Nigeria was among 11 countries that participated in an international counter-terrorism operation that used artificial intelligence to identify 126 suspected foreign terrorist fighters from more than 108,000 facial images obtained from jihadist content online.
Codenamed Operation Shams II, the five-day operation was coordinated by the International Criminal Police Organisation, INTERPOL, in Tunis, Tunisia, from June 1 to 5, 2026.
The operation brought together 28 specialised law enforcement officers and experts from Nigeria, Côte d’Ivoire, Ghana, Iraq, Kenya, Malaysia, the Philippines, Qatar, Tajikistan, Tunisia and Uzbekistan.
According to INTERPOL, the operation was aimed at disrupting terrorist networks and their financing by strengthening international investigations in the digital space.
During the exercise, officers extracted 108,076 facial images from visual materials published online by jihadist groups.
AI agents and AI-generated scripts were subsequently deployed to automate parts of the data-gathering and investigative process. The technology was used to remove duplicate photographs and assess the quality of the images.
Following the automated screening, the number of images was reduced to 6,362 unique, high-quality facial images, which were then processed through INTERPOL’s facial recognition system.
The organisation, however, stressed that the results generated with the assistance of AI were not accepted without human review.
It said trained officers and analysts examined and verified the results in accordance with INTERPOL’s rules governing the processing of data.
Additional intelligence provided by INTERPOL’s National Central Bureau in Baghdad, Iraq, also included hundreds of images associated with terrorism suspects.
INTERPOL said the exercise had so far led to the identification of 126 foreign terrorist fighters from the images processed during the operation.
“These matches will enrich existing intelligence on suspects, including potential locations and social networks,” the organisation said.
It added that the information was being integrated into its databases to strengthen international efforts to detect, track and disrupt the movement of terrorist suspects across borders.
INTERPOL further disclosed that investigative leads generated during the operation were already being used to support judicial proceedings in participating countries.
One of the cases involves two suspected foreign terrorist fighters who are currently in detention, while thousands of additional images remain to be processed and could provide further investigative leads.
The operation also focused on terrorist financing, with investigators using cryptocurrency-tracing tools to follow suspected illicit financial flows.
According to INTERPOL, the financial investigation resulted in three urgent requests to a virtual asset service provider for customer information as authorities sought to disrupt suspected terrorist financing channels.
The participating countries also held discussions with representatives of the online gaming industry over concerns about the potential radicalisation of young people through online platforms.
INTERPOL Director of Counter-Terrorism, María Carmen Muñoz González, said the operation demonstrated the potential of combining international police cooperation with responsible use of AI-assisted analytical tools.
“The success of Operation Shams II demonstrates the value of combining international law enforcement cooperation with responsible AI-assisted analytical capabilities,” she said.
Muñoz González added that the approach adopted during the operation could serve as a model for future international law enforcement exercises targeting criminal networks.
Operation Shams II was conducted under the CT TECH+ Project, funded by the European Union’s Foreign Policy Instruments and supported by the United Nations Office of Counter-Terrorism.
INTERPOL described the exercise as the first operation of its kind to deploy AI-assisted capabilities on such a large scale to process terrorist-related visual content and generate investigative leads.
