Interpol uses AI to identify 126 suspected terrorists in multinational operation

Yesterday 19:00

Interpol has identified 126 suspected terrorists through an investigation that combined artificial intelligence, facial recognition and international police cooperation, highlighting the growing role of advanced technologies in efforts to track terrorism networks.

The operation, known as Shams II, brought together law enforcement specialists and technology experts from 11 countries during a five-day operation conducted in Tunis from June 1 to 5.

AI transforms the analysis of extremist imagery

According to Interpol, the operation involved 28 specialists from Côte d’Ivoire, Ghana, Iraq, Kenya, Malaysia, Nigeria, the Philippines, Qatar, Tajikistan, Tunisia and Uzbekistan.

Investigators collected more than 108,000 facial images from visual material published online by jihadist organizations. AI-powered agents and advanced scripts were used to automate parts of the data-gathering and investigative process.

The technology helped investigators identify duplicate images and assess the quality of the material before it entered Interpol's facial-recognition system.

After this initial filtering, investigators extracted 6,362 unique, high-quality images for further analysis.

Human analysts remain central to the process

Despite the extensive use of artificial intelligence, the identification process did not rely solely on automated decisions.

Interpol said AI-generated results were subsequently reviewed and verified by trained police officers and analysts. The additional human assessment was intended to examine the matches produced by the technological systems before they could be used as investigative leads.

The operation also benefited from intelligence supplied by Interpol's National Central Bureau in Baghdad. Iraqi authorities contributed a large body of terrorism-related intelligence, including hundreds of additional images that could be analyzed through the same process.

More identifications could follow

The 126 identifications announced by Interpol may not represent the final outcome of the operation.

The agency said thousands of additional images still need to be processed, meaning the number of identified individuals could increase over the coming months as investigators continue examining the available material.

The people targeted by this work fall within the broader category of foreign terrorist fighters, a term used by the United Nations for individuals who travel outside their country of residence or nationality with the intention of committing, organizing or preparing terrorist acts, participating in them, or receiving or providing terrorist training, including in the context of armed conflicts.

Interpol has not released the identities or nationalities of the 126 people identified. It has also not specified whether any of them have already been arrested.

Cryptocurrency analysis adds another investigative layer

The Shams II operation was not limited to facial recognition.

Investigators also employed advanced cryptocurrency-analysis tools to follow potential illicit financial flows linked to terrorism.

The combination of biometric identification, digital investigation and financial intelligence illustrates how international law enforcement agencies are increasingly bringing together different technological tools to process large volumes of information.

European and UN-backed initiative

Shams II was financed through European Union foreign-policy instruments and supported by the United Nations Office of Counter-Terrorism (UNOCT).

The operation was conducted as part of the CT Tech+ project, placing artificial intelligence and other digital technologies within a broader international framework for counter-terrorism cooperation.

The results also underline the importance of combining automated technologies with trained investigators. While AI can rapidly process and organize vast quantities of visual data, final investigative assessments remain dependent on human verification and international police cooperation.