Kayhan Space Investigates Satellite Intelligence for CNN with CesiumJS
In March 2026, Iran struck Prince Sultan Air Base near Riyadh, Saudi Arabia, wounding US servicemembers and damaging aircraft. CNN journalists hypothesized that Russian satellites supported Iran’s intelligence before the attack. To evaluate this possibility, reporters worked with Kayhan Space, a spaceflight safety, operations, and intelligence company. Kayhan used its flagship product Satcat, whose geospatial and orbital visualization is built on CesiumJS, to verify satellite capabilities and behavior.
Kayhan Space uses CesiumJS in Satcat. The team, with Satcat AI Analyst, examined Russian satellite capabilities and behavior, assisting CNN in reporting that Iranian attacks on Prince Sultan Air Base in March 2026 may have been supported by Russian intelligence. Courtesy Kayhan Space.
Colorado-based Kayhan Space was founded in 2019 as a spaceflight safety company. One of its first flagship products, Pathfinder, was launched in 2022, with orbital visualization built on Cesium. As Kayhan expanded to deliver satellite operations capabilities and analytics, Pathfinder’s capabilities were integrated into Satcat in 2024 alongside new intelligence tools and public-facing features, making parts of the platform available to the public for the first time. Satcat’s geospatial and orbital visualization is built on CesiumJS. The tool’s spaceflight safety capabilities provide operator coordination, risk assessment reports for close approaches, and recommendations for mitigating risk, aligning with operators’ workflows.
Despite its vastness, space is a busy place, and information can be noisy: Are numbers calculated correctly? Does the data adhere to standards? What is this spacecraft’s history? Is it behaving normally? Is its owner friendly or an adversary? And, of course, what do you want to do about it?
Some of Kayhan Space’s users are Capella Space, AST SpaceMobile, NOAA, and now CNN.
COSMOS 2573 is a Russian EO satellite. This simulation shows satellite paths and visibility cones. Courtesy Kayhan Space.
Hyun Seo, Chief Product Officer at Kayhan Space, employed an AI-assisted analysis tool within Satcat to begin examining capabilities and behavior of the entire Russian satellite fleet. “What Russian satellites had the best visibility over Prince Sultan Air Base in March?” he prompted the AI.
Working with the CNN team, Seo dug in to fact-check the results and use Satcat to build accurate 3D simulations, based on time of day, weather, orbit, and satellite function. Inactive satellites as well as navigation and communications satellites, for example, moved off the list, but electro-optical (EO), synthetic aperture radar (SAR), radio frequency (RF), and infrared (IR) were in play.
Seo recorded the simulations directly from the app, moving from analysis to broadcast-ready visualization, and used only public data so that CNN journalists could repeat his steps—verifying in 3D with their own tooling and sources, vital for accurate reporting. Seo also created primers on EO, SAR, RF, and IR for the CNN broadcast, including the Cesium globe for geospatial context and visual consistency but with larger-than-life models of the satellites for illustration for a broad audience.
Seo created primers on EO, SAR, RF, and IR for CNN’s broadcast. Courtesy Kayhan Space.
Satcat gets public data on spacecraft and debris ownership, launch, position, weather, mission, and more from Space-Track, Celestrak, NOAA, the European Space Agency, and other providers. Position data comes as TLEs with SGP4 propagation, and users can add proprietary data for their own constellations. Privileged access gives users the SP Catalog from the US Space Force with synthetic covariance as well as owner/operator ephemerides. Instead of separate spreadsheets, Satcat fuses data streams with a 3D globe in CesiumJS for accurate, immersive visualization and analysis in a browser.
“We get value from the tech, Sandcastles and reference material, and community. Even with AI coding tools, it’s just not worth using something else. We use Cesium because we’re not just concerned with the visualization but with the maths,” said Seo.
The 3D models of satellites Seo shared with CNN are glTF/glb. The models were not streamed with the simulation; CNN added the models to the recording for the broadcast. The underlying data and orbit paths remained grounded in Kayhan Space’s analysis, so reporters used real space data as evidence of Russian intelligence support ahead of Iranian missile attacks on Prince Sultan Air Base.
3D model of a Bars-M EO satellite for Russian military intelligence, like Cosmos 2573. Courtesy Kayhan Space.
With accurate data visualized and analyzed in Kayhan Space’s CesiumJS-powered Satcat, journalists were able to verify information and create a visual story viewers could understand. You can watch the full CNN Investigates clip here.
Detail and accuracy are foundations of the Cesium platform. Learn to build your own time-dynamic visualization and simulation app for space with CesiumJS.