Open Source Intelligence (OSINT) Guide

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Open-source intelligence (OSINT) is an affordable and accessible method for applying intelligence to enterprise cybersecurity management and other business use cases.

Open source intelligence is sourced from all corners of the web, and while that makes the data incredibly comprehensive, it also brings forth a large body of data that needs to be fact-checked and reviewed closely for the best possible results.

Let’s take a closer look at what open-source intelligence is, how it works, and how you can apply this type of intelligence to your business operations most effectively.

What Is Open Source Intelligence?

Open source intelligence is a type of data-driven intelligence that scours the internet and other public sources for information that’s relevant to a user’s query or search. Most often, OSINT is used to strategically collect information about a particular individual, group of people, organization, or other public entity.

Historically, OSINT developed before the internet and was a military espionage technique for finding relevant information about military enemies in newspapers, radio broadcasts, and other public data sources. While most data sources used for OSINT today are online or somehow digitized, OSINT analysts still have the option to collect physical data from public, open sources.

Also see: Top Data Visualization Tools

Passive vs. Active OSINT

Passive and active OSINT are both viable open source intelligence collection methods with different amounts of hands-on activity and in-depth research required.

With passive OSINT, users most often complete a simple search engine, social media, or file search or look at a website’s or news site’s homepage through a broad lens. They aren’t actively trying to collect highly specific information but rather are unobtrusively looking at the easiest-to-find, top-of-the-stack intelligence available. With this intelligence collection method, the goal is often to collect useful information without alerting targets or data sources to your intelligence collection activities.

When practicing active OSINT, the methods tend to be more intrusive and involved. Users may complete more complex queries to collect obscure intelligence and metadata from databases and network infrastructure, for example. They also might fill out a form or pay to get through a paywall for more information.

In some cases, active OSINT may even involve reaching out directly to sources for more information that is not publicly available or visible. While active OSINT is more likely to give users real-time, in-depth information than passive OSINT, it is much more difficult to do covertly and may lead you to legal troubles if your data collection methods aren’t careful.

Open Source Intelligence Data Sources

Open source intelligence can be sourced from any public dataset or property. These are some of the most common OSINT data sources from across the web:

• Social media platforms
• Public-facing websites
• News media
• Academic and scientific studies
• Internet of Things databases
• Business directories
• Financial reports
• Images and image libraries
• Public records, both digital and physical

Also see: Best Data Analytics Tools 

How Does Open Source Intelligence Work?

For individuals and organizations that want to take advantage of open source intelligence, a simple way to get started is with a search engine query. Often, asking the right question about the demographic information you need is the first step to finding relevant open source data entries that can lead to more detailed information.

Beyond using search engines for internet-wide data searches, you can also refine and focus your search on specific data platforms or databases, such as a certain social media platform. Depending on your goals and experience, you may also benefit from analyzing open source threat intelligence feeds and other sources that frequently update massive amounts of data.

If your data collection and analysis goals require you to work with big data sources like databases, data lakes, or live feeds, manual searches and research are ineffective. To quickly process and sort through large amounts of intelligence, you’ll want to consider investing in a web scraping or specialized OSINT tool that can automate and speed up the data analysis process.

OSINT Use Cases

Have you ever “Facebook stalked” someone you just met or Google searched your family’s last name to see what pops up? Both of these are simple examples of how even individuals practice a simplified form of open source intelligence in their daily lives.

Businesses, too, may collect OSINT without realizing it, but in most cases, they are collecting this kind of intelligence for a distinct competitive advantage or cause. Here are some of the most common OSINT use cases in practice today:

• Threat intelligence, vulnerability management, and penetration testing: Especially when used in combination with more comprehensive threat intelligence platforms, open source intelligence and data collection can give security analysts and professionals a more comprehensive picture of their threat landscape, any notable threat actors, and historical context for past vulnerabilities and attacks.
• Market research and brand monitoring: If you want to get a better look at both quantitative purchase histories and overall brand sentiment from customers, OSINT is an effective way to collect broad demographic intelligence about how your brand is performing in the eyes of the consumer. For this particular use case, you may conduct either passive or active OSINT in social media platforms, user forums, CRMs, chat logs, or other datasets with customer information.
• Competitive analysis: In a different version of the example above, you can complete OSINT searches on competitor(s) to learn more about how they’re performing in the eyes of customers.
• Geolocation data sourcing and analysis: Publicly available location data, especially related to video and image files, can be used to find an individual and/or to verify the accuracy of an image or video.
• Real-time demographic analyses over large populations: When large groups of people are participating in or enduring a major event, like an election cycle or a natural disaster, OSINT can be used to review dozens of social media posts, forum posts, and other consumer-driven data sources to get a more comprehensive idea of how people feel and where support efforts — like counterterrorism or disaster relief response, for example — may be needed.
• Background checks and law enforcement: While most law enforcement officials rely on closed-source, higher intelligence feeds for background checks and identification checks, OSINT sources can help fill in the blanks, especially for civilians who want or need to learn more about a person. Keep in mind that there are legal limits to how open source intelligence can be used to discriminate in hiring practices.
• Fact-checking: Journalists, researchers, and everyday consumers frequently use OSINT to quickly check multiple sources for verifiable information about contentious or new events. For journalistic integrity and ethical practice, it’s important to collect information directly from your sources whenever possible, though OSINT sources can be a great supplement in many cases.

Also read: Generative AI: 15 Enterprise Use Cases You Can Implement

10 OSINT Tools and Examples

Particularly for passive OSINT and simple queries, a web scraping tool or specialized “dork” query may be all that you need. But if you’re looking to collect intelligence on a grander scale or from more complex sources, consider getting started with one or several of the following OSINT tools:

1. Spyse: An internet asset registry that is particularly useful for cybersecurity professionals who need to find data about various threat vectors and vulnerabilities. It is most commonly used to support pentesting.
2. TinEye: A reverse image search engine that uses advanced image identification technology to deliver intelligence results.
3. SpiderFoot: An automated querying tool and OSINT framework that can quickly collect intelligence from dozens of public sources simultaneously.
4. Maltego: A Java-based cyber investigation platform that includes graphical link analysis, data mining, data merging, and data mapping capabilities.
5. BuiltWith: A tool for examining websites and public e-commerce listings.
6. theHarvester: A command-line Kali Linux tool for collecting demographic information, subdomain names, virtual host information, and more.
7. FOCA: Open source software for examining websites for corrupted documents and metadata.
8. Recon-ng: A command-line reconnaissance tool that’s written in Python.
9. OSINT Framework: Less of a tool and more of a collection of different free OSINT tools and resources. It’s focused on cybersecurity, but other types of information are also available.
10. Various data analysis and AI tools: A range of open source and closed source data analysis and AI tools can be used to scale, automate, and speed up the process of collecting and deriving meaningful insights from OSINT. Generative AI tools in particular have proven their efficacy for sentiment analysis and more complex intelligence collection methods.

More on a similar topic: Top 9 Generative AI Applications and Tools

Pros and Cons of Open Source Intelligence

Pros of OSINT

• Optimized cyber defenses: Improved risk mitigation and greater visibility into common attack vectors; hackers sometimes use OSINT for their own intelligence, so using OSINT for cyber defense is often an effective response.
• Affordable and accessible tools: OSINT data collection methods and tools are highly accessible and often free.
• Democratized data collection: You don’t need to be a tech expert to find and benefit from this type of publicly available, open source data; it is a democratized collection of valuable data sources.
• Quick and scalable data collection methods: A range of passive and active data sourcing methods can be used to obtain relevant results quickly and at scale.
• Compatibility with threat intelligence tools and cybersecurity programs: OSINT alone isn’t likely to give cybersecurity professionals all of the data they need to respond to security threats, but it is valuable data that can be fed into and easily combined with existing data sources and cybersecurity platforms.

Cons of OSINT

• Accessible to bad actors and hackers: Just like your organization can easily find and use OSINT, bad actors can use this data to find vulnerabilities and possible attack vectors. They can also use OSINT-based knowledge to disrupt and alter intelligence for enterprise OSINT activity.
• Limitations and inaccuracies: Public information sources rarely have extensive fact-checking or approval processes embedded into the intelligence collection process. Especially if multiple data sources share conflicting, inaccurate, or outdated information, researchers may accidentally apply misinformation to the work they’re doing.
• User error and phishing: Users may unknowingly expose their data to public sources, especially if they fall victim to a phishing attack. This means anyone from your customers to your employees could unintentionally expose sensitive information to unauthorized users, essentially turning that private information into public information.
• Massive amounts of data to process and review: Massive databases, websites, and social media platforms may have millions of data points that you need to review, and in many cases, those numbers are constantly growing and changing. It can be difficult to keep up with this quantity of data and sift through it to find the most important bits of intelligence.
• Ethical and privacy concerns: OSINT is frequently connected without the target’s knowledge, which is an issue with AI and ethics. Depending on the data source and sourcing method, this information can be used to harm or manipulate people, especially when it’s PII or PHI that has accidentally been exposed to public view.

Bottom Line: Using OSINT for Enterprise Threat Intelligence

Getting started with open source intelligence can be as simple as conducting a Google search about the parties in question. It can also be as complex as sorting through a publicly available big data store with hundreds of thousands of data entries on different topics.

Regardless of whether you decide to take a passive or active approach, make sure all members of your team are aware of the goals you have in mind with open source intelligence work and, more importantly, how they can collect that intelligence in a standardized and ethical manner.

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