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 Video Falsely Shows a Warplane Bombing a Dam During 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 27, 2026, by a user named UrbnIre. The 27-second video allegedly shows a warplane bombing a dam in Nepal, causing the structure to collapse. The video has been viewed more than 12,600 times, reposted 18 times, and liked 25 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 unrealistic water dynamics, unnatural jet movement, and visual rendering artifacts.

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 UrbnIre 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 RizwanJokhio-k1d4o and was also shared by users on Facebook.

In conclusion, the investigation indicates that the viral video does not authentically depict a warplane bombing a dam in Nepal during the August 2026 floods. Analyses conducted using Gemini and HIVE Moderation identified multiple indicators suggesting that the footage was generated using artificial intelligence, including unrealistic water dynamics, unnatural aircraft movement, and visual rendering artifacts. The video was also found circulating across multiple social media platforms, demonstrating how quickly AI-generated content can spread during a major disaster.

This case illustrates how a real natural disaster can be exploited as the backdrop for entirely fabricated visual content. By presenting AI-generated footage as evidence of an event that did not occur, such content can mislead viewers, create confusion, and distort public understanding of an unfolding crisis. It therefore highlights the importance of verifying both the authenticity and context of viral footage before sharing it, 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

 

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

Fact Check: Viral Tiananmen Square Video Supporting Taiwan Independence Is AI-Generated

 

On August 23, 2026, a user named J4207Jin posted a 10-second video on X. The video appears to show a person holding a Taiwanese flag and chanting slogans in Tiananmen Square. The person can be heard saying, “Taiwan is not part of China, and it is independent.” The video has been viewed more than 30,000 times, reposted 13 times, and liked 64 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 features as potential indicators of AI generation, including inconsistencies in lighting and shadows, unnatural movements of people in the video, and irregularities in the background.

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 was not first shared on August 23, 2026, but had circulated on different social media platforms several months earlier. The earliest instance identified during the investigation was an X post by a user named MinMin89485072 on January 1, 2026. The video was later shared on Instagram by a user named hellotaiwanese on January 4, 2026.

In conclusion, the investigation indicates that the viral video does not authentically depict a person holding a Taiwanese flag and making pro-Taiwan independence statements in Tiananmen Square. Analyses conducted using Gemini and HIVE Moderation identified indicators suggesting that the footage was generated using artificial intelligence. Furthermore, reverse image searches revealed that the video had circulated online months before the August 23, 2026 post, with the earliest identified version dating back to January 1, 2026. This case demonstrates how AI-generated content can be presented as footage of a real-world political event and potentially mislead viewers. It also highlights the importance of verifying both the authenticity and original context of viral videos, particularly when they involve politically sensitive issues.

 

 

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 Video Falsely Claims to Show Iranian Missiles Prepared for Attack on Israel

On August 24, 2026, a user named IRGC_Press posted a 15-second video on X. The video shows military vehicles transporting a large missile decorated with Iranian flags, accompanied by police escort vehicles.

The post accompanying the video stated: “Breaking: Iran announces it will use multi-warhead missiles with massive destructive power in waves 92 and 93 of its attacks on Israel tonight. It will be devastating for the Zionists, and other surprises have been prepared for them!”

 

The video and accompanying post have been viewed 5,382 times, reposted 55 times, and liked 159 times.

However, a subsequent investigation revealed that the video was not authentic and had been generated using artificial intelligence. IRGC_Press regularly shares false or misleading information using AI-generated content on X. To assess the authenticity of the footage, the video was examined using Grok and HIVE Moderation.

The video was initially analyzed using Grok, which determined that the content had been generated using artificial intelligence. It was subsequently analyzed using HIVE Moderation, which also indicated that the footage 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 analysis revealed that the video was first shared by a Facebook user on April 4, 2026, and was subsequently circulated on various other social media platforms at different times.

In conclusion, the investigation indicates that the video does not depict authentic footage of Iranian military vehicles transporting a multi-warhead missile for an imminent attack on Israel. Analyses conducted using Grok and HIVE Moderation suggest that the video was generated using artificial intelligence. Furthermore, reverse image searches revealed that the footage had circulated online months before the claim posted on August 24, 2026, further undermining the assertion that it showed preparations for an attack that night. This case demonstrates how AI-generated content can be combined with urgent and alarming claims to create misleading narratives and potentially influence public perceptions during periods of heightened geopolitical tension. It also highlights the importance of verifying both the authenticity and original context of viral visual content before accepting or sharing claims associated with 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

Video Allegedly Showing Recent Attacks in Ukraine Is Actually From 2017

On June 21, 2026, a 19-second video was posted on X by @MesutUdaySaddam. The post claimed that the video showed Russia’s recent missile attacks on Ukraine on June 21 and the resulting explosions. The video has been viewed more than 81,300 times and has received 400 likes.

 

The video was investigated for authenticity because it contained elements that could suggest it was created using artificial intelligence. It was analyzed using Grok, Google SynthID, and HIVE Moderation tools. All three tools confirmed that the footage was real and not AI-generated. In other words, the video shared on X was determined to depict an actual event.

However, analyses by both Grok and Gemini indicate that the video does not show recent Russian attacks on Ukraine. Instead, it contains footage from an event that occurred in 2017 or earlier.

To determine the video’s actual time frame, it was further examined using Google’s reverse image search. This analysis revealed that the footage is from a fire and explosion that occurred on March 23, 2017, at a military ammunition depot in Balakliya, in Ukraine’s Kharkiv region.

In conclusion, the video is not AI-generated and contains real footage. However, it does not depict the Russian missile attacks on Ukraine on June 21, 2026, as claimed. Presenting footage from a different event in 2017 as if it were current demonstrates that the content is misleading. This example illustrates that even authentic footage can be used for disinformation when it is shared with incorrect information about the date, location, or event.

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.