#FactCheck - Viral Video of Argentina Football Team Dancing to Bhojpuri Song is Misleading

Executive Summary

A video of Swatantra Bhardwaj is being shared on social media. Another man can also be seen with Bhardwaj in the video. Swatantra Bhardwaj came into the spotlight following an alleged assault involving the father of a protester during a protest by the Cockroach Janta Party at Jantar Mantar. Social media posts claim that the video was recorded immediately after his release from jail and shows him openly threatening people. CyberPeace Research Wing’s Research found the viral claim to be false. Our Research revealed that the video being shared on social media is old. Swatantra Bhardwaj was released from jail on September 17, while our Research found that the video has been available online since June. Therefore, the claim that the video was recorded immediately after Bhardwaj’s release from jail is misleading.

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Claim:

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A Facebook user shared the viral video on September 17, 2026, with the caption: “The Indian judicial system has failed once again... Swatantra Bhardwaj has started again immediately after coming out, even though the court has imposed a condition that he will not make any statements to the media. But listen to what he is saying.” The post link, archive link, and screenshot are provided below.

https://www.facebook.com/reel/1349048917301713 

https://archive.ph/xCkWd

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Fact Check

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To verify the date of Swatantra Bhardwaj’s release from jail, we searched Google using relevant keywords. During the search, we found a report published by Aaj Tak on September 18, 2026. According to the report, social media influencer Swatantra Bhardwaj, who came into the spotlight following an alleged assault during a protest at Jantar Mantar, was released from Delhi’s Tihar Jail on September 17, 2026, after being granted bail by the court and completing the necessary legal formalities. Soon after walking out of the main gate of the jail, he ran towards a taxi and left without speaking to the media personnel present there. The post link and screenshot are provided below.

https://www.aajtak.in/india/story/swatantra-bhardwaj-released-tihar-jail-jantar-mantar-protest-assault-case-ntc-ntyv-rpti-2645424-2026-09-18 

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To verify the authenticity of the viral claim, we conducted a reverse image search of the keyframes from the video. During the search, we found the same video on a YouTube channel, where it was published on September 7, 2026. Meanwhile, the report mentioned above clearly states that Swatantra Bhardwaj was released from Delhi’s Tihar Jail on September 17, 2026. The report link and screenshot are provided below. 

https://www.youtube.com/watch?v=-3V0pwJbpwg 

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At the end of our Research, we found another version of the same video, which was uploaded by a person identified as Vaibhav Kumar on June 26, 2026. The post link and screenshot are provided below. 

https://www.instagram.com/reels/DaBs7Q-T8xc/ 

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Conclusion

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Our Research found that the video being shared on social media is old. Swatantra Bhardwaj was released from jail on September 17, while our Research found that the video had already been available online since June. Therefore, the claim that the video was recorded immediately after Bhardwaj’s release from jail is misleading.

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Introduction 

In today’s digital world, data has emerged as the new currency that influences global politics, markets, and societies. Companies, governments, and tech behemoths aim to control data because it accords them influence and power. However, a fundamental challenge brought about by this increased reliance on data is how to strike a balance between privacy protection and innovation and utility.

In recognition of these dangers, more than 200 Nobel laureates, scientists, and world leaders have recently signed the Global Call for AI Red Lines. Governments are urged by this initiative to create legally binding international regulations on artificial intelligence by 2026. Its goal is to stop AI from going beyond moral and security bounds, particularly in areas like political manipulation, mass surveillance, cyberattacks, and dangers to democratic institutions.

One way to address the threat to privacy is through pseudonymization, which makes it possible to use data valuable for research and innovation by substituting personal identifiers for artificial ones. Pseudonymization thus directly advances the AI Red Lines initiative's mission of facilitating technological advancement while lowering the risks of data misuse and privacy violations.

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The Red Lines of AI: Why do they matter?

The Global Call for AI Red Lines initiative represents a collective attempt to impose precaution before catastrophe, which was done with the objective of recognising the Red Lines in the use of AI tools. Thus, anything that unites the risks of using AI is due to the absence of global safeguards. Some of these Red Lines can be understood as; 

• Cybersecurity breaches in the form of exposure of financial and personal data due to AI-driven hacking and surveillance. 
• Occurrence of privacy invasions due to endless tracking.
• Generative AI can also help to create realistic fake content, undermining the trust of public discourses, leading to misinformation. 
• Algorithmic amplification of polarising content can also threaten civic stability, leading to a demographic disruption. 

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Legal Frameworks and Regulatory Landscape

The regulations of Artificial Intelligence stand fragmented across jurisdictions, leaving significant loopholes aside. Some of the frameworks already provide partial guidance. The European Union’s Artificial Intelligence Act 2024 bans “unacceptable” AI practices, whereas the US-China Agreement also ensures that nuclear weapons remain under human, not machine-controlled. The UN General Assembly has adopted resolutions urging safe and ethical AI usage, with a binding and elusive global treaty. 

On the front of data protection, the General Data Protection Regulations (GDPR) of EU offers a clear definition of Pseudonymisation under Article 4(5). It also describes a process where personal data is altered in a way that it cannot be attributed to an individual without additional information, which must be stored securely and separately. Importantly, pseudonymised data still qualifies as “personal data” under GDPR.  However, India’s Digital Personal Data Protection Act (DPDP) 2023 adopts a similar stance. It does not explicitly define pseudonymisation in broad terms, such as “personal data” by including potentially reversible identifiers. According to Section 8(4) of the Act, companies are meant to adopt appropriate technical or organisational measures. International bodies and conventions like the OECD Principles on AI or the Council of Europe Convention 108+ emphasize accountability, transparency, and data minimisation. Collectively, these instruments point towards pseudonymization as a best practice, though interpretations of its scope differ. 

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Strategies for Corporate Implementation 

For a company, pseudonymisation is not just about compliance, it is also a practical solution that offers measurable benefits. By pseudonymising data, businesses can get benefits, such as; 

• Enhancing Privacy protection by masking identifiers like names or IDs by reducing the impact of data breaches. 
• Preserving Data Utility, unlike having a full anonymisation, pseudonymisation also retains patterns that are essential for analytical innovation. 
• Facilitating data sharing can allow organizations to collaborate with their partners and researchers while maintaining proper trust.  

According to these benefits, competitive advantages get translated to clauses where customers find it more likely to trust organizations that prioritise data protection, while pseudonymisation further enables the firms to engage in cross-border collaboration without violating local data laws. 

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Balancing Privacy Rights and Data Utility

Balancing is a central dilemma; on one side lies the case of necessity over data utility, where companies, researchers and governments rely on large datasets to enhance the scale of AI innovation. On the other hand lies the question of the right to privacy, which is a non-negotiable principle protected under the international human rights law. 

Pseudonymisation offers a practical compromise by enabling the use of sensitive data while reducing the privacy risks. Taking examples of different domains, such as healthcare, it allows the researchers to work with patient information without exposing identities, whereas in finance, it supports fraud detection without revealing the customer details. 

Conclusion

The rapid rise of artificial intelligence has led to the outpacing of regulations, raising urgent questions related to safety, fairness and accountability. The global call for recognising the AI red lines is a bold step that looks in the direction of setting universal boundaries. Yet, alongside the remaining global treaties, practical safeguards are also needed. Pseudonymisation exemplifies such a safeguard, which is legally recognised under the GDPR and increasingly relevant in India’s DPDP Act. It balances the twin imperatives of privacy, protection, and data utility. For organizations, adopting pseudonymisation is not only about ensuring regulatory compliance, rather, it is also about building trust, ensuring resilience, and aligning with the broader ethical responsibilities in this digital age. As the future of AI is debatable, the guiding principles also need to be clear. By embedding techniques for preserving privacy, like pseudonymisation, into AI systems, we can take a significant step towards developing a sustainable, ethical and innovation-driven digital ecosystem. 

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References 

https://www.theverge.com/ai-artificial-intelligence/782752/ai-global-red-lines-extreme-risk-united-nations

https://www.techaheadcorp.com/blog/shadow-ai-the-risks-of-unregulated-ai-usage-in-enterprises/

https://planetmainframe.com/2024/11/the-risks-of-unregulated-ai-what-to-know/

https://cepr.org/voxeu/columns/dangers-unregulated-artificial-intelligence

https://www.forbes.com/sites/bernardmarr/2023/06/02/the-15-biggest-risks-of-artificial-intelligence/ 

https://artificialintelligenceact.eu/the-act/

Executive Summary:

Given that AI technologies are evolving at a fast pace in 2024, an AI-oriented phishing attack on a large Indian financial institution illustrated the threats. The documentation of the attack specifics involves the identification of attack techniques, ramifications to the institution, intervention conducted, and resultant effects. The case study also turns to the challenges connected with the development of better protection and sensibilisation of automatized threats. 

Introduction

Due to the advancement in AI technology, its uses in cybercrimes across the world have emerged significant in financial institutions. In this report a serious incident that happened in early 2024 is analysed, according to which a leading Indian bank was hit by a highly complex, highly intelligent AI-supported phishing operation. Attack made use of AI’s innate characteristic of data analysis and data persuasion which led into a severe compromise of the bank’s internal structures.

Background

The chosen financial institution, one of the largest banks in India, had a good background regarding the extremity of its cybersecurity policies. However, these global cyberattacks opened up new threats that AI-based methods posed that earlier forms of security could not entirely counter efficiently. The attackers concentrated on the top managers of the bank because it is evident that controlling such persons gives the option of entering the inner systems as well as financial information. 

Attack Execution

The attackers utilised AI in sending the messages that were an exact look alike of internal messages sent between employees. From Facebook and Twitter content, blog entries, and lastly, LinkedIn connection history and email tenor of the bank’s executives, the AI used to create these emails was highly specific. Some of these emails possessed official formatting, specific internal language, and the CEO’s writing; this made them very realistic. 

 It also used that link in phishing emails that led the users to a pseudo internal portal in an attempt to obtain the login credentials. Due to sophistication, the targeted individuals thought the received emails were genuine, and entered their log in details easily to the bank’s network, thus allowing the attackers access. 

Impact

It caused quite an impact to the bank in every aspect. Numerous executives of the company lost their passwords to the fake emails and compromised several financial databases with information from customer accounts and transactions. The break-in permitted the criminals to cease a number of the financial’s internet services hence disrupting its functions and those of its customers for a number of days. 

 They also suffered a devastating blow to their customer trust because the breach revealed the bank’s weakness against contemporary cyber threats. Apart from managing the immediate operations which dealt with mitigating the breach, the financial institution was also toppling a long-term reputational hit. 

Technical Analysis and Findings

1. The AI techniques that are used in generation of the phishing emails are as follows: 

•  The attack used powerful NLP technology, which was most probably developed using the large-scaled transformer, such as GPT (Generative Pre-trained Transformer). Since these models are learned from large data samples they used the examples of the conversation pieces from social networks, emails and PC language to create quite credible emails. 

 Key Technical Features: 

•  Contextual Understanding: The AI was able to take into account the nature of prior interactions and thus write follow up emails that were perfectly in line with prior discourse. 
•  Style Mimicry: The AI replicated the writing of the CEO given the emails of the CEO and then extrapolated from the data given such elements as the tone, the language, and the format of the signature line. 
•  Adaptive Learning: The AI actively adapted from the mistakes, and feedback to tweak the generated emails for other tries and this made it difficult to detect. 

2. Sophisticated Spear-Phishing Techniques

Unlike ordinary phishing scams, this attack was phishing using spear-phishing where the attackers would directly target specific people using emails. The AI used social engineering techniques that significantly increased the chances of certain individuals replying to certain emails based on algorithms which machine learning furnished. 

 Key Technical Features: 

•  Targeted Data Harvesting: Cyborgs found out the employees of the organisation and targeted messages via the public profiles and messengers were scraped. 
•  Behavioural Analysis: The latest behaviour pattern concerning the users of the social networking sites and other online platforms were used by the AI to forecast the courses of action expected to be taken by the end users such as clicking on the links or opening of the attachments. 
•  Real-Time Adjustments: These are times when it was determined that the response to the phishing email was necessary and the use of AI adjusted the consequent emails’ timing and content. 

3. Advanced Evasion Techniques

The attackers were able to pull off this attack by leveraging AI in their evasion from the normal filters placed in emails. These techniques therefore entailed a modification of the contents of the emails in a manner that would not be easily detected by the spam filters while at the same time preserving the content of the message. 

Key Technical Features: 

•  Dynamic Content Alteration: The AI merely changed the different aspects of the email message slightly to develop several versions of the phishing email that would compromise different algorithms. 
•  Polymorphic Attacks: In this case, polymorphic code was used in the phishing attack which implies that the actual payloads of the links changed frequently, which means that it was difficult for the AV tools to block them as they were perceived as threats. 
•  Phantom Domains: Another tactic employed was that of using AI in generating and disseminating phantom domains, that are actual web sites that appear to be legitimate but are in fact short lived specially created for this phishing attack, adding to the difficulty of detection. 

4. Exploitation of Human Vulnerabilities

This kind of attack’s success was not only in AI but also in the vulnerability of people, trust in familiar language and the tendency to obey authorities. 

Key Technical Features: 

•  Social Engineering: As for the second factor, AI determined specific psychological principles that should be used in order to maximise the chance of the targeted recipients opening the phishing emails, namely the principles of urgency and familiarity. 
•  Multi-Layered Deception: The AI was successfully able to have a two tiered approach of the emails being sent as once the targeted individuals opened the first mail, later the second one by pretext of being a follow up by a genuine company/personality. 

Response

On sighting the breach, the bank’s cybersecurity personnel spring into action to try and limit the fallout. They reported the matter to the Indian Computer Emergency Response Team (CERT-In) to find who originated the attack and how to block any other intrusion. The bank also immediately started taking measures to strengthen its security a bit further, for instance, in filtering emails, and increasing the authentication procedures. 

 Knowing the risks, the bank realised that actions should be taken in order to enhance the cybersecurity level and implement a new wide-scale cybersecurity awareness program. This programme consisted of increasing the awareness of employees about possible AI-phishing in the organisation’s info space and the necessity of checking the sender’s identity beforehand.

Outcome

Despite the fact and evidence that this bank was able to regain its functionality after the attack without critical impacts with regards to its operations, the following issues were raised. Some of the losses that the financial institution reported include losses in form of compensation of the affected customers and costs of implementing measures to enhance the financial institution’s cybersecurity. However, the principle of the incident was significantly critical of the bank as customers and shareholders began to doubt the organisation’s capacity to safeguard information in the modern digital era of advanced artificial intelligence cyber threats. 

 This case depicts the importance for the financial firms to align their security plan in a way that fights the new security threats. The attack is also a message to other organisations in that they are not immune from such analysis attacks with AI and should take proper measures against such threats.

Conclusion

The recent AI-phishing attack on an Indian bank in 2024 is one of the indicators of potential modern attackers’ capabilities. Since the AI technology is still progressing, so are the advances of the cyberattacks. Financial institutions and several other organisations can only go as far as adopting adequate AI-aware cybersecurity solutions for their systems and data. 

 Moreover, this case raises awareness of how important it is to train the employees to be properly prepared to avoid the successful cyberattacks. The organisation’s cybersecurity awareness and secure employee behaviours, as well as practices that enable them to understand and report any likely artificial intelligence offences, helps the organisation to minimise risks from any AI attack.

Recommendations

1. Enhanced AI-Based Defences: Financial institutions should employ AI-driven detection and response products that are capable of mitigating AI-operation-based cyber threats in real-time. 
2.  Employee Training Programs: CYBER SECURITY: All employees should undergo frequent cybersecurity awareness training; here they should be trained on how to identify AI-populated phishing. 
3.  Stricter Authentication Protocols: For more specific accounts, ID and other security procedures should be tight in order to get into sensitive ones. 
4.  Collaboration with CERT-In: Continued engagement and coordination with authorities such as the Indian Computer Emergency Response Team (CERT-In) and other equivalents to constantly monitor new threats and valid recommendations. 
5.  Public Communication Strategies: It is also important to establish effective communication plans to address the customers of the organisations and ensure that they remain trusted even when an organisation is facing a cyber threat. 

Through implementing these, financial institutions have an opportunity for being ready with new threats that come with AI and cyber terrorism on essential financial assets in today’s complex IT environments.

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