Fact Check: AI-Generated Video of a Girl’s Rescue Falsely Linked to the 2026 Nepal Floods

 

On August 26, 2026, a massive flood occurred along the Nepal-China border. Following the disaster, many social media users shared images and videos purportedly related to the flooding. However, some of this content was unrelated to the disaster, shared in a misleading context, or generated using artificial intelligence.

One such example is a video shared on X on September 1, 2026, by a user named alfuratyalatiqe. The 30-second video allegedly shows a young girl being rescued from beneath rubble during the floods in Nepal. The video is emotionally striking, as the girl is completely covered in mud and appears to be in distress. Furthermore, the footage appears highly realistic, potentially making it difficult for viewers to recognize that it was generated using artificial intelligence. The video has been viewed more than 6,200 times, reposted five times, and liked 30 times.

 

However, a subsequent investigation revealed that the video was not authentic and had been generated using artificial intelligence. To assess the authenticity of the footage, the video was examined using HIVE Moderation and UncovAI.

The video was initially analyzed using HIVE Moderation, which identified significant indicators that the footage had been generated using artificial intelligence.

 

The video was subsequently analyzed using UncovAI. Consistent with the findings from HIVE Moderation, UncovAI also identified the footage as AI-generated. The results from both detection tools therefore provide evidence that the video does not authentically document a rescue operation during the Nepal floods.

 

Frames from the video were also examined using Google’s reverse image search to determine whether the footage had previously appeared online. The investigation revealed that the video had been shared not only by alfuratyalatiqe but also by numerous other users on X. Furthermore, the footage had circulated beyond X and appeared on several other social media platforms. For example, the video was also uploaded to Instagram. Images or footage from the video were additionally shared on Facebook and YouTube.

The circulation of the same AI-generated content across multiple platforms demonstrates how synthetic disaster footage can spread beyond a single social media account and potentially reach substantially larger audiences. Its realistic appearance and emotionally compelling subject matter may further increase the likelihood that viewers perceive the footage as authentic documentation of a real rescue operation.

In conclusion, the investigation indicates that the viral video does not authentically show a young girl being rescued during the August 2026 floods in Nepal. Analyses using HIVE Moderation and UncovAI identified the footage as AI-generated.

This case demonstrates how realistic and emotionally compelling AI-generated videos can be falsely associated with real disasters and spread across social media. It highlights the importance of verifying the authenticity and context of viral footage before sharing it.

 

 

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

Fact Check: Misleading Nepal Flood Video Mixes AI-Generated Content With Real Footage

On August 26, 2026, a massive flood occurred along the Nepal-China border. Following the disaster, many social media users shared images and videos purportedly related to the flooding. However, some of this content was unrelated to the disaster, shared in a misleading context, or generated using artificial intelligence.

One such example is a video shared on X on August 31, 2026, by a user named ReddyKriti70747. The 30-second video allegedly shows people being rescued from the floods in Nepal. After being posted, the video was viewed more than 573,100 times, reposted over 2,200 times, and liked more than 13,000 times.

 

However, a subsequent investigation revealed that the video combines AI-generated content with authentic but unrelated footage. Specifically, the first nine seconds of the video were identified as AI-generated, while the remaining segments appear to contain authentic footage unrelated to the Nepal floods. To assess the authenticity of the content, the video was examined using Gemini and UncovAI.

The video was initially analyzed using Gemini, which identified AI-generated content in the footage. Gemini highlighted several potential indicators of AI generation, including physical anomalies and inconsistencies between the audio and visual elements.

The footage was subsequently analyzed using UncovAI, which also detected AI-generated content. The findings from both tools therefore indicate that the video does not consist entirely of authentic documentation of the Nepal floods. Instead, it combines an AI-generated segment with authentic but unrelated footage and presents them together as if they depict rescue operations during the disaster.

This combination of synthetic and authentic but unrelated footage makes the video particularly misleading, as genuine visual elements can lend credibility to fabricated content and make it more difficult for viewers to distinguish between real and AI-generated scenes.

In conclusion, the video is misleading. It does not authentically document rescue operations during the August 2026 Nepal floods. The first nine seconds were identified as AI-generated, while the remaining segments appear to consist of authentic but unrelated footage. By combining AI-generated scenes with real footage from unrelated events and presenting them as a single account of the Nepal floods, the video creates a false impression of what actually occurred.

 

 

 

 

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

Fact Check: AI-Generated Image Falsely Presented as the Girne Port Passenger Ship Accident

On August 30, 2026, a passenger ship en route to Taşucu, Mersin, capsized at Girne Port in Northern Cyprus. The accident resulted in fatalities and injuries, with some passengers reported missing. Following the incident, numerous related posts began circulating on social media. While many of these posts contained authentic news reports and images, others included content generated using artificial intelligence.

One example of such content appeared on X. On August 31, 2026, a user named aynuresultanova shared an image purportedly showing the site of the accident. The post containing the image was viewed more than 28,300 times, reposted 17 times, and liked 386 times.

 

However, a subsequent investigation revealed that the image was not authentic and had been generated using artificial intelligence. To assess its authenticity, the image was examined using HIVE Moderation and UncovAI.

The image was first analyzed using HIVE Moderation, which indicated that it had been generated using artificial intelligence.

 

The image was then independently analyzed using UncovAI, another AI-detection tool. UncovAI also indicated that the image was AI-generated, supporting the findings of the HIVE Moderation analysis.

Taken together, the results from both AI-detection tools indicate that the image does not authentically depict the site of the passenger ship accident in Girne Port, despite being presented on social media as an image of the real event.

In conclusion, the investigation indicates that the image circulating on X does not authentically depict the passenger ship accident at Girne Port in Northern Cyprus. Analyses conducted using HIVE Moderation and UncovAI both indicated that the image was generated using artificial intelligence. Although the ship accident itself was a real event, the image presented as showing the scene of the disaster was artificially created.

This case demonstrates how AI-generated images can be attached to real breaking-news events and presented as authentic visual evidence. Such content can be particularly misleading because it combines a genuine event with fabricated imagery, making it more difficult for viewers to distinguish between authentic reporting and synthetic content. The example highlights the importance of verifying the authenticity and source of images before sharing them, especially during rapidly developing news events.

 

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

Fact Check: AI-Generated Video of Grieving Children Falsely Linked to the 2026 Nepal Floods

On August 26, 2026, a massive flood occurred along the Nepal-China border. Following the disaster, many social media users shared images and videos purportedly related to the flooding. However, some of this content was unrelated to the disaster, shared in a misleading context, or generated using artificial intelligence.

One such example is a video shared on X on August 30, 2026, by a user named LostInMaybe0. The 26-second video allegedly shows two young children who lost their family in the floods in Nepal. The video is particularly emotional, as it appears to portray the children grieving the loss of their family. In addition, the footage appears highly realistic, which may make it difficult for viewers to recognize that it is AI-generated. The video has been viewed more than 508 times, reposted twice, and liked once.

 

 

However, a subsequent investigation revealed that the video was not authentic and had been generated using artificial intelligence. To assess the authenticity of the footage, the video was examined using Gemini, HIVE Moderation, and BioID.

The video was initially analyzed using Gemini, which determined that the content had been generated using artificial intelligence. Gemini identified several potential indicators of AI generation, including morphing, anatomical anomalies, and unnatural elements in the background.

The video was subsequently analyzed using HIVE Moderation, which also indicated that the footage was AI-generated.

 

Because the footage appeared highly realistic, it was additionally analyzed using BioID, another AI detection tool. The BioID analysis produced findings consistent with those of Gemini and HIVE Moderation, concluding that the video had been generated using artificial intelligence.

 Frames from the video were also examined using Google’s reverse image search to determine whether the footage had previously appeared online. The investigation revealed that the video had been shared not only by LostInMaybe0 but also by numerous other users on X. Furthermore, the footage had circulated beyond X and appeared on several other social media platforms. For example, the video was also uploaded to Instagram.

Notably, the video also appeared on the websites of news organizations. For example, NTV published the footage on its website on August 30 under the headline “Nepal Disaster Little Boy Searches Parents Holding Sister.” The circulation of the video by news outlets is particularly significant because it demonstrates how realistic AI-generated content can move beyond social media and enter the broader news ecosystem. As a result, such content may reach audiences who assume that footage published by established media organizations has already been verified.

In conclusion, the investigation indicates that the viral video does not authentically depict two children who lost their family during the August 2026 floods in Nepal. Analyses conducted using Gemini, HIVE Moderation, and BioID consistently indicated that the footage was generated using artificial intelligence. Despite being AI-generated, the video appears highly realistic and uses an emotionally powerful narrative involving children who supposedly lost their family in a real natural disaster.

The fact that the video circulated across multiple social media platforms and was subsequently published by a news organization demonstrates how AI-generated content can move from social media into the broader news ecosystem. This case also illustrates how emotionally compelling AI-generated imagery can exploit real human tragedies, potentially making misleading content more persuasive and more likely to be shared. As generative AI produces increasingly realistic footage, verifying the authenticity, source, and context of visual content is essential—particularly during natural disasters and other breaking news events.

 

 

 

 

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

Fact Check: Partly AI-Generated Video Misrepresented as Authentic Footage of the 2026 Nepal Floods

On August 26, 2026, a massive flood occurred along the Nepal-China border. Following the disaster, many social media users shared images and videos purportedly related to the flooding. However, some of this content was unrelated to the disaster, shared in a misleading context, or generated using artificial intelligence.

One such example is a video shared on X on August 29, 2026, by a user named Riyaz_H_Khan. The 15-second video purportedly shows scenes from the flood disaster in Nepal. Within one hour of being posted, the video had been viewed more than 1,025 times, reposted seven times, and liked 18 times.

 

However, a subsequent investigation revealed that the video contains both AI-generated and authentic footage. Specifically, the first five seconds of the video were identified as AI-generated, while the remaining footage appears to be authentic. To assess the authenticity of the content, the video was examined using HIVE Moderation and UncovAI.

The video was initially analyzed using HIVE Moderation, which detected indicators of AI-generated content in the footage. Further examination showed that these indicators were associated with the first five seconds of the video.

The footage was subsequently analyzed using UncovAI, which also detected AI-generated content. The findings from both tools therefore indicate that the video combines AI-generated imagery with authentic footage rather than consisting entirely of genuine documentation of the Nepal floods.

In conclusion, the investigation indicates that the 15-second video should not be considered entirely authentic footage of the August 2026 floods in Nepal. Analyses conducted using HIVE Moderation and UncovAI identified the first five seconds of the video as AI-generated. The video therefore combines artificially generated imagery with real footage while being presented to viewers as a continuous recording of the disaster.

This case highlights an important challenge in identifying AI-generated misinformation: manipulated content does not necessarily have to be entirely artificial. AI-generated segments can be combined with authentic footage, making misleading videos more difficult for viewers to recognize. As generative AI becomes increasingly integrated into visual content, verifying individual segments of a video—as well as its overall context—is essential, particularly when assessing footage associated with breaking news and natural disasters.

 

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 

Fact Check: AI-Generated Flood Video Falsely Presented as Footage of the 2026 Nepal Floods

On August 26, 2026, a massive flood occurred along the Nepal-China border. Following the disaster, many social media users shared images and videos purportedly related to the flooding. However, some of this content was unrelated to the disaster, shared in a misleading context, or generated using artificial intelligence.

One such example is a video shared on X on August 28, 2026, by a user named amanda_npo. The 10-second video purportedly shows scenes from the flood disaster in Nepal. The video has been viewed more than 665 times, reposted 15 times, and liked 51 times.

 

However, a subsequent investigation revealed that the video was not authentic and had been generated using artificial intelligence. To assess the authenticity of the footage, the video was examined using Gemini and UncovAI.

The video was initially analyzed using Gemini, which determined that the content had been generated using artificial intelligence. Gemini identified several potential indicators of AI generation, including unrealistic water dynamics, unnatural movement of objects, and visual rendering artifacts.

The video was subsequently analyzed using UncovAI, which also indicated that the footage was AI-generated.

 

Frames from the video were also examined using Google’s reverse image search to determine whether the footage had previously appeared online. The investigation revealed that the video had been shared not only by amanda_npo but also by numerous other users on X. Furthermore, the footage had circulated beyond X and appeared on several other social media platforms. For example, the video was uploaded to YouTube by a user named bmcvlogs88 and was also shared by users on Instagram.

Notably, the video also appeared on the official websites of some news organizations. For example, CNN Türk published the footage on its website under the headline “Footage of the Flood Disaster in Nepal.” The circulation of the video by news outlets is particularly significant because it demonstrates how AI-generated content can move beyond social media and enter the broader news ecosystem, potentially reaching audiences who may assume that footage published by established media organizations has already been verified.

In conclusion, the investigation indicates that the viral video does not authentically depict the August 2026 floods in Nepal. Analyses conducted using Gemini and UncovAI identified multiple indicators suggesting that the footage was generated using artificial intelligence, including unrealistic water dynamics, unnatural object movements, and visual rendering artifacts.

Despite being AI-generated, the video circulated across multiple social media platforms and was even published by some news outlets as footage of the Nepal floods. This case demonstrates how AI-generated content can move rapidly from social media into the broader information ecosystem and potentially be mistaken for authentic documentation of a real-world disaster. It also highlights the increasing importance of verifying the authenticity, source, and context of visual content before publication, particularly during breaking news events when misleading or fabricated footage can spread rapidly.

 

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

Fact Check: AI-Generated Elephant Rescue Videos Falsely Linked to the 2026 Nepal Floods

On August 26, 2026, a massive flood occurred along the Nepal-China border. Following the disaster, many social media users shared images and videos purportedly related to the flooding. However, some of this content was unrelated to the disaster, shared in a misleading context, or generated using artificial intelligence.

One such example is a video shared on X on August 29, 2026, by a user named freddyzur. The 10-second video allegedly shows an elephant rescuing two children during the floods in Nepal. The video has been viewed more than 211,000 times, reposted over 3,100 times, and liked more than 12,000 times.

 

However, a subsequent investigation revealed that the video was not authentic and had been generated using artificial intelligence. To assess the authenticity of the footage, the video was examined using HIVE Moderation, which indicated that the content was AI-generated.

Frames from the video were also analyzed using Google’s reverse image search to determine whether the footage had previously appeared online. The investigation revealed that the video had been shared not only by freddyzur but also by numerous other users on X. Furthermore, the footage had spread beyond X and appeared on various other social media platforms. The investigation also identified numerous similar videos, particularly on X, purportedly showing elephants rescuing people during the floods in Nepal.

Another example is a 15-secondvideo posted on X on August 28, 2026, by a user named izzetcapa. The video allegedly shows an elephant rescuing a person from floodwaters in Nepal. It has been viewed more than 408,400 times and liked over 18,000 times.

 

However, a subsequent investigation revealed that this video was also not authentic and had been generated using artificial intelligence. To assess its authenticity, the footage was analyzed using HIVE Moderation, which indicated that the video was AI-generated.

 

Taken together, these examples demonstrate a broader pattern of AI-generated videos depicting elephants allegedly rescuing people during the Nepal floods. Although presented as footage of real rescue operations, analysis indicates that these videos were artificially generated and circulated in connection with an actual natural disaster.

In conclusion, the investigation indicates that the viral videos do not authentically depict elephants rescuing people during the August 2026 floods in Nepal. Analysis conducted using HIVE Moderation identified the footage as AI-generated. The presence of multiple similar videos circulating across X and other social media platforms also demonstrates how AI-generated content can rapidly spread during a major natural disaster and be presented as genuine footage of real events.

These examples highlight a growing form of disaster-related disinformation in which generative AI is used to create emotionally compelling but fabricated scenes and associate them with an ongoing crisis. Such content can attract significant engagement because of its dramatic and emotional nature, while potentially misleading viewers about what actually occurred. The widespread circulation of these videos underscores the importance of verifying the authenticity, source, and context of viral footage before sharing it, particularly during natural disasters and other breaking news events.

 

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

Fact Check: AI-Generated Dam Disaster Video Falsely Linked to the 2026 Nepal Floods

On August 26, 2026, a massive flood occurred along the Nepal-China border. Following the disaster, many social media users shared images and videos purportedly related to the flooding. However, some of this content was unrelated to the disaster, shared in a misleading context, or generated using artificial intelligence.

One such example is a video shared on X on August 28, 2026, by a user named RadharamnDas. The 30-second video purportedly shows damage to a dam in Nepal and the resulting destruction. Within three hours of being posted, the video had been viewed more than 229,000 times, reposted 507 times, and liked more than 1,100 times.

 

However, a subsequent investigation revealed that the video was not authentic and had been generated using artificial intelligence. To assess the authenticity of the footage, the video was examined using Gemini and HIVE Moderation.

The video was initially analyzed using Gemini, which determined that the content had been generated using artificial intelligence. Gemini identified several potential indicators of AI generation, including objects that appear to morph or change unnaturally, unnatural movements of people in the footage, and inconsistencies in lighting and shadows.

The video was subsequently analyzed using HIVE Moderation, which also indicated that the footage was AI-generated.

 

Frames from the video were also examined using Google’s reverse image search to determine whether the footage had previously appeared online. The investigation revealed that the video had been shared not only by RadharamnDas but also by numerous other users on X. Furthermore, the footage had circulated beyond X and appeared on several other social media platforms, demonstrating how widely the AI-generated video had spread in connection with the Nepal floods.

In conclusion, the investigation indicates that the viral video does not show authentic footage of dam damage caused by the August 2026 floods along the Nepal-China border. The footage was widely circulated across X and other social media platforms, allowing the misleading content to reach a large audience within a short period of time.

This case demonstrates how AI-generated content can be presented as genuine footage of an ongoing natural disaster, potentially misleading viewers and creating confusion during a crisis. As generative AI makes increasingly realistic visual content easier to produce, verifying the authenticity and context of viral images and videos is becoming even more important, particularly during breaking news events and natural disasters.

 

 

 

 

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 Military Training Video Shared on TikTok Is Not Authentic

On March 31, 2026, a 10-second video was shared on TikTok by prizrak_kupyanska_zov. The post claimed that the footage depicted Russian soldiers undergoing rigorous military training. The video received 138 likes and was reposted 11 times.

 

However, subsequent investigation revealed that the video was not authentic and had been generated using artificial intelligence technologies. The authenticity of the footage was examined using BioID and HIVE Moderation.

The video was initially analyzed using HIVE Moderation, which determined that the content had been generated through artificial intelligence. It was subsequently examined using BioID, which reached the same conclusion, confirming that the footage was not genuine and had been synthetically produced.

 

In addition to the technical analyses, a detailed visual examination of the video revealed several inconsistencies commonly associated with AI-generated content. For example, while the soldiers shown during the first eight seconds of the video display Russian flags on their arms, the soldier appearing at the eighth second does not have this flag. This inconsistency within the same scene constitutes a significant indicator of artificial manipulation.

In conclusion, the video allegedly depicting Russian soldiers in training was generated using artificial intelligence technologies. Both the findings from technical detection tools and the observable visual inconsistencies demonstrate that the content does not represent authentic footage.

 

 

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 Video Allegedly Showing Captured Ukrainian Soldiers Was Generated Using Artificial Intelligence

On June 9, 2026, a 59-second video was posted on X by @AdrianoValui. The video purportedly shows Ukrainian soldiers taken prisoner by Russian forces. Within four hours of being shared, the footage had been viewed more than 28,000 times, received 573 likes, and was reposted 192 times.

 

 

However, subsequent investigation revealed that the video was not authentic and had been generated using artificial intelligence technologies. The authenticity of the footage was examined using Grok, the Media Analysis, Verification, and Retrieval Group (MeVer), and HIVE Moderation.

Initial analysis conducted with Grok suggested that the video was not genuine, indicating that it had likely been generated using AI and may have been circulated for pro-Russian propaganda purposes. Similarly, the assessment carried out by MeVer identified multiple visual inconsistencies commonly associated with AI-generated content, further supporting the conclusion that the video had been synthetically produced.

The footage was subsequently analyzed using HIVE Moderation, which confirmed that it had been generated using artificial intelligence, consistent with the findings from Grok and MeVer.

 

Moreover, the visible TikTok logo in the video indicates that the content was not originally posted on X and had previously circulated on other social media platforms. A reverse image search was therefore conducted, revealing that the video was first shared on TikTok on November 4, 2025, by “liliakv.” It was later posted on Facebook on December 16, 2025, by a user named “Petruss Krsska,” and continued to circulate through reposts across TikTok and Facebook on various dates.

 

 

In conclusion, the video allegedly depicting Ukrainian soldiers captured by Russian forces was generated using artificial intelligence technologies. The fact that the footage circulated across multiple platforms for several months demonstrates how AI-generated disinformation can persist over extended periods and be repeatedly presented as authentic. Particularly during times of war and conflict, it is essential to verify the source and accuracy of 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.

 

Different Wars, Same Fake Video

On June 8, 2026, an 11-second video was posted on X by @IsraelSpoofX. The accompanying claim stated that Israeli air defense systems had detected and destroyed five Iranian warplanes. The video was viewed more than 1,600,000 times, received over 4,000 likes, and was reposted 926 times.

 

 

The same video was posted again on June 9, 2026, this time by @RussianArmy_ on X. However, the June 9 post claimed that the footage showed Russian air defense systems detecting and destroying five Ukrainian warplanes en route to attack Russia. Although both posts used identical footage, they attributed it to different conflicts and countries. The June 9 post received over 145,000 views, more than 1,400 likes, and 439 reposts.

However, the video shared by these two users and associated with two separate wars is not authentic; it was generated using artificial intelligence. The authenticity of the footage was examined using Grok, Google SynthID, and HIVE Moderation.

Initial analysis conducted with Grok indicated that both the video and the accompanying claims were not credible. Similarly, Google SynthID identified multiple visual and physical inconsistencies characteristic of AI-generated content. These findings strongly suggested that the footage had been synthetically produced.

 

The video was subsequently analyzed using HIVE Moderation, which confirmed that it was AI-generated, consistent with the results obtained from Grok and Google SynthID.

 

 

In conclusion, the video allegedly depicting Israel destroying Iranian warplanes and Russia destroying Ukrainian warplanes was generated using artificial intelligence. The recirculation of identical AI-generated content under different geopolitical narratives illustrates how easily disinformation can spread across social media platforms. This case once again underscores the importance of verifying visual content—particularly in relation to international conflicts and military developments—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.

Videos of Soldiers Crying Posted on X Contain Disinformation

On June 8, 2026, a 15-second video was posted on X by @aattzz23. The video depicts a Ukrainian soldier, allegedly 23 years old, crying. The accompanying post claims that the soldier had been sent to the front lines and was therefore in distress. Within two hours, the video was viewed 732 times and received 34 likes.

 

 

However, subsequent investigation revealed that the video was not authentic and had been generated using artificial intelligence. The footage was analyzed using Google SynthID and HIVE Moderation, both AI-content detection tools. The results from both analyses confirmed that the video was AI-generated.

 

AI-generated videos portraying soldiers in emotional distress are not limited to the context of the war in Ukraine. Similar content has circulated on social media in relation to other conflicts. For example, on June 1, 2026, a nine-second video was shared on X by the user @DailyChinaNews. The video, which has been viewed more than 16,600 times and received 339 likes, shows a female U.S. soldier crying and stating that she misses her family.

 

Like the video shared on June 8, the June 1 video was also created using artificial intelligence. Analysis conducted using Google SynthID and HIVE Moderation determined that the footage was AI-generated. In particular, the SynthID analysis identified visual and physical inconsistencies characteristic of synthetic media.

 

In conclusion, both videos allegedly depicting Ukrainian and American soldiers crying were generated using artificial intelligence. These cases demonstrate how emotionally charged AI-generated content can be employed to influence public opinion during periods of war and conflict. It is therefore essential to verify the authenticity of content—especially material involving soldiers, civilians, or alleged victims of war—through reliable sources and technical detection tools before sharing it.

 

 

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.

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.

Video Linked to Attacks in Ukraine Found to Be AI-Generated

On June 2, 2026, Russian drones and missiles reportedly targeted Kyiv, the capital of Ukraine, and several other cities during the early morning hours. According to reports, the attacks resulted in at least 18 fatalities and more than 100 injuries in Kyiv and other affected areas. Images, videos, and updates related to the attacks were widely circulated across numerous social media platforms. One such post was shared on June 2, 2026, by the user @EthanLevins2 on X.

 

The 46-second video was viewed more than 12,600 times and reposted 102 times within a short period. It also received 773 likes. However, subsequent investigations revealed that the footage had been generated using artificial intelligence. The video was analyzed using HIVE Moderation, which confirmed that the content had been created with AI-based tools.

In conclusion, the short video posted on X on June 2 was artificially generated and does not depict authentic events. Technical analysis identified several inconsistencies characteristic of AI-generated media. This case illustrates how visual content associated with breaking news and ongoing conflicts can spread rapidly when presented as genuine footage. Particularly during periods of war, conflict, and crisis, it is essential to verify the authenticity of shared videos and images through 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.