How can AI assist OSINT researchers

Open-source intelligence (OSINT) is gaining more attention due to the massive volume of digital data generated daily by computing devices, Internet of Things (IoT) sensors, and people's interactions on social media platforms. Government agencies and business organizations have rushed to exploit OSINT in gathering and analyzing public data due to its cost-effectiveness and the precious intelligence value it can provide for its adopters.

However, as with every technology, OSINT has some drawbacks and challenges. The most obvious two are the sheer volume of digital data and the associated resources (e.g., time and expertise) needed to analyze collected data. Fortunately, artificial intelligence (AI) has emerged to solve these challenges, and this is what we will focus on in this article.

How can AI technology be leveraged to assist OSINT gatherers? 

AI can greatly enhance the capabilities of OSINT researchers by automating tasks, analyzing large volumes of digital data that contain both structured and unstructured data, and uncovering insights that human analysts might miss. Here are the most prominent ways in which AI can assist OSINT researchers:

Data collection

The first task of OSINT gatherers is to collect data from publicly available sources based on a predefined plan. While we will not discuss a preferred OSINT plan in this article, data collection consumes considerable time for OSINT gatherers as it can span many online resources based on the investigative case. AI technology can assist by providing intelligent data web scrapers that leverage machine-learning (ML) technology to harvest data intelligently based on user requests. For instance, AI-powered web scrapers can do the following:

• Handle dynamic content easily and without human intervention. For instance, many websites use JavaScript to dynamically generate content as users interact with the website. AI-powered scrapers can fetch and collect such content by mimicking human browsing behavior
• AI-powered web scrapers can bypass anti-scraping measures implemented by some websites through adaptive behavior patterns and rotating network signatures
• Correlate data automatically from multiple sources and establish connections between seemingly unrelated information points
• Gather unstructured data, like free text, text in PDF documents, and TXT files, and insert it into a specific data format, such as a Microsoft Excel spreadsheet, based on user request
• Extract data on a predefined schedule and update it again with new information when the source changes
• Analyze the sentiment and context behind the collected data using natural language processing (NLP) technology and categorize collected data accordingly

Natural language processing (NLP)

NLP is a sub-branch of AI technology that can understand human text. By leveraging NLP technology, OSINT gatherers can do the following:

• Extract key entities from text content, such as names, locations, cities, country names, and dates
• Create relationship maps between named entities, showing connections between people, organizations, and locations mentioned in collected data
• Translate foreign language contents into any other language, such as translating from Arabic or Chinese to English, allowing OSINT researchers to utilize foreign resources in their research
• Summarize lengthy text documents and provide key information in a concise summary

Facilitate image and video analysis

During their investigations, OSINT researchers frequently need to analyze multimedia files, such as images and video files. AI can facilitate and streamline analyzing multimedia content through the following:

• Identifying objects in images and videos automatically. AI-powered tools can identify objects such as human faces, animals, buildings, or other objects in images and videos and extract them automatically
• Advanced Optical Character Recognition (OCR) capabilities that can extract text from complex visual media, including handwritten documents and low-resolution images
• Comprehensive metadata analysis to extract hidden information about image creation, modification date, and GPS coordinates, if available
• Facial recognition AI-powered tools can identify a specific person's face in large numbers of images and videos
• Verifying collected images and videos, including detecting various types of manipulation beyond deepfakes

Social media intelligence

AI-powered tools can harvest and analyze vast volumes of content published on social media platforms. It can facilitate OSINT gatherers' work by:

• Identifying complex behavioral patterns across multiple social media platforms to detect coordinated activities
• Generating detailed network relationship maps to understand information flow and key influencers in a specific online community, such as a Facebook group or a subreddit
• Detecting and analyzing bot accounts
• Identifying trending topics, hashtags, or conversations across large numbers of social media platforms

Threat intelligence

AI-powered tools have become a critical component in the cyber threat intelligence arsenal that enhances OSINT capabilities.

• AI technology has the ability to analyze vast amounts of threat data to identify patterns that may indicate new attack vectors or techniques
• AI can automatically extract indicators of compromises (e.g., IP addresses, domain names, file hashes) from various sources, such as threat feeds, social media, and dark web forums
• AI can analyze historical data to predict future threats
• AI can correlate data from diverse sources (e.g., threat intelligence feeds, social media sites, dark web, internal logs such as security solutions and networking devices logs) to establish the credibility and severity of a threat

Enhanced search capabilities

AI-powered search tools can understand OSINT researchers' search queries based on their context, which helps researchers get more precise results from search engines. AI solutions can also navigate and extract data from less accessible parts of the internet, such as deep and dark websites.

Simplify and aid in verification and fact-checking 

Part of the collected data could be disinformation or incorrect data. OSINT researchers cannot incorporate data into their investigation until they are assured it is accurate and trustworthy. AI-powered solutions can aid in the verification and fact-checking phase. For instance, AI-powered solutions can check data sources to identify which sources are reliable or not. These solutions can also search online to cross-reference data with other sources to measure their truthfulness.

Geospatial analysis

A major benefit of AI-powered solutions is their ability to analyze content such as images and videos in addition to their metadata to locate their geographical location. For instance, AI can analyze geotagged data across social media platforms to track movements or identify activity hotspots. Images acquired from satellites can automatically be analyzed to detect changes in terrain, infrastructure, or other features.

Automated reporting

The last phase of any OSINT gathering task is reporting. AI technology can better prepare and generate OSINT reports that incorporate key findings in an organized way. For instance, AI can aid in compiling data into structured reports, complete with visualizations and summaries.

AI technology is revolutionizing OSINT research by addressing key challenges in collecting massive volumes of digital data and analyzing it. AI technology enhances OSINT capabilities through intelligent data collection, advanced natural language processing, and automated multimedia analysis. AI-powered tools excel at processing social media content, generating threat intelligence, and performing accurate geospatial analysis. These tools can identify complex patterns, extract crucial information from various sources, and cross-reference data for verification. AI also streamlines the investigation process by automating reporting tasks and enhancing search capabilities across both surface, deep and dark web sources. This technological integration allows OSINT researchers to focus on high-value analytical tasks while automating time-consuming manual processes.