Artificial Intelligence can help turbocharge your OSINT investigations.

In the past few years, the use of artificial intelligence has rapidly moved into mainstream use. What once sounded like a science-fiction dream is now used to achieve all sorts of productivity goals.

Prior to the availability of these types of tools, we’d have to conduct investigations manually, or use scripting and purpose-built tools to help us process or obtain data. Now though, we can use artificial intelligence to help us analyse and process data much more effectively, as well as leverage large language models for research or assistance.

This is the second of our new series that looks to explore how we can use tools like Grok or ChatGPT to help us improve our open-source investigations. We’ll also discuss and consider some of the options available for local usage for those who might like to look at this while mitigating privacy concerns.

ChatGPT has a broad feature set as default, making it a useful tool, albeit with some restrictions. Source: chat.openai.com

AI Options

The wide range of models that are currently available means that you're probably going to be able to select a model that works well for your purposes.

If you’re looking at conducting basic OSINT or building a sockpuppet social media account, you might find that ChatGPT is useful out of the box. However, if social media sleuthing is more your style, then you might find something like Grok to be more useful for your purposes.
In the interests of thinking outside the box though, it’s also worth remembering that ChatGPT hasn’t been the only game in town for a while now.

Perplexity AI is pretty useful for gathering info or carrying out recon on Google, while blockchain fans will even find Web-3 based options like Griffin AI available to help with analysis of wallets, transactions and more.

If you prefer to configure your own hardware, Deepseek and OpenLlama are great options to start with if you’re looking to experiment more with a local model.

Now, we don’t need to be limited to a single tool. Instead, we can find the best option available for the task we need to fulfil.

Web-3 based options can be great for exploring the blockchain and transactions. Source: Griffin AI

Privacy Concerns

An ever-present consideration in today's world, when using AI tools we’ll need to give some strong thought to privacy considerations and how to protect sensitive data.

There’s already been intense discussions around the usage of social media posts and other data to help configure and train systems like ChatGPT, and looking at the privacy information shows us that our inputs and responses will also be used and evaluated.

This doesn’t mean we can’t use these systems in the way we’d like. What it does mean though, is that we should sanitise all inputs to ensure that our confidential information stays confidential.

Privacy should always be a concern. It’s worth reviewing the notes. Source: openai.com

Problems like this are one of the reasons that considering a locally based model that you have built yourself can be such a good option. While it comes with a significant hardware and technical commitment, keeping your data locally changes the dynamic around privacy considerations.

Optimizing

If you’re willing to deal with logins and identify yourself as an actual human, you’ll get a far broader range of tools to play with, as well as being able to pre-configure your model to give the best possible outputs.

Typically, we can do this in two ways. Firstly, we can use the “memory” to help preload conditions into the model. This could include configuring it to act in an investigative role and giving it specific instructions regarding the types of information we might be looking for. Using the memory means that every input comes with these conditions, meaning you won’t have to be as reliant on your prompt to achieve good results.

The second way is by looking at our own prompt and optimising that for the best results too.

We can do this by being very specific with our terminology and asking for clarification to optimise our search. For example.

“Act as an Open-Source Intelligence (OSINT) Analyst. I need you to assist in gathering and analyzing publicly available information on [Topic/Individual/Company]. Your role is to provide concise insights and findings from credible sources, avoiding personal opinions or speculation. To achieve the best results, ask me any questions you need for clarification purposes prior to starting”.

Lastly, we should consider the model in use as well. Often, you’ll see a big difference depending on the type of model you select.

On X/Twitter, for instance, the difference in outputs between Grok 3 and previous iterations was a notable point of contention.

More Ideas

While AI can be great for the bigger stuff, you’ll also find it useful as a research tool as well. For instance, you can use it to help you learn about a new tool or piece of software or even use it to assist you with more specific tasks such as geolocation or image classification.
Also, if you’re a social-media analyst, you might find this next bit particularly useful. One of our fav uses for AI is leveraging it to create engaging and realistic social media accounts that are unique.

Rather than having to come up with a personality that fits, we can use a well-crafted prompt to create detailed accounts that can be used as investigative sockpuppets in mere seconds. The best bit is we’ll receive much more detailed information than we’d get by doing the same role manually.

When properly used, artificial intelligence tools have much to offer savvy cyber analysts. Do you use AI-based tools in your workflow?

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