Sometimes it means working against the algorithm. Google orders results one way, but special search operators let you filter by file type, language or domain. It is useful to use different engines such as DuckDuckGo or Bing to counter algorithmic bias.

Other queries need specialized engines, such as people searches, or use-case-specific databases like the leaked email database at haveibeenpwned.com. Many sources are free but time-consuming, while specialist software is typically expensive. The OSINT Framework is a good map of sources, and Moz.com is worth using to master advanced search operators.

What Does an OSINT Investigator Do?

An OSINT investigator gathers and analyzes information, then extracts knowledge from the findings. Protocols vary by organization, but most investigations follow a recognizable framework:

• Collecting from open sources: following the mantra “start with what you know,” the investigator searches on emails, phone numbers, usernames, names and addresses to build a file on the case.
• Filtering: many findings are mismatches or irrelevant and must be set aside, because working with the wrong information leads to the wrong call.
• Analysis: using inductive reasoning, the analyst builds a theory from what the data shows, working toward actionable insight.
• Gaining insight: finally the investigator makes a recommendation and presents the reasoning. It is good practice to involve a second investigator here to check for bias.

One technique separates strong analysts from slow ones: correlate identifiers together rather than in isolation. Searching an email, then a phone, then an IP as three separate lookups yields disparate scraps. Feeding them as one connected profile lets a scoring engine weigh them in relation to each other, which is where the real signal lives.

In short, intelligence is analysis plus information.

OSINT for Applicant and Remote-Worker Fraud

Hiring has become one of the newest arenas for OSINT. Organizations increasingly face fraudulent job applicants, including operatives from sanctioned regions who pose as remote workers to reach payroll or internal systems. The stakes are real: US authorities have indicted operations that generated tens of millions through fraudulent employment, and in one case a fake engineer tried to install malware on day one.

Here OSINT flips from vetting customers to vetting candidates, and the question becomes whether a claimed identity leaves the footprint it should. The tell is rarely a single smoking gun, but a cluster of mismatches read together, such as:

• an IP claiming a US location while device geolocation points elsewhere
• a screen resolution typical of a desktop on an applicant claiming to be on a phone
• a device model sold only in another region
• remote-access software running on the machine

Each is explainable on its own. Combined, they expose the deception.

How Can OSINT Help With Fraud Prevention?

OSINT helps in two ways: it fills the gaps an automated system leaves, and it keeps you ahead of the fraudsters targeting you. When a risk score cannot settle a case on its own, an analyst uses OSINT to gather the missing context and track what fraudsters are planning next.

When automated rules fall short

OSINT is most often paired with manual reviews, stepping in when the automated ruleset cannot assess a case on its own. A risk score reflects only the data captured for a given action, so a human gathers the rest.

The discipline is to build the picture yourself rather than lean on the customer. As one risk leader put it, the whole aim is to not touch the customer: instead of asking a suspected high roller for three months of bank statements, the team assembles what it needs from the tools at its disposal, keeping things frictionless for legitimate users.

Staying ahead of fraudsters

The second major use is keeping current with what fraudsters are doing. OSINT techniques can search carder forums and the dark web to see what is trending and what you need to prepare for, from new cash-out methods to the tactics being shared for beating a specific platform.

The questions every analyst asks

OSINT covers the classic who, what, when, where, why and how, but a fraud analyst keeps returning to three:

• Are you really who you say you are?
• Is this too good to be true?
• Does this person fit our customer profile?

The two halves of the identity puzzle

The better fraudsters probe both the gaps in your system and the gaps in your thinking. Someone who just bought stolen credit card details will research the victim, match the transaction to what you might find, and route through a proxy that survives an address-distance check. So a case usually has two sides:

• The presented identity: details that may match a real person who is a victim of identity theft or a money mule.
• The user’s own signals: device metadata, IP, provided email and phone.

The real question is whether those two halves are linked by anything beyond the transaction in front of you.

What actually links the two halves

Finding that link is the heart of the work, and a handful of signals do most of it:

• Shared device or IP: a device fingerprint built from hardware and behavior persists across sessions, so two accounts on the same machine connect even when the names and emails differ.
• Email maturity: an address first seen years ago with a broad platform footprint reads very differently from one created last week with nothing attached to it.
• Phone-to-name mismatch: when a caller-ID (CNAM) lookup returns a different name than the application, the phone and the identity do not belong together.
• Prior fraud flags: an email, phone or IP that another company has already reported as fraudulent, surfaced through shared or consortium data.

Use your internal data, too

OSINT is not limited to the open web. As a fraud manager you hold a wealth of internal data, so examine connected users and entities and run OSINT on them. Links visible internally often surface online, and intelligence gained externally can reveal new points of interest inside your system, which is common when dissecting fraud rings. Michael Bazzell’s workflows at IntelTechniques.com are worth practicing until they become second nature.

OSINT: Capturing Evidence and Notetaking

For a basic case, saving links beside your notes may be enough. But bit rot (data degradation) is real, you are handling hints and evidence, and skilled cybercriminals cover their tracks as carefully as they practice operational security.

So preserve everything. Lean on archive.is or the Wayback Machine (archive.org), a screenshotting plugin for your browser, or the industry-standard Hunchly extension, which is licensed yearly.

Conclusion

OSINT is the Swiss army knife in an analyst’s kit, and it earns its place against cybercriminals who specialize in beating automated defenses. The craft comes down to finding what someone would rather you did not.

Plenty of tools can automate the mechanics, but the mindset is what matters: handling information in the right context, drawing the correct conclusions, and deciding on that basis.

FAQ

Sources

• OSINT Framework