Images and Video Purporting to Show Iran Capturing Israeli and American Soldiers Were Generated Using Artificial Intelligence

On April 12, 2026, a 36-second video related to the war involving Iran, Israel, and the United States was posted on X under the username @MariaAlkaff_. The video purportedly shows Iranian soldiers capturing Israeli soldiers and depicts the treatment of the captured personnel. The post received 337 comments, was reposted 1,300 times, garnered 3,200 likes, and accumulated approximately 117,000 views.

 

However, the video is not authentic and was generated using artificial intelligence. It was initially analyzed using Google SynthID, which identified multiple indicators suggesting AI generation. In particular, inconsistencies in content, contextual coherence, and visual accuracy indicated that the footage had been produced using various AI-based tools.

In addition to SynthID, the video was examined using HIVE Moderation, another AI detection platform. The results from HIVE Moderation corroborated the initial findings, confirming that the video was generated through artificial intelligence.

 

 

A similar image was also shared on Facebook and Instagram on April 3, 2026. The accompanying claim alleged that the image depicted an F-35 pilot shot down by Iran on April 3, 2026, during interrogation.

Like the video shared on April 12, this image was also generated using artificial intelligence. Analysis conducted with SynthID revealed several anomalies—such as irregular physical features, lighting inconsistencies, and unusual environmental details within the interrogation setting—indicating AI production. Further examination using HIVE Moderation determined that the image was 92.5% likely to have been AI-generated.

 

In conclusion, both the image shared on April 3 and the video posted on April 12 are not authentic; both were created using artificial intelligence.

If you suspect that a video, image, or audio file has been created using artificial intelligence or deepfake technology and would like free assistance in verifying its authenticity, you may send the link to the content or the file itself to allaboutdeepfake@gmail.com.

The Same AI-Generated Video Reposted with Different War Claims

On May 4, 2026, several news websites published reports alleging that Iran had struck a U.S. warship. However, the U.S. Central Command (CENTCOM) denied these claims and issued an official statement confirming that no such attack had occurred.

Despite this clarification, numerous social media users—primarily on X—shared videos purporting to show Iran attacking a U.S. naval vessel. One such video was posted on May 4, 2026, by the user @almohamadawi31.

Within 15 hours, the video had been viewed more than 107,000 times, reposted 543 times, and received over 1,400 likes. Subsequent analysis revealed that the footage was not authentic but had been generated using artificial intelligence. A review conducted using HIVE Moderation confirmed that the video was AI-generated.

The same AI-generated video, originally shared on May 4, 2026, was reposted on June 4, 2026, by the user @RussianArmys. In this instance, the accompanying claim alleged that Russia had launched a devastating missile attack on the U.S. aircraft carrier USS Abraham Lincoln, completely destroying the vessel and killing more than 200 personnel. The reposted video received over 107,200 views and more than 309 likes.

However, technical verification confirmed that the reposted footage was identical to the video circulated on May 4 and was entirely AI-generated. This case illustrates how the same synthetic content can be repurposed at different times and attributed to entirely different conflicts. Moreover, a review of posts from the account @RussianArmys indicates a consistent pattern of sharing unverified claims, fake news, disinformation, and AI-generated media.

In conclusion, both the video claiming that Iran attacked a U.S. warship and the video alleging a Russian attack on the USS Abraham Lincoln were generated using artificial intelligence. The repeated circulation of identical AI-generated content under different geopolitical conflicts demonstrates how easily synthetic disinformation can spread across social media platforms. Therefore, especially in the context of military conflicts and international crises, it is essential to verify visual content using reliable sources and technical detection tools.

If you suspect that a video, image, or audio file has been created using artificial intelligence or deepfake technology and would like free assistance in verifying its authenticity, you may send the link to the content or the file itself to allaboutdeepfake@gmail.com.

AI-Generated Explosion Video Circulates on Social Media

 On May 31, 2026, a 13-second video was posted on X by @Persianserene1. The post claimed that the footage depicted an explosion following an attack on Iran by U.S. and Israeli aircraft.

The video garnered significant attention, accumulating over 94,100 views, more than 4,700 likes, and over 1,300 reposts. However, subsequent investigation revealed that the footage was generated using artificial intelligence. An analysis conducted with HIVE Moderation confirmed that the content was AI-generated.

 

The post on X indicated that the video had previously been shared on Instagram, suggesting that it did not originate on X and had circulated across multiple social media platforms. A reverse image search was therefore conducted, which determined that the video was first uploaded to Instagram on May 30, 2026, by a user identified as “javadi__1364.”

In conclusion, the short video shared on X on May 31 was artificially generated and does not depict a real event. This case illustrates how AI-generated content can be recirculated by different users across various social media platforms for disinformation purposes. It underscores the critical importance of verifying the authenticity of visual content, particularly during periods of conflict and geopolitical tension.

If you suspect that a video, image, or audio file has been created using artificial intelligence or deepfake technology and would like free assistance in verifying its authenticity, you may send the link to the content or the file itself to allaboutdeepfake@gmail.com.

AI-driven fraud as an emerging cyber risk: Evidence from a global incident-based analysis

The rapid proliferation of artificial intelligence (AI) and deepfake technologies has introduced new and complex risks to individuals, companies, financial systems, and digital trust. While existing research has primarily examined deepfakes in sexual or political contexts, systematic analyses of AI-enabled fraud remain limited. This study addresses this gap by conducting an incident-based analysis of 167 documented cases of AI- and deepfake-enabled fraud worldwide between 2019 and 2025. Drawing on Cyber-Routine Activities Theory (C-RAT), the study examines temporal trends, victim targeting patterns, financial losses, and cross-national variations to assess how emerging AI technologies reshape opportunity structures for cybercrime. The findings reveal a sharp increase in AI-assisted fraud after 2022, coinciding with the public availability of generative AI tools. Victimization patterns shifted from companies toward individuals, while financial losses initially concentrated among companies before increasingly affecting individual victims. Country-level analysis highlights substantial variation, including evidence that targeted regulatory interventions can reduce exposure to AI-enabled fraud, as demonstrated in the People’s Republic of China. Overall, the results support C-RAT’s core assumptions regarding motivated offenders, suitable targets, and capable guardianship, while extending the theory to account for AI-driven cyber threats and systemic forms of guardianship. The study emphasizes that AI-enabled fraud represents a structural social risk inherent in modern digital infrastructures. Effective mitigation requires multi-layered strategies integrating technical controls, organizational investment in cybersecurity, and adaptive regulatory governance.

LINK: https://www.tandfonline.com/doi/full/10.1080/07366981.2026.2631066

Exploring the Reflection of the Definitional Problem of Terrorism in Public Opinion Using Wikipedia Data

Abstract

Terrorism is a global issue, particularly after the 9/11 attacks in the United States. Despite the global attention, there is no common definition of terrorism, as what one country defines as a terrorist is considered a freedom fighter by another. However, the impact of a country's attitude towards such organizations on people's perceptions and discourse has not been thoroughly explored. Accordingly, this study examines Wikipedia content related to the People's Defense Units (YPG), an organization recognized as a terrorist entity by some countries but not defined as such by others. Turkish Wikipedia content about YPG, representing Türkiye, which recognizes YPG as a terrorist organization, is compared with English Wikipedia content about YPG, a viewpoint held by countries like the USA and the UK, which do not recognize it as a terrorist organization. Additionally, Turkish and English content related to the Islamic State of Iraq and Syria (ISIS), recognized as a terrorist organization worldwide, is also examined using the sentiment analysis. The analysis reveals that the dominant sentiment in Turkish Wikipedia content related to YPG, representing Türkiye that recognizes YPG as a terrorist organization, is negative, while the dominant sentiment in English Wikipedia content is positive. Conversely, the prevalent emotion in both Turkish and English Wikipedia content about ISIS, universally acknowledged as a terrorist organization, is negative. In summary, the study finds that the attitudes and opinions of countries towards an organization are reflected in society, and the public's attitude towards the organization in the country they reside in also influences the discourse about that organization.

LINK: https://dergipark.org.tr/en/pub/ijshs/issue/89666/1614095