Mapping Cyber Threats with Geospatial OSINT
Geospatial OSINT (Open Source Intelligence) integrates location-based data with traditional cyber intelligence to identify the origins, patterns, and physical contexts of cyber threats. By combining tools like satellite imagery, IP geolocation, and metadata analysis, cybersecurity teams can map digital attacks to real-world locations, uncover threat actor movements, and improve response strategies.
Key takeaways:
- What it is: Geospatial OSINT uses geographic data from public sources to enhance cyber threat analysis.
- Why it matters: It reveals attack patterns, links threats to specific regions, and supports real-time monitoring.
- How it works: Analysts use tools like Shodan, EXIFTool, and GIS software to track IPs, analyze metadata, and visualize threats.
- Real-world examples: Used in cases like tracking APT33‘s espionage campaigns and military movements during the Ukraine conflict.
Introduction to Geospatial OSINT
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Core Concepts of Geospatial OSINT in Cybersecurity
Geospatial OSINT (Open Source Intelligence) is built on four main ideas: visualization, pattern identification, movement tracking, and geographic contextualization. Visualization transforms complex data into maps, making spatial connections instantly clear. Pattern identification dives into spatial analysis to uncover attack hotspots and trends hidden in raw data. Movement tracking focuses on monitoring the physical movements of threat actors or assets using geolocation signals. Geographic contextualization brings in the "where" factor, connecting digital evidence like IP addresses and domains to real-world locations.
"Geospatial tools and mapping technologies are essential components of modern OSINT investigations. They provide the ability to visualise, analyse, and interpret spatial data, uncovering valuable insights and enhancing overall analysis." – Cyber Huntress
These concepts aren’t just theoretical – they’re incredibly practical. Experts estimate that 80–90% of strategic intelligence is derived from open-source information, and geospatial techniques play a huge role in extracting that value.
Using Geospatial Data for Cyber Threat Analysis
Cybersecurity teams rely on geospatial data to uncover vulnerabilities and track threats. Tools like Shodan and Censys help map digital infrastructure, pinpointing device locations, open ports, and SSL certificates. Metadata analysis, such as extracting GPS coordinates from EXIF data in images, can reveal where a file originated or where a photo was taken.
A real-world example? During the 2022 Russian invasion of Ukraine, the Centre for Information Resilience (CIR) launched the "Eyes on Russia" initiative. By combining satellite imagery with TikTok videos, they tracked military movements, identified vehicle types, and mapped staging areas – often ahead of official military confirmations.
Geospatial intelligence also plays a key role in linking digital activity to physical locations. For instance, researchers investigating Iranian APT group APT33 used WHOIS and passive DNS data to trace command-and-control servers. This analysis tied the servers to locations associated with known threat actors, uncovering a large-scale espionage campaign targeting the aviation and energy sectors.
Databases like GeoNames, with over 11 million place names and geospatial coordinates, provide a solid foundation for geocoding threat data. Teams can refine location accuracy by cross-referencing IP data with time zones and ISP history or by using tools like EXIFTool to extract GPS data from images shared by potential threat actors.
These techniques seamlessly integrate into broader cybersecurity workflows, improving both threat detection and response capabilities.
Adding Geospatial Intelligence to Cyber Workflows
Incorporating geospatial intelligence into cybersecurity processes boosts both the speed and precision of threat detection and response. For instance, teams can set up keyword alerts on social media platforms to monitor for posts with location tags tied to specific terms. This provides real-time situational awareness during unfolding events. Past investigations have shown the effectiveness of such methods, proving their value in rapid response scenarios.
Custom GIS overlays, created with tools like QGIS or ArcGIS Online, allow analysts to combine multiple data layers – such as infrastructure maps, political boundaries, population density, and attack frequency – into a single, cohesive view. This layered approach can reveal connections between physical vulnerabilities and digital attack patterns. For example, mapping exposed cloud storage buckets by region can highlight which data centers or providers are most at risk.
| Tool | Key Function | Cybersecurity Application |
|---|---|---|
| Shodan | Search engine for connected devices | Mapping digital infrastructure and vulnerable ports |
| EXIFTool | Metadata extraction | Identifying GPS coordinates from image files |
| QGIS | Open-source GIS software | Creating custom threat maps and advanced spatial analysis |
| Sentinel Hub | High-resolution satellite data | Monitoring large-scale movements or environmental changes |
The rise of AI-powered OSINT tools is taking these workflows to the next level. Machine learning and computer vision now automate tasks like detecting objects in satellite imagery or scanning social media for emerging threats. This automation dramatically cuts down response times, enabling teams to act within minutes rather than hours – often before a threat has the chance to escalate.
Tools for Geospatial OSINT
Essential Geospatial OSINT Tools for Cybersecurity Threat Mapping
Geospatial OSINT leverages a mix of visualization platforms, mapping databases, and AI-driven tools to monitor infrastructure changes and automate threat detection. These tools work seamlessly within existing workflows, enhancing both visualization and real-time analysis of potential threats.
Google Earth and Satellite Imagery
Google Earth stands out as a go-to resource for high-resolution satellite imagery and 3D terrain visualization. Its historical imagery feature is especially useful for tracking changes over time, such as the construction of data centers, military facilities, or other infrastructure linked to cyber operations. Analysts have used it to document significant developments that hint at potential expansions in digital surveillance.
"Google Earth is ideal for visualizing geographic areas, conducting site reconnaissance, and analyzing historical changes in a location." – Cyber Huntress
Additionally, Google Street View provides ground-level imagery, enabling analysts to verify physical locations and infrastructure details with precision.
OpenStreetMap for Detailed Location Data
OpenStreetMap (OSM) offers a unique advantage over satellite imagery by providing editable vector data enriched with geographic metadata. As a community-driven platform, it delivers up-to-date information on landmarks, transportation systems, and infrastructure, thanks to contributions from users worldwide. This makes it highly effective for tasks such as custom mapping and proximity analyses, like pinpointing all internet exchange points within a 5-mile radius of a vulnerable facility.
"OSM is excellent for creating detailed maps, integrating geographic data into other applications, and conducting geospatial analysis." – Cyber Huntress
The platform’s API allows seamless integration of geographic data into custom GIS overlays and threat dashboards. Its open-source nature means organizations can develop specialized tools tailored to their unique threat landscapes – whether that’s mapping exposed IoT devices in urban areas or correlating cyberattack origins with nearby infrastructure. Together, tools like Google Earth and OSM form the foundation for advanced intelligence layers like The Security Bulldog.
The Security Bulldog for Threat Mapping
Taking geospatial OSINT a step further, The Security Bulldog injects actionable insights directly into threat analysis workflows. While platforms like Google Earth and OpenStreetMap excel at visualization, The Security Bulldog simplifies the OSINT process by combining mapping capabilities with intelligence gathering. Its natural language processing (NLP) engine pulls critical data from sources like MITRE ATT&CK and CVE databases, filtering out irrelevant information.
One of the platform’s key advantages is its ability to tackle data overload. Instead of manually reviewing countless threat reports to uncover geographic patterns, The Security Bulldog’s machine learning algorithms identify emerging risks and link them to specific locations in real time. Teams can create tailored feeds that align with their IT environments, ensuring that the intelligence is not only relevant but also actionable. By integrating with existing SOAR and SIEM tools, these geospatial insights flow directly into detection and response workflows, streamlining threat management and response.
Techniques for Mapping Cyber Threats with Geospatial OSINT
Building on foundational concepts, these techniques illustrate how geospatial intelligence can be transformed into actionable threat mapping strategies.
IP Geolocation Tracing
IP addresses, when combined with domain and certificate data, offer valuable geographic insights. This digital trail allows analysts to track an adversary’s activities across various regions and link malicious actions to specific threat groups. Automated machine learning tools are particularly effective at correlating IP data with geographic locations. Additionally, active methods like public malware sandboxing and certificate lookups provide deeper insights for targeted threat investigations.
Geotagging and Social Media Analysis
Social media platforms are a goldmine of geotagged content, often revealing the real-time locations and movements of threat actors. Analysts monitor keyword alerts to capture incidents as they unfold, extracting geotag data from shared photos and videos. These visual clues are then verified using street-level imagery tools to ensure accuracy. Metadata, such as EXIF, IPTC, and XMP, provides GPS coordinates and timestamps, which can be directly mapped. Tools like Google MyMaps allow teams to plot this data, creating shareable and interactive visual maps of incidents.
Once the geographic data is gathered, GIS overlays play a critical role in turning it into actionable intelligence.
GIS Overlays for Threat Visualization
GIS overlays take raw geographic data and transform it into clear, visual intelligence by layering multiple data points onto maps. The table below highlights key GIS overlay techniques and their cybersecurity applications:
| GIS Overlay Technique | Cybersecurity Application | Key Advantage |
|---|---|---|
| Heatmaps | Visualizing attack density | Highlights geographic hotspots of malicious activity |
| Geofencing | Perimeter monitoring | Sends alerts for activity within virtual boundaries |
| Infrastructure Layering | Risk assessment | Links cyber threats to physical assets |
| 3D Visualization | Site reconnaissance | Provides realistic context for combined physical and cyber security |
| Movement Analysis | Tracking threat actors | Reconstructs movement paths and predicts future locations |
Platforms like The Security Bulldog enhance these techniques by integrating geospatial overlays with live threat feeds. Historical imagery can reveal changes in infrastructure that might indicate emerging threats. Additionally, resources like the GeoNames database, which includes over 11 million place names with coordinates, ensure precise location matching.
Case Studies: Geospatial OSINT in Action
Real-world examples highlight how geospatial intelligence transforms threat data into actionable defenses. These case studies showcase the practical impact of geospatial OSINT in cybersecurity.
Identifying Attack Patterns Across Regions
In September 2025, SentinelLABS and enterprise CTI teams uncovered a Lazarus Group campaign targeting over 230 cryptocurrency professionals. By combining OSINT with geospatial data – like mapping IP addresses to countries and ASNs – analysts exposed the infrastructure supporting malware such as InvisibleFerret. This enabled rapid countermeasures to mitigate the threat.
Earlier that year, in March 2025, Bybit suffered a massive $1.5 billion heist orchestrated by the Lazarus Group. Using geospatial forensics and tools like Validin, investigators uncovered the group’s command-and-control infrastructure and tracked asset redeployment efforts.
"Analysis across ~3 years of related OSINT exposed a dense web of linked personas, indicators, infrastructure, and campaigns." – CyberCrank
These examples demonstrate how geospatial data reveals regional attack patterns, but its utility doesn’t stop there – it also aids in tracking individual threat actors.
Tracking Threat Actors Using Geographic Data
Geospatial intelligence goes beyond identifying regional trends; it can also track the movements of specific threat actors. For instance, in early 2023, the threat group VOLTZITE infiltrated a U.S. utility, exfiltrating GIS data, SCADA configurations, and OT assets. In response, the utility deployed Dragos to monitor IT-OT traffic. This allowed analysts to detect VOLTZITE’s "living off the land" tactics and neutralize threats before they could disrupt essential operations.
Another example occurred in May 2025, when DTEX released a report titled "Exposing DPRK’s Cyber Syndicate." The report detailed how North Korean "Hidden IT Workers" infiltrated the tech and finance sectors by falsifying their locations. To counter this, HR teams collaborated with CTI experts to verify geolocations during interviews and monitored remote access endpoints for unusual geographic activity. This approach extended geospatial verification into areas like hiring and identity validation.
"VOLTZITE has been observed performing reconnaissance and enumeration of multiple U.S.-based electric companies since early 2023, and since then has targeted emergency management services, telecommunications, satellite services, and defense industrial bases." – Josh Hanrahan, Principal Adversary Hunter, Dragos
Best Practices and Advanced Visualization Techniques
Ensuring Data Accuracy and Reliability
Don’t rely on just one source. To ensure accuracy, cross-check information by combining multiple sources like social media posts, satellite imagery, and ground-level photos. This approach helps verify details such as location, timestamps, and device metadata.
"Skilled practitioners do not rely on a single source but instead confirm findings using multiple independent sources. This process helps ensure the accuracy and reliability of the intelligence being produced." – Nico Dekens, "Dutch Osint Guy"
Double-check metadata carefully. Tools like ExifTool can extract crucial details such as GPS coordinates, timestamps, and camera information. These details can then be cross-referenced with historical weather data for further validation.
Verify infrastructure claims. Use crowdsourced databases like WiGLE.net to map Wi-Fi SSIDs and BSSIDs, and perform IP geolocation lookups to confirm location assertions. Make sure to document timestamps, URLs, and source data to meet evidentiary standards. Once the data’s reliability is confirmed, it can then be transformed into actionable insights through advanced visualization techniques.
Using Advanced Visualization Tools
After ensuring data accuracy, visualization tools can turn raw information into clear, actionable maps. Tools like Google Earth and QGIS are excellent for converting datasets into visual maps. Use features such as 3D terrain visualization and historical imagery to track changes over time and create heatmaps for spatial analysis.
Incorporate real-time data and overlays. Temporal overlays can help map activity timelines, making it easier to connect behaviors with real-world events. Platforms like ArcGIS Online enable real-time monitoring, while tools like Cree.py and Maltego can link geospatial data with digital artifacts to provide a comprehensive picture.
Conclusion
Key Takeaways
Geospatial OSINT is reshaping how cybersecurity teams operate by adding a geographic lens to digital intelligence. This guide explored how tools like satellite imagery, IP geolocation, social media analysis, and metadata extraction can uncover the origins of threats and reveal attack patterns.
From platforms like Google Earth and OpenStreetMap to advanced GIS overlays and AI-powered analysis, these techniques empower security teams to locate threat actors, map digital infrastructure, and verify attribution with a level of precision that’s hard to match. Real-world cases, such as the Centre for Information Resilience’s tracking of military activity and the investigation into APT33’s command-and-control systems, highlight how geospatial OSINT provides actionable intelligence in high-stakes scenarios.
"The future of intelligence gathering is not just open. it’s intelligent." – Ahmed Rashwan, Freelance Copywriter, CYBNODE
Next Steps for Cybersecurity Teams
To stay ahead of evolving threats, it’s crucial to put these insights into action.
Start by identifying geospatial data sources that align with your specific threat landscape. Use machine learning tools to automate data collection and handle the vast amount of public information available. Then, integrate geospatial intelligence seamlessly into your current security workflows.
Platforms like The Security Bulldog can simplify this process by combining open-source cyber intelligence with geographic insights. Its AI-driven natural language processing engine can save your team valuable time, speeding up threat detection by connecting geospatial data to broader intelligence. Begin with passive reconnaissance to map your organization’s external attack surface, and then expand into active monitoring using these visualization techniques.
FAQs
How does geospatial OSINT enhance cybersecurity threat detection?
Geospatial OSINT adds a powerful location-based layer to cybersecurity by linking cyber threats to specific physical locations. This method allows analysts to spot patterns and connections that might otherwise go unnoticed. For example, it can reveal clusters of compromised IP addresses tied to certain regions or highlight ransomware activity concentrated in particular geographic areas.
Using tools like satellite images, geotagged social media data, and image metadata, security teams can track the origins of attacks, follow the movements of malicious actors, and even identify physical changes – like the construction of new infrastructure – that could signal a developing threat. This kind of intelligence provides a clearer picture, enabling quicker decisions and more targeted responses.
The Security Bulldog incorporates geospatial OSINT into its AI-driven platform, automatically linking location-tagged data with threat indicators and vulnerabilities. This integrated approach helps security teams focus on the most pressing risks, cut down investigation times, and handle threats with greater precision.
What tools are used in geospatial OSINT to map cyber threats?
Geospatial OSINT analysts rely on a range of tools to turn location data into meaningful insights that help map cyber threats. These tools often include geospatial visualization platforms, which compile and display location coordinates to reveal patterns and hotspots of malicious activity. For instance, tools like Cree.py allow users to map geographic data from various online sources, while resources such as the OSINT Framework provide access to satellite imagery, social media monitoring tools, and web-camera feeds.
Key features of these tools include high-resolution satellite imagery to pinpoint critical infrastructure, real-time web-camera feeds for observing physical activities, and social media monitoring to track geotagged posts. By combining these capabilities, cybersecurity teams can link digital threats to physical locations, monitor potential attacker movements, and respond to risks with greater precision.
How can geospatial OSINT be integrated into existing cybersecurity workflows?
Geospatial OSINT can fit right into your existing cybersecurity processes, adding a valuable layer of location-based insights to your threat analysis. By tapping into resources like satellite imagery, public-camera feeds, and geo-tagged social media posts, security teams can incorporate spatial data to better identify the locations of malicious actors, compromised systems, or unusual activities.
The Security Bulldog streamlines this integration with its AI-driven NLP engine, which processes and standardizes geospatial OSINT data. It connects seamlessly with widely-used tools like SIEM platforms and ticketing systems, ensuring these insights appear directly in your current dashboards. This enables teams to map out threats, focus on high-priority investigations, and even automate responses – all without interrupting their usual workflow. The outcome? Quicker decisions and a more complete understanding of the threat landscape.