#FactCheck-AI-Altered Video Falsely Claims Indian Army Air Defence Officer Resigned Over ‘Operation Sindoor’
Executive Summary
A video of a soldier is being widely circulated on social media with the claim that an Indian Army Air Defence officer named Anurag Thakur resigned, alleging that soldiers martyred during “Operation Sindoor” were ignored by the government. However, research by the CyberPeace Research Wing found the claim to be false. The viral video has been manipulated with AI-generated audio and is being shared with a misleading narrative.
Claim:
Instagram users shared the clip claiming: “Indian Army Air Defence officer Anurag Thakur has resigned. He said the Government of India did not even acknowledge the deaths of soldiers.”
Fact Check:
The research began with keyword searches related to the alleged resignation of an “Indian Army Air Defence JCO Anurag Thakur.” No credible or reputed media report was found supporting such a claim. A reverse image search of a frame from the viral video led to the original footage posted by news agency ANI on its official X account on March 22, 2026. The original video runs for 1 minute and 42 seconds A comparison of both videos showed that in the viral clip, the soldier appears to be speaking in English, whereas in ANI’s authentic video, the same soldier is speaking in Hindi while addressing the media.
In the original video, shared by ANI from Bhuj, Gujarat, the JCO explained that on the morning of May 7, 2025, they learned that Indian armed forces had destroyed enemy terror launch pads, marking the beginning of “Operation Sindoor.” He said he motivated his unit and they were prepared to respond. He further stated that on May 8, an enemy drone heading toward a vital location was detected and shot down using minimal ammunition. Two more drones were sent the following day and were also neutralised. He added that “Operation Sindoor” demonstrated the capability of the Indian Army and Air Defence units.
ANI had also summarised the same remarks in English in its post, which further confirmed that the viral version had been tampered with. For additional verification, the audio from the viral clip was examined using AI-based detection tools. Hiya Deepfake Voice Detector flagged it as likely fake, while Resemble AI also identified the audio as manipulated.
Conclusion:
The viral video claiming that an Indian Army Air Defence JCO resigned over ignored martyrs of “Operation Sindoor” is false. The original footage has been altered and artificial AI-generated audio was added to create a misleading narrative.
Related Blogs
How clothing patterns, movement and real-world conditions can affect computer vision
Introduction
A person walks in front of an AI camera. The person is clearly visible to us, yet the system may not always identify the person with the same confidence. This sounds strange until we understand one basic fact: a camera records an image, while an AI model interprets that image through patterns learned during training.
This idea became popular through demonstrations such as “The T-Shirt Invisibility Cloak,” where specially designed clothing was shown as a way to interfere with person-detection systems. The wearer does not become physically invisible. The camera still captures the person. Instead, the visual pattern can make a particular AI model less confident or cause an incorrect prediction.
So, how can a piece of clothing affect machine vision? And what does this tell us about the strengths and limitations of AI surveillance?
How Does an AI Camera See?
A normal CCTV camera mainly captures and records video. An AI camera adds software that analyses the video for a specific task, such as detecting a person, vehicle, face or event.
A simple way to understand the process is:
The model does not understand a person exactly as a human does. It processes numerical representations learned from training data. For a person detector, the question is closer to “Do these visual patterns match the class ‘person’?” than “I know this is a human.”
Think About It
A human sees a person wearing a complex shirt and easily separates the shirt design from the person. An AI model must decide what the visual patterns in the image mean for its particular task.
When Clothing Becomes Difficult
Clothing can become challenging when it changes the visual information available to a model.
Complex patterns can add many edges, repeated shapes and textures to an image. These do not automatically confuse an AI camera, but they can influence the features a detector uses.
Low contrast can create another problem. If clothing is close in colour or brightness to the background, the boundary between the person and the environment may be harder to separate, especially in poor lighting or low-resolution footage.
Movement creates another challenge. A loose jacket, flowing fabric or layered clothing changes shape as the person walks or turns. Researchers designing adversarial T-shirts have had to account for these non-rigid changes because a printed pattern does not stay flat on a moving body.
The T-Shirt Invisibility Cloak
The video “The T-Shirt Invisibility Cloak” is a simple introduction to a larger research area called physical adversarial examples.
In adversarial machine learning, researchers study inputs deliberately designed to make a model produce an incorrect prediction. With clothing, the visual pattern is physically printed on a garment and then captured by a camera.
A 2019 study by Xu and colleagues demonstrated an adversarial T-shirt designed to interfere with person detectors in the physical world. Under their test conditions, the reported physical attack success rate against YOLOv2 was 57%. The work also modelled cloth deformation caused by movement.
A 2022 CVPR study on adversarial texture extended the idea to different viewing angles and tested physical clothing such as T-shirts, skirts and dresses.
But there is an important limitation: an adversarial garment is not a universal invisibility cloak. Different cameras and AI systems use different models, training data and processing pipelines. A pattern that affects one detector may have little effect on another.
Why Does the AI Get It Wrong?
Clothing may be only one part of the problem. A model can receive features different from what it learned during training. Camera angle, distance, movement, lighting, motion blur, compression and occlusion can also change the image.
Imagine the same person in four situations:
There may not be one fixed answer. AI performance depends on the combination of conditions.
AI Camera vs Human Vision
Humans use context. We understand that clothes wrinkle, people turn, shadows change and objects may temporarily block part of a body. An AI detector is more task-specific and can become less reliable when input conditions differ from the data used to train or evaluate it.
This does not make AI useless. It makes realistic testing important.
Building More Reliable AI Surveillance
The lesson is not that AI cameras should be abandoned. They should be tested under difficult, realistic conditions.
Testing can include different clothing patterns, colours, body positions, distances, camera angles, lighting conditions and crowded scenes. Security teams should also distinguish between person detection, facial recognition, tracking and behaviour analysis because these are different tasks. [6]
Most importantly, an automated alert should be treated as a prediction, not unquestionable truth. Important decisions should include appropriate human review.
A New Research Direction
Research is also moving beyond ordinary visible-light cameras. A 2026 CVPR paper explored adversarial clothing designed to affect both visible and infrared surveillance systems. At the same time, researchers continue to study ways of making models more robust against physical adversarial attacks.
This creates a continuing security cycle:
That cycle is a normal part of security research.
At a Glance: Human Vision vs AI Detection
Conclusion
The idea of an “invisible T-shirt” is fascinating because it challenges a common assumption about AI: if a machine can see an image, we expect it to understand that image correctly.
A person can remain completely visible while a particular AI detector becomes less confident or makes a wrong prediction. Clothing patterns, texture, folds, movement, lighting, camera angle and other factors can interact with a model in unexpected ways. Research has demonstrated physical adversarial clothing against person detectors, while newer work is exploring more complex surveillance conditions.
The real lesson is not that a shirt can make someone invisible. AI vision is a prediction system with strengths and weaknesses. Understanding those weaknesses helps researchers build better defences, helps security teams evaluate systems realistically, and reminds us that automated surveillance should be deployed with technical care, human oversight and respect for privacy.
References
- The T-Shirt Invisibility Cloak
- YouTube video referenced for the article’s introductory example: https://www.youtube.com/watch?v=NyofHyRm5CQ
- Xu, K., Zhang, G., Liu, S., Fan, Q., Sun, M., Chen, H., Chen, P.-Y., Wang, Y., & Lin, X. (2020). Adversarial T-shirt! Evading Person Detectors in a Physical World. Computer Vision – ECCV 2020, 665–681. https://doi.org/10.1007/978-3-030-58558-7_39
- Study demonstrating a physical adversarial T-shirt against person detection and modelling non-rigid cloth deformation during movement. https://arxiv.org/abs/1910.11099
- Thys, S., Van Ranst, W., & Goedemé, T. (2019). Fooling Automated Surveillance Cameras: Adversarial Patches to Attack Person Detection. CVPR Workshops.
- Earlier work showing physical adversarial patches can reduce the accuracy of person detectors. https://openaccess.thecvf.com/content_CVPRW_2019/html/CV-COPS/Thys_Fooling_Automated_Surveillance_Cameras_Adversarial_Patches_to_Attack_Person_Detection_CVPRW_2019_paper.html
- Hu, Z., Huang, S., Zhu, X., Sun, F., Zhang, B., & Hu, X. (2022). Adversarial Texture for Fooling Person Detectors in the Physical World. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 13307–13316.
- Study extending physical adversarial clothing to multiple viewing angles and garments including T-shirts, skirts and dresses. https://openaccess.thecvf.com/content/CVPR2022/html/Hu_Adversarial_Texture_for_Fooling_Person_Detectors_in_the_Physical_World_CVPR_2022_paper.html
- Long, J., Jiang, T., Liu, H., Ma, C., Zhou, W., Yang, Y., & Yao, W. (2026). Thermally Activated Dual-Modal Adversarial Clothing against AI Surveillance Systems. CVPR 2026.
- Recent work exploring adversarial clothing against visible and infrared surveillance systems. https://openaccess.thecvf.com/content/CVPR2026/html/Long_Thermally_Activated_Dual-Modal_Adversarial_Clothing_against_AI_Surveillance_Systems_CVPR_2026_paper.html
- Li, S., Zhang, S., Chen, G., Wang, D., Feng, P., Wang, J., Liu, A., Yi, X., & Liu, X. (2023). Towards Benchmarking and Assessing Visual Naturalness of Physical World Adversarial Attacks. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 12324–12333.
- Useful context on physical adversarial attacks and the challenge of making them visually natural. https://openaccess.thecvf.com/content/CVPR2023/papers/Li_Towards_Benchmarking_and_Assessing_Visual_Naturalness_of_Physical_World_Adversarial_CVPR_2023_paper.pdf [6]
Introduction
It’s a proud moment for Indians that India will host the G- 20 administration, which will bring the world’s 20 largest profitable nations together on a single platform during the post-economic recovery and the Russia- Ukraine conflict, which has increased geopolitical pressures among nations over the last many times and made the G- 20 a precedence of nations. With this administration, India has to make cybersecurity precedence, as the security and integrity of the critical structure and digital platforms are top precedence in 2023. The necessity for a secure cyberspace is pivotal given the exponential increase in the volume and kind of cyber-attacks, particularly to crucial structures the most recent illustration is the ongoing interruption at New Delhi’s All India Institute of Medical lores caused by a ransomware assault. It has been observed that the mode of attacks are more sophisticated and targets communication structure, critical structure, transport systems, and especially the information technology sector and fiscal system.
The structure that enables the delivery of government services to be more effective. As a result,cyber-secured critical structures and digital public forums are necessary for public security, bettered governance, and, most importantly, maintaining people’s trust. The G20 can be enhanced and contribute towards securing digital public platforms and the integrity of the critical structure. This time, in 2023, digital security is the top precedence.
G20 cybersecurity enterprises and politic sweat
The emphasis on cybersecurity was maintained throughout the Italian and Indonesian regulations in 2021 and 2022, independently, by emphasizing the significance of cyberspace during Digital Economy Working Group addresses. Specifically, under the Indonesian Presidency, the prominent cybersecurity focus was clear in the recent Bali Leaders’ protestation, which noted, among other effects, the significance of fighting misinformation juggernauts and cyber attacks, as well as guaranteeing connectivity structure security. The cyber incident report by the Financial Stability Board on carrying further uniformity in cyber incident reporting In 2016, a G20 digital task force was created under the Chinese administration to understand digital technology issues. Under the Saudi administration, the cybersecurity gap at the G20 was bridged by addressing the issues of MSMs. India has also refocused on the significance of creating secure, secure, and stronger-friendly digital platforms.
G20- India’s digital invention alliance( G-20-DIA) a cyber-secure Bharat
- Under India’s administration, the G20’s Digital Economy Working Group is led by the Ministry of Electronics and Information Technology( MeitY, DEWG).
- The Ministry concentrated on three major areas during India’s G20 administration digital skill development, digital public structure, and cyber security.
- The EWG’s DIA and Stay Safe Online enterprise further the ideal of lesser digital metamorphosis by guaranteeing a safe and creative cyber terrain. They want to offer a smooth and secure delivery of public services.
The G20 Digital Innovation Alliance
(G20- DIA) strives to find, admit, and encourage the relinquishment of innovative and poignant digital technologies produced by invited G20 startups and-member governments.
- These technologies must meet humanity’s conditions in six crucial areas husbandry, health, education, finance, secure digital structure, and indirect frugality.
- The inventions created around these motifs will be supported by the Digital Public Goods structure, allowing them to be espoused encyclopedically, closing the digital gap and icing sustainable and indifferent growth.
- The G20 Digital Innovation Alliance( G20- DIA) conference will be held on the perimeters of the Digital Economy Working Group( DEWG) meeting in Bengaluru.
- Top-nominated entrepreneurs from each order will present their ideas to a worldwide community of investors, instructors, pots, and other stakeholders at this event.
India’s” Stay Safe Online crusade”
The” Stay Safe Online” crusade attempts to raise mindfulness about the significance of remaining safe in the online world amid our adding reliance on it. With the fast expansion of the technical terrain and the growing number of internet druggies in India, new difficulties are arising. The Stay Safe Online crusade aims to educate individuals about cyber pitfalls and how to avoid them. The time-long crusade will target children, women, scholars, and aged citizens, as well as individuals with disabilities, preceptors, and government officers in particular. It’ll be done in Hindi, English, and indigenous languages to reach a larger followership. It’ll distribute mindfulness information in infographics, short pictures, cartoon stories, and so on through extensively employed social media platforms and other channels. The primary stakeholders will be government agencies, civil societies, and NGOs.
Conclusion
To wind up, it can be said that cyber security has become the most essential part of transnational affairs. As India hosts the G20 administration in 2023, the docket relating to cybersecurity gains a global stage, where cyber-related issues are addressed and honored encyclopedically, and nations can combat these issues; also, India aims to raise cyber mindfulness among its citizens.
Executive Summary:
A short video clip of Prime Minister Narendra Modi is going viral on social media. In the clip, he can be heard saying, “What sins did we commit in our previous life that we were born in India?” Users are sharing this video claiming that the Prime Minister insulted India and its people during a foreign visit. However, an research by the CyberPeace found that the claim is misleading. The viral clip is taken out of context from a longer speech delivered by Modi during his visit to Shanghai, China, in 2015
Claim:
A Facebook user named “Bittu Yadav” shared the reel, portraying the statement as anti-India. The caption reads:“Look at this, and you supporters—see how your ‘leader’ is praising the country.”
Post link and archive link:
Fact Check:
To verify the claim, we searched relevant keywords on Google and found the full video uploaded on May 16, 2015, on the official YouTube channel of the Bharatiya Janata Party. The video shows Prime Minister Narendra Modi addressing the Indian community in Shanghai, China.
In the 57-minute speech, at around 51 minutes 25 seconds, Modi was referring to the pessimistic atmosphere in India before 2014. He said: “Within a year… people used to say, ‘Leave it, nothing will happen now. Who knows what sins we committed in our previous life that we were born in India’… From that mindset, today the world says that if there is a country growing at the fastest pace, it is India.”
This clearly shows that Modi was citing a past sentiment to highlight how perceptions about India have changed over time, not expressing his personal view. Media reports from his May 2015 China visit also noted that he addressed around 5,000 members of the Indian community in Shanghai, where he spoke about India’s economic growth and initiatives like “Make in India.”
Conclusion:
The viral claim is false. The video has been edited and shared out of context. In reality, Prime Minister Narendra Modi was referring to a past mindset before 2014 while highlighting the change in India’s global perception.
