#FactCheck - Viral Clip and Newspaper Article Claiming 18% GST on 'Good Morning' Messages Debunked

‍Introduction 

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In September 2025, social media feeds were flooded with strikingly vintage saree-type portraits. These images were not taken by professional photographers, but AI-generated images. More than a million people turned to the "Nano Banana" AI tool of Google Gemini, uploading their ordinary selfies and watching them transform into Bollywood-style, cinematic, 1990s posters. The popularity of this trend is evident, as are the concerns of law enforcement agencies and cybersecurity experts regarding risks of infringement of privacy, unauthorised data sharing, and threats related to deepfake misuse.

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What is the Trend?

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This trend in AI sarees is created using Google Geminis' Nano Banana image-editing tool, editing and morphing uploaded selfies into glitzy vintage portraits in traditional Indian attire. A user would upload a clear photograph of a solo subject and enter prompts to generate images of cinematic backgrounds, flowing chiffon sarees, golden-hour ambience, and grainy film texture, reminiscent of classic Bollywood imagery. Since its launch, the tool has processed over 500 million images, with the saree trend marking one of its most popular uses. Photographs are uploaded to an AI system, which uses machine learning to alter the pictures according to the description specified. The transformed AI portraits are then shared by users on their Instagram, WhatsApp, and other social media platforms, thereby contributing to the viral nature of the trend.

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Law Enforcement Agency Warnings

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1. A few Indian police agencies have issued strong advisories against participation in such trends. IPS Officer VC Sajjanar warned the public: "The uploading of just one personal photograph can make greedy operators go from clicking their fingers to joining hands with criminals and emptying one's bank account." His advisory had further warned that sharing personal information through trending apps can lead to many scams and fraud.
2. Jalandhar Rural Police issued a comprehensive warning stating that such applications put the user at risk of identity theft and online fraud when personal pictures are uploaded. A senior police officer stated: "Once sensitive facial data is uploaded, it can be stored, analysed, and even potentially misused to open the way for cyber fraud, impersonation, and digital identity crimes.

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The Cyber Crime Police also put out warnings on social media platforms regarding how photo applications appear entertaining but can pose serious risks to user privacy. They specifically warned that selfies uploaded can lead to data misuse, deepfake creation, and the generation of fake profiles, which are punishable under Sections 66C and 66D of the IT Act 2000.

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Consequences of Such Trends

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The massification of AI photo trends has several severe effects on private users and society as a whole. Identity fraud and theft are the main issues, as uploaded biometric information can be used by hackers to generate imitated identities, evading security measures or committing financial fraud. The facial recognition information shared by means of these trends remains a digital asset that could be abused years after the trend has passed. ‘Deepfake’ production is another tremendous threat because personal images shared on AI platforms can be utilised to create non-consensual artificial media. Studies have found that more than 95,000 deepfake videos circulated online in 2023 alone, a 550% increase from 2019. The images uploaded can be leveraged to produce embarrassing or harmful content that can cause damage to personal reputation, relationships, and career prospects.

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Financial exploitation is also when fake applications in the guise of genuine AI tools strip users of their personal data and financial details. Such malicious platforms tend to look like well-known services so as to trick users into divulging sensitive information. Long-term privacy infringement also comes about due to the permanent retention and possible commercial exploitation of personal biometric information by AI firms, even when users close down their accounts.

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Privacy Risks

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A few months ago, the Ghibli trend went viral, and now this new trend has taken over. Such trends may subject users to several layers of privacy threats that go far beyond the instant gratification of taking pleasing images. Harvesting of biometric data is the most critical issue since facial recognition information posted on these sites becomes inextricably linked with user identities. Under Google's privacy policy for Gemini tools, uploaded images might be stored temporarily for processing and may be kept for longer periods if used for feedback purposes or feature development. 

Illegal data sharing happens when AI platforms provide user-uploaded content to third parties without user consent. A Mozilla Foundation study in 2023 discovered that 80% of popular AI apps had either non-transparent data policies or obscured the ability of users to opt out of data gathering. This opens up opportunities for personal photographs to be shared with anonymous entities for commercial use. Exploitation of training data includes the use of personal photos uploaded to enhance AI models without notifying or compensating users. Although Google provides users with options to turn off data sharing within privacy settings, most users are ignorant of these capabilities. Integration of cross-platform data increases privacy threats when AI applications use data from interlinked social media profiles, providing detailed user profiles that can be taken advantage of for purposeful manipulation or fraud. Inadequacy of informed consent continues to be a major problem, with users engaging in trends unaware of the entire context of sharing information. Studies show that 68% of individuals show concern regarding the misuse of AI app data, but 42% use these apps without going through the terms and conditions.

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CyberPeace Expert Recommendations

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While the Google Gemini image trend feature operates under its own terms and conditions, it is important to remember that many other tools and applications allow users to generate similar content. Not every platform can be trusted without scrutiny, so users who engage in such trends should do so only on trustworthy platforms and make reliable, informed choices. Above all, following cybersecurity best practices and digital security principles remains essential.

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Here are some best practices:-

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1.Immediate Protection Measures for User

In a nutshell, protection of personal information may begin by not uploading high-resolution personal photos into AI-based applications, especially those trained for facial recognition. Instead, a person can play with stock images or non-identifiable pictures to the degree that it satisfies the program's creative features without compromising biometric security. Strong privacy settings should exist on every social media platform and AI app by which a person can either limit access to their data, content, or anything else.

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2.Organisational Safeguards

AI governance frameworks within organisations should enumerate policies regarding the usage of AI tools by employees, particularly those concerning the upload of personal data. Companies should appropriately carry out due diligence before the adoption of an AI product made commercially available for their own use in order to ensure that such a product has its privacy and security levels as suitable as intended by the company. Training should instruct employees regarding deepfake technology.

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3.Technical Protection Strategies

Deepfake detection software should be used. These tools, which include Microsoft Video Authenticator, Intel FakeCatcher, and Sensity AI, allow real-time detection with an accuracy higher than 95%. Use blockchain-based concepts to verify content to create tamper-proof records of original digital assets so that the method of proposing deepfake content as original remains very difficult.

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4.Policy and Awareness Initiatives

For high-risk transactions, especially in banks and identity verification systems, authentication should include voice and face liveness checks to ensure the person is real and not using fake or manipulated media. Implement digital literacy programs to empower users with knowledge about AI threats, deepfake detection techniques, and safe digital practices. Companies should also liaise with law enforcement, reporting purported AI crimes, thus offering assistance in combating malicious applications of synthetic media technology.

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5.Addressing Data Transparency and Cross-Border AI Security

Regulatory systems need to be called for requiring the transparency of data policies in AI applications, along with providing the rights and choices to users regarding either Biometric data or any other data. Promotion must be given to the indigenous development of AI pertaining to India-centric privacy concerns, assuring the creation of AI models in a secure, transparent, and accountable manner. In respect of cross-border AI security concerns, there must be international cooperation for setting common standards of ethical design, production, and use of AI. With the virus-like contagiousness of AI phenomena such as saree editing trends, they portray the potential and hazards of the present-day generation of artificial intelligence. While such tools offer newer opportunities, they also pose grave privacy and security concerns, which should have been considered quite some time ago by users, organisations, and policy-makers. Through the setting up of all-around protection mechanisms and keeping an active eye on digital privacy, both individuals and institutions will reap the benefits of this AI innovation, and they shall not fall on the darker side of malicious exploitation. 

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References

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1. https://www.hindustantimes.com/trending/amid-google-gemini-nano-banana-ai-trend-ips-officer-warns-people-about-online-scams-101757980904282.html%202
2. https://www.moneycontrol.com/news/india/viral-banana-ai-saree-selfies-may-risk-fraud-warn-jalandhar-rural-police-13549443.html
3. https://www.parliament.nsw.gov.au/researchpapers/Documents/Sexually%20explicit%20deepfakes.pdf
4. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year
5. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year
6. https://socradar.io/top-10-ai-deepfake-detection-tools-2025/

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Executive Summary:

A viral online video claims visuals of a massive rally organised in Manipur for stopping the violence in Manipur. However, the CyberPeace Research Team has confirmed that the video is a deep fake, created using AI technology to manipulate the crowd into existence. There is no original footage in connection to any similar protest. The claim that promotes the same is therefore, false and misleading.

Claims:

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A viral post falsely claims of a massive rally held in Manipur.

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Fact Check:

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Upon receiving the viral posts, we conducted a Google Lens search on the keyframes of the video. We could not locate any authentic sources mentioning such event held recently or previously. The viral video exhibited signs of digital manipulation, prompting a deeper investigation.

We used AI detection tools, such as TrueMedia and Hive AI Detection tool, to analyze the video. The analysis confirmed with 99.7% confidence that the video was a deepfake. The tools identified "substantial evidence of manipulation," particularly in the crowd and colour gradience , which were found to be artificially generated.

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Additionally, an extensive review of official statements and interviews with Manipur State officials revealed no mention of any such rally. No credible reports were found linking to such protests, further confirming the video’s inauthenticity.

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Conclusion:

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The viral video claims visuals of a massive rally held in Manipur. The research using various tools such as truemedia.org and other AI detection tools confirms that the video is manipulated using AI technology. Additionally, there is no information in any official sources. Thus, the CyberPeace Research Team confirms that the video was manipulated using AI technology, making the claim false and misleading.‍

• Claim: Massive rally held in Manipur against the ongoing violence viral on social media.
• Claimed on: Instagram and X(Formerly Twitter)
• Fact Check: False & Misleading

Introduction

Privacy has become a concern for netizens and social media companies have access to a user’s data and the ability to use the said data as they see fit. Meta’s business model, where they rely heavily on collecting and processing user data to deliver targeted advertising, has been under scrutiny. The conflict between Meta and the EU traces back to the enactment of GDPR in 2018. Meta is facing numerous fines for not following through with the regulation and mainly failing to obtain explicit consent for data processing under Chapter 2, Article 7 of the GDPR. ePrivacy Regulation, which focuses on digital communication and digital data privacy, is the next step in the EU’s arsenal to protect user privacy and will target the cookie policies and tracking tech crucial to Meta's ad-targeting mechanism. Meta’s core revenue stream is sourced from targeted advertising which requires vast amounts of data for the creation of a personalised experience and is scrutinised by the EU. 

Pay for Privacy Model and its Implications with Critical Analysis

Meta came up with a solution to deal with the privacy issue - ‘Pay or Consent,’ a model that allows users to opt out of data-driven advertising by paying a subscription fee. The platform would offer users a choice between free, ad-supported services and a paid privacy-enhanced experience which aligns with the GDPR and potentially reduces regulatory pressure on Meta. 

Meta presently needs to assess the economic feasibility of this model and come up with answers for how much a user would be willing to pay for the privacy offered and shift Meta’s monetisation from ad-driven profits to subscription revenues. This would have a direct impact on Meta’s advertisers who use Meta as a platform for detailed user data for targeted advertising, and would potentially decrease ad revenue and innovate other monetisation strategies.

For the users, increased privacy and greater control of data aligning with global privacy concerns would be a potential outcome. While users will undoubtedly appreciate the option to avoid tracking, the suggestion does beg the question that the need to pay might become a barrier. This could possibly divide users between cost-conscious and privacy-conscious segments. Setting up a reasonable price point is necessary for widespread adoption of the model.

For the regulators and the industry, a new precedent would be set in the tech industry and could influence other companies’ approaches to data privacy. Regulators might welcome this move and encourage further innovation in privacy-respecting business models. 

The affordability and fairness of the ‘pay or consent’ model could create digital inequality if privacy comes at a digital cost or even more so as a luxury. The subscription model would also need clarifications as to what data would be collected and how it would be used for non-advertising purposes. In terms of market competition, competitors might use and capitalise on Meta’s subscription model by offering free services with privacy guarantees which could further pressure Meta to refine its offerings to stay competitive. According to the EU, the model needs to provide a third way for users who have ads but are a result of non-personalisation advertising.

Meta has further expressed a willingness to explore various models to address regulatory concerns and enhance user privacy. Their recent actions in the form of pilot programs for testing the pay-for-privacy model is one example. Meta is actively engaging with EU regulators to find mutually acceptable solutions and to demonstrate its commitment to compliance while advocating for business models that sustain innovation. Meta executives have emphasised the importance of user choice and transparency in their future business strategies.

Future Impact Outlook

• The Meta-EU tussle over privacy is a manifestation of broader debates about data protection and business models in the digital age. 
• The EU's stance on Meta’s ‘pay or consent’ model and any new regulatory measures will shape the future landscape of digital privacy, leading to other jurisdictions taking cues and potentially leading to global shifts in privacy regulations. 
• Meta may need to iterate on its approach based on consumer preferences and concerns. Competitors and tech giants will closely monitor Meta’s strategies, possibly adopting similar models or innovating new solutions. And the overall approach to privacy could evolve to prioritise user control and transparency.

Conclusion

Consent is the cornerstone in matters of privacy and sidestepping it violates the rights of users. The manner in which tech companies foster a culture of consent is of paramount importance in today's digital landscape. As the exploration by Meta in the ‘pay or consent’ model takes place, it faces both opportunities and challenges in balancing user privacy with business sustainability. This situation serves as a critical test case for the tech industry, highlighting the need for innovative solutions that respect privacy while fostering growth with the specificity of dealing with data protection laws worldwide, starting with India’s Digital Personal Data Protection Act, of 2023.

Reference:

• https://ciso.economictimes.indiatimes.com/news/grc/eu-tells-meta-to-address-consumer-fears-over-pay-for-privacy/111946106 
• https://www.wired.com/story/metas-pay-for-privacy-model-is-illegal-says-eu/ 
• https://edri.org/our-work/privacy-is-not-for-sale-meta-must-stop-charging-for-peoples-right-to-privacy/ 
• https://fortune.com/2024/04/17/meta-pay-for-privacy-rejected-edpb-eu-gdpr-schrems/ 

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