Online, image is everything. From profile pictures to product shots, screenshots to selfies, CCTV captures to first-hand news footage - digitally, pictures tell a thousand words. For OSINT investigators, it’s even more true.
In this guide, we’re looking at the big picture. We’ll zoom out and show you what image OSINT actually is, how AI is changing the scene, and how image search works (reverse image search and regular) - before zooming back in on the specific tools you need to perfect your skills. By the end, you’ll be an old master. Let’s get to work.
What Is Image OSINT?
Image OSINT is exactly what it says on the paintbox: extracting intelligence from publicly-available images. If you’re analysing open-source data to get insights - in other words, to learn something - then congratulations. You’re doing OSINT! Image OSINT is just the same thing, but the open-source data is in image format.
With image OSINT, you can find out all kinds of information. You can learn about the history of an image file online, identify the people or objects inside it, understand the context it was created in, and even set on specific visual details to spark new investigation ideas.
However, there are a couple of other differences between text-based OSINT, and image OSINT. Whilst an email address (before processing) is just a string of letters, a single photo can contain dozens of data points at once: faces, clothing, objects, architecture, language, brands, reflections, shadows… the list goes on and on. And that’s before we even get into metadata.
Each one of these data points can be a pivot that changes your entire investigation - and that’s what makes OSINT with images so powerful. You’re not just searching for or with image data, you’re searching through it too.
What Is Reverse Image Search (and How Does It Really Work)?
Reverse image search is one of the fundamentals of image OSINT. It flips the usual search process, and starts from the other side of the canvas. Instead of typing keywords into a search bar, you upload an image. Then, the search system takes this image and matches it to visually similar results from across the web.
Traditional reverse image search works by analysing patterns across the entire image. That could be matching up similar colour palettes, or even spatial relationships and measurements. The algorithm then compares those features against an extensive index of previously crawled images, and returns anything that’s a near-match.
This works well for identifying:
- reused photos
- stock images
- product shots
- buildings and landmarks
- memes and screenshots
But it’s far less reliable for identifying people. Unless the individual you want to identify is astronomically famous (with millions of photos out there for the system to crawl), you’ll struggle to find them with a traditional image search. If you’re searching for a private person, your image OSINT efforts will often come back empty-handed.
Traditional vs AI-Powered Image OSINT
This is where AI image OSINT comes in. Where traditional reverse image search treats the image as a whole, AI-powered image search breaks it down into component parts, and analyses these parts individually.
Rather than seeing a complete “picture”, modern AI tools see a collection of faces, objects, text, brands, vehicles, architecture, and environmental context - everything, everywhere in the image, all at once. Each of these elements is searched, simultaneously.
(Note: AI image OSINT is not to be confused with using OSINT to spot AI images. Although this is possible too!)
With AI-driven OSINT with images, you can:
- recognise faces across different lighting, angles, or edits
- identify objects like watches, shoes, vehicles, or weapons
- detect landmarks or architectural styles
- read signs and text inside images
- match altered, cropped, or filtered photos
- connect images to social media profiles
This turns image OSINT into a multi-pivot investigation tool. One photo can generate ten leads - if you know how to work it.
Essential Tools for Image OSINT
No single tool can do everything; you can’t paint a portrait with a trowel. So, just as an artist needs more than one colour on her palette, investigators need multiple image tools to get the full picture.
Like regular search engines index different parts of the internet, image OSINT tools will each cover different areas - making them perfect for different tasks. Here are all the pro tools we prefer to use when we want photo OSINT results.
Yandex
Best for: Detail. Yandex is one of the strongest tools for detail-focused searching. It’s particularly good at recognising faces even when backgrounds, lighting, or angles change - so you won’t have to edit images before you search them to get good results. It also performs well on architecture and geographic features, and supports search operators (aka dorks) for more precise queries.
PimEyes
Best for: Faces. PimEyes is one of the most advanced publicly accessible facial recognition tools available. It excels at matching human faces, even from low-resolution or poor-quality images. Plus, if you have a little cash to spare, the paid tiers will give you direct source links, making it a powerful option for serious investigations.
Lenso.ai
Best for: AI-powered searching. Lenso.ai is a modern AI-driven platform built for difficult cases. It handles edited, angled, or partially obscured details well, and does a great job of searching specifics from within the image you provide.
The system uses multiple trained models for faces, places, objects and more, so it’s automatically specialised to whatever you throw at it. On top of that, it allows long-term monitoring through alerts when new matches appear. If other search engines struggle, try this one.
TinEye
Best for: Traditional searching. An oldie, but a goodie. TinEye is a classic reverse image search engine that still earns its place in the OSINT toolkit. It’s excellent for finding older versions of images, detecting edits, and tracing image origins.
The fact that Tineye has been going so long means it has the widest index - so it’ll bring up results from way back that other services either haven’t crawled yet, or can’t anymore. This makes it especially useful for historical matches, and identifying original uploads.
Google Lens (and Bing Visual Search)
Best for: Simplicity. Maybe you don’t have a complex query - you just need a quick and dirty solution that gets the job done. In those cases, these are the OSINT image tools for you.
Like their text-based versions, Google Lens and Bing Visual Search are general-purpose reverse image search engines. They’re not great at identifying private individuals or anything too tricky, but they shine when it comes to objects, products, landmarks, and “what is this thing?” searches.
Sometimes, a picture tells a thousand words. See how image OSINT cracked a real life case in our Case Study:
"Facebook knows us better than we know ourselves … unlike the majority of social media platforms, Facebook requires users to input a real ‘government’ name - not to mention the host of other data, posts, photos and videos users happily upload..."
Read more: Using Facebook to Crack Fraud and Find Missing Persons with OSINT Tactical
