#FactCheck- AI-Generated Video Falsely Claims Iran Attack on Apple, Microsoft in Israel

Introduction
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" सर्वे भवन्तु सुखिनः, सर्वे सन्तु निरामयाः " May all be happy, may all be free from suffering. This timeless invocation reflects a vision of collective well-being, where progress is meaningful only when shared, and protection extends to every individual in society. This very philosophy lies at the heart of Corporate Social Responsibility, which seeks to ensure that growth is not isolated or unequal, but inclusive, ethical, and mindful of the broader social good.  

At its core, Corporate Social Responsibility is not merely a statutory obligation, it is a reflection of a deeper ethical commitment, an acknowledgement that growth must carry with it a sense of duty towards society. In many ways, CSR embodies the idea that progress without responsibility is incomplete, and that corporations, as key actors shaping modern life, must help safeguard the very communities they engage with.
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Reframing Digital Literacy Through Cyber Safety in CSR Frameworks
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In India, this moral vision has been given a legal structure under the Companies Act, 2013, CSR Schedule VII, which mandates certain classes of companies to allocate a portion of their profits towards socially beneficial activities. Section 135 of the Act requires companies meeting specified financial thresholds to undertake CSR initiatives, guided by principles of inclusivity, sustainability, and social welfare. The underlying values are clear, CSR is intended not as charity, but as a strategic and accountable contribution to societal development.

Schedule VII of the Act further outlines the broad areas that qualify as CSR, including “Education and Digital Literacy”, gender equality, rural development, and measures for reducing inequalities. Within this framework, promoting “digital literacy” has increasingly been recognised as a legitimate and necessary CSR activity, especially in the context of a rapidly digitising society like India.

However, the current understanding of digital literacy within CSR remains incomplete. It often emphasises access and usage, teaching individuals how to navigate digital platforms, use devices, and engage with online services. What remains insufficiently addressed is the question of safety. In an environment where cyber fraud, data breaches, online harassment, and identity theft are becoming increasingly common, digital literacy without cyber awareness risks becoming a partial and potentially harmful intervention.

Embedding cyber awareness and capacity building within ‘digital literacy’ in explicit form is therefore not optional, it is essential. This includes equipping individuals with the ability to recognise online threats, protect personal data, understand digital consent, and respond effectively to cyber risks. It also requires recognising that vulnerable populations, including first-time internet users, women, and marginalised communities, often face disproportionate exposure to cyber harm.

“It is pertinent to note that Cybersecurity awareness training is relevant to CSR but is not yet consistently implemented as an explicit CSR activity. It is often included indirectly within digital literacy programs, highlighting the need for a more structured, progressive and integrated approach.”

Given this reality, there is a strong case for explicitly recognising cyber awareness as a distinct and integral component of CSR activities, rather than treating it as an implicit subset of digital literacy. Doing so would not only align CSR with contemporary societal risks but also ensure that corporate interventions move beyond enabling access to actively ensuring safety.

In a digital society, empowerment without protection is incomplete. If CSR is to truly reflect its foundational values, it must evolve to address not just the opportunities of the digital age, but also its risks.
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Why Cyber Safety Must Be Central to CSR
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The current state of digital ecosystems, which used to operate as secondary systems, now functions as essential systems that support government operations, banking systems, educational institutions, and social communication. The digital environment has its vulnerabilities, which create direct dangers for people in society. The elderly, first-time internet users, and rural communities face higher cyber threat risks because they often lack knowledge and protective resources on responsible use. The implementation of CSR initiatives that provide digital access to these groups, along with how to handle risks, will create greater benefit for their safety. Organisations must encourage the implementation of cyber safety training in their CSR programs because doing so will create value while fulfilling their ethical obligations. The empowerment process needs to achieve complete success, which protects people from any potential dangers according to the "do no harm" principle.
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Key Components of CyberPeace-Aligned Digital Literacy
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To make CSR initiatives more effective and future-ready, organisations should incorporate the following elements into their digital literacy programs:

1. Cyber Awareness and Risk Recognition: The training program teaches participants how to recognise typical security threats, which include phishing attacks and scams, deepfake technology and misinformation.
2. Data Protection and Privacy Literacy: The program teaches users how to protect their personal information, together with the process of giving consent and the methods used to handle their online presence. 
3. Responsible Digital Behaviour: The program teaches people how to use the internet responsibly by showing them how to make ethical decisions that require both respect and accountability while understanding the legal consequences of their actions. 
4. Incident Response and Reporting Mechanisms: The program teaches users about cyber incident response, which includes all reporting methods and available support resources. 
5. Inclusion-Focused Design: The program develops specific solutions which protect various demographic groups from their particular vulnerabilities while maintaining accessibility and essential programmatic relevance.

Policy and Institutional Alignment
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The integration of cyber safety into corporate social responsibility lets organisations achieve their national objectives, which include:

• Strengthening digital trust and resilience
• Supporting safe digital inclusion initiatives
• Complementing the efforts of institutions working on cybersecurity awareness and capacity building

The structured approach requires organisations to execute three specific steps, which include:

• Partnering with cybersecurity organisations and civil society
• Developing standardised cyber awareness modules
• The organisation will use behavioural change indicators to evaluate its impact instead of relying on access metrics.

The Way Forward
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Digital-era Corporate Social Responsibility needs to transition from its present state of providing access to digital resources toward establishing secure online platforms for users. The understanding of digital literacy needs to shift from its current status as a technical ability toward its new definition as a social competency that encompasses safety, responsibility and resilience training.

Companies need to understand their digital transformation obligations because their digital transformation efforts require them to handle all associated risks. The implementation of cyber safety within corporate social responsibility frameworks will enable organisations to develop a secure and trustworthy digital environment that includes all users.

Conclusion
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The implementation of corporate social responsibility needs to fulfil its core mission of creating societal benefits through inclusive practices that span all current digital possibilities and their associated security threats. The field of digital literacy requires a new framework that combines digital safety practices with its existing educational materials.

The digital safety practice ensures that people obtain essential knowledge and skills that enable them to use digital resources securely when they access online content. The process of accomplishing shared community prosperity needs to establish a framework that benefits every person through social advancement and the protection of their rights.
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References
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• https://upload.indiacode.nic.in/schedulefile?aid=AC_CEN_22_29_00008_201318_1517807327856&rid=79
• https://www.allresearchjournal.com/archives/2025/vol11issue4/PartF/11-5-60-511.pdf
• https://www.unesco.org/en/dtc-finance-toolkit-factsheets/corporate-social-responsibility-csr
• https://www.investopedia.com/terms/c/corp-social-responsibility.asp
• https://digitalmarketinginstitute.com/blog/corporate-16-brands-doing-corporate-social-responsibility-successfully
• https://www.imd.org/blog/sustainability/csr-strategy/

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Introduction
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In April 2026, there was a fascinating example of the risks of generative artificial intelligence (AI). An Indian medical student, aged 22, developed a fake AI-driven influencer "Emily Hart" and leveraged the persona to amass a substantial social media following, engagement and revenue. 

It isn't just a case of online fraud. It is a turning point in the nature of influence, veracity, and profitability in the digital world. Ultimately, it poses a troubling question. If users can't tell the difference between real and fake people, then what is online trust?
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The Making of a Synthetic Influencer

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“Emily Hart” was a young, conservative American nurse. The identity was completely made-up, created with the help of AI programs that produced eerily realistic images, captions and engagement techniques.

The creator did not work with random content. They crafted the influencer to cater to a particular audience. With this in mind, the account was able to target conservatives in the United States who are politically active. It is reported that some of its posts have achieved millions of views, and within a few months, the influencer had thousands of followers.

Monetisation followed naturally. The account owner monetised through subscriptions and the sale of merchandise, reportedly earning thousands of dollars a month with fewer than an hour a day of "work" on the account.

The disproportionate effort and reward is what is interesting about this case. This is a unique example of how people can now use very little capital to create digital personas that attract value.

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Why It Worked: Engagement, Identity, and Algorithmic Incentives

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The "Emily Hart" case was no accident. It was enabled by three complementary factors.

First, identity targeting was crucial. The persona was constructed to fit a particular worldview and culture, making it more relevant and resonating with the target audience. AI platforms were even deployed to better target and position the persona, and it is suggested that micro-targeting would increase engagement.

Second, it was amplified by algorithms. Social media algorithms favour engagement, sometimes favouring emotional and divisive content. The account exploited this by producing visually appealing content with a strong political message, what the creator called "engageable" content.

Third, the authenticity of the AI content minimised distrust. Generative models have become so realistic that it is hard to tell if images are real or not. Specialists point out that AI increases the credibility and scalability of fake profiles, increasing their influence and reach.

All of this combined to make deception profitable. 

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The Blurring of Authenticity in Digital Spaces
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The "Emily Hart" phenomenon is emblematic of a broader shift in authenticity. Historically, influence was correlated with human personalities who establish trust over time. But AI upends this paradigm by allowing the creation of entirely fabricated personalities capable of mimicking, and even surpassing, human influencers.

This has two immediate consequences.

First, the truth is harder to discern. While platforms might require that AI-generated content be disclosed, there are inconsistencies in how this is policed. Here, the account apparently didn't disclose until it was banned for fraud.

Second, authenticity may not be as important to consumers. Consumers may view content for ideological or emotional reasons, rather than for its accuracy. This indicates that the rise of synthetic influencers is not just a technical problem but also a behavioural one.

The implication is stark. The internet is evolving into a place where authenticity is more important than truth.
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Economic Incentives and the Rise of Synthetic Monetisation
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The key difference between this fraud and previous ones is the business model. This creator didn't break into a computer or steal personal information. He cultivated an audience and sold attention.

This is an example of how the internet economy works. Attention is a commodity and platforms aim to generate it. AI reduces the cost of creating attention-generating artefacts, enabling people to amplify their reach.

This gives rise to synthetic monetisation. Online characters can be developed, fine-tuned and leveraged as money-spinning assets. In this case, identity is a product.

This raises regulatory challenges. Current laws on fraud, advertising and consumer protection may not be sufficient to cover cases of deceptive content sourced from an identity.
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Platform Responsibility and Enforcement Gaps
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The role of platforms in enabling such scenarios cannot be overlooked. Although platforms have policy guidelines on disclosure of AI-generated content, these are inconsistently applied.

In the case of "Emily Hart", the account apparently existed for some time before being shut down for scamming. This implies that either the ability to detect such accounts is weak or the tools used are reactive.

The challenge is structural. Companies are rewarded for engagement, and fake accounts can help to achieve this. But they must also promote authenticity and protect against fraud.

This presents a challenge between commercial interests and user safety. Without enforcement, synthetic influencers will become more prevalent. 
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Policy Implications: Rethinking Trust and Verification
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^{The "Emi}ly Hart" incident highlights a number of policy issues.

First, disclosure policies must be improved and harmonised. Consumers need to be clear when content is generated by AI, and platforms need to police this.

Second, identity verification needs to be updated. Classic forms of verification may not hold up in an era of imaginary characters amassing legions of fans. Alternative digital verification may be needed.

Third, new regulations should apply to synthetic identities. This means clarifying distinctions between art, commerce and fraud.

Finally, digital literacy becomes critical. Consumers need to be equipped to operate in a space where virtual personas aren't always human.

Conclusion
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The rise of "Emily Hart" is not just an example of one person using AI to make money. It is a glimpse of a digital revolution.

AI is redefining how influence can be generated, trust can be established and value can be monetized. As digital personas become more realistic, the distinction between human and machine will remain unclear.

The challenge will not be to stop AI being used to generate content. It is to ensure that the systems that mediate our online interactions are able to tell the difference, and that we are not left on our own to sort it all out.

When anyone can make a convincing identity for themselves, trust will no longer be a given. It will need to be engineered, policed and protected. 

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Introduction
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The recent investigation of Patan Cyber Crime Police as part of Operation Mule Hunt 2.0 reveals the sheer scale and intricacy of India's burgeoning cyber fraud economy. Police found that a total of 13 current accounts were being operated at a cooperative bank in the Patan district of Gujarat and used for siphoning 398.43 crore of cyber fraud transaction data on 228 cybercrime cases across states. Further investigations against 14 current account holders and intermediaries show the indispensability of mule accounts in laundering criminal money. The recent incident cannot be taken as isolated; the story points at a formalised and industrialised fraud economy with a robust banking infrastructure, a growing payment gateway, and complex networks.
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What Is a Mule Account and Why Should You Care?
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The term "mule account" is benign but plays a critical role in modern cybercrime networks. The Reserve Bank of India defines a mule account as a bank account that serves as a vehicle to transfer money proceeds from unlawful transactions and can be operated by people coerced by the prospect of high earnings or by way of inducement.

This mechanism can be witnessed through the investigation of the Patan cybercrime incident, where an investor can be defrauded by a fake investment website, employment fraud, or a digital arrest scheme. After transactions from the victim account, funds would quickly flow into the mule account, which would be held by a legitimate KYC customer. These transactions would then be passed on, between 1 lakh and 5 lakh transactions within hours, to multiple accounts as alleged by the Indian Cyber Crime Coordination Centre (I4C) before they get difficult to trace by being passed through informal channels or converted to cryptocurrency.

In the Patan case, it is alleged that the middlemen enticed locals and offered commissions to open firms and current accounts at Harij Nagrik Sahakari Bank and subsequently gave up their ATM cards, checkbooks, SIMs, and net banking facilities to the operators of the account. It is estimated that such accounts channeled an amount of 398.43 crore to 228 Indian cybercrime cases.

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The Scale of India's Mule Account Crisis

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The scale of the mule account ecosystem is reflected in India's rapidly worsening cybercrime statistics. As of data from the National Cyber Crime Reporting Portal (NCCRP), a total of 22.68 lakh complaints were registered in 2024, a jump by 42% from 2023. This was not even half the rate of financial loss, which jumped by 206% in 2023 (22,845 crore) and stood at 22,495 crore in 2025 (complaints jumped to 28.15 lakh). The increase in fraudulent transactions therefore outweighs the stability in financial losses significantly.

Mule accounts are the backbone of this crime network. To curb this phenomenon, the Indian Cyber Crime Coordination Centre (I4C) launched a Suspect Registry along with Indian banks and financial institutions in September 2024. 24.67 lakh accounts of suspected mules were identified in this, preventing over 8,031 crore in fraudulent transactions. Despite these efforts, a recent statement from the ED found over 12,000 crore being routed via mule accounts, shell firms, and cryptocurrency.

This isn't isolated to certain banks. 2024 alone saw over 65,000 mule accounts detected in Karnataka. By analyzing the Citizen Financial Cyber Frauds Reporting and Management System, about 40,000 such accounts were detected in SBI branches, and thousands more were detected across the PNB, Canara Bank, Kotak Mahindra Bank, and Airtel Payments Bank. The Patan case also clearly highlights that cooperative banks' lack of compliance and lower levels of transaction-monitoring systems contribute to easily creating and using mule accounts.

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Operation Mule Hunt: Gujarat's Coordinated Offensive

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This bust in Patan is just one manifestation of a much wider coordinated effort by the state government. Operation Mule Hunt 1.0, which ran from November to December 2025 across the state of Gujarat, was a month-long campaign by Gujarat Police's Cyber Centre of Excellence (CCOE) that unearthed 2,289 crore of fraudulent transactions, led to the registration of 565 FIRs, arrest of 638 accused, and impounding of 913 mule accounts with connections to over 4,000 cases of cybercrime nationwide.

This was followed up with the second installment of the operation, which was kicked off in all districts of Gujarat in 2026. The two-week campaign, which began across the state on January 8 this year, resulted in the Surat City Police alone arresting 77 people and uncovering close to 23.85 crore in fraudulent transactions. In what looks like one of the single largest single-district bust-ups in the operation, the Patan incident itself, with a staggering 398.43 crore routed through only 13 accounts, is remarkable.

The extraordinary nature of the operation is seen in the intelligence capabilities that drove it. It wasn't that police accidentally stumbled upon the Patan network; they worked back on it. After using data from the union government’s inter-agency platform, SAMANVAYA, a coordination platform for data on cybercrimes and the NCCRP, they traced suspicious clusters of transactions in the Harij Nagrik Sahakari Bank accounts to build a chain of evidence connecting the accountholders to the middlemen and, from the middlemen, to the whole ring of fraud. Twenty accused have been chargesheeted under the Bharatiya Nyaya Sanhita (BNS), and fourteen have been arrested, while six are still absconding.

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The Human Cost Nobody Talks About

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Behind every crore of scam money lies a real person who actually lost the real money. Of the 75%+ fraud losses incurred in 2025, 75% are from investment scams alone. Victims of stock trading scams lost ₹4,636 crore, spread across 2.28 lakh complaints filed in 2024. "Digital arrest" scams, in which fraudsters posing as law enforcement officials psychologically blackmail the victims to transfer money,  claimed ₹2,576 crore between 2022 and the first quarter of 2025.

For the victims it's never about the money: it's the retired teacher's lifetime savings from Chhattisgarh, the small trader's capital from Rajkot, the emergency money of the Bhopal family, or just savings from an ordinary person. And the mule accounts' networks are why most of it is never retrieved. Once the money is thrown into the layering chain, it's exponentially more difficult to trace it after every jump.

Then there's another category of victims that often gets overlooked, and they are the mule account holders themselves, many being semi-literate people from semi-urban or rural backgrounds approached with ₹10,000 in commission and with no awareness about the legalities of lending their bank details. With the BNS now they stand to get convicted for grave crimes, but the awareness of this trap is very low.

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Recommendations and Suggestions

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This isn't something India is facing passively. I4C, along with RBI, has developed Mule Account Hunter software. This software can be used by banks for the detection of suspect accounts through the use of behavioral analysis, device intel, and transaction pattern recognition. The Union Home Minister has directly asked all cooperative banks across the country to adopt this software at the earliest. Failure to do so, he warned, would make consumer safety from cyber fraud incomplete.

Apart from technology, three other areas need to go hand in hand: stringent KYC enforcement for cooperative and small finance banks; the prime locations of the mule recruitment network; greater awareness for the masses regarding the criminal liability one takes up when lending their accounts; and efficient inter-agency coordination so that the intelligence gathered on platforms like SAMANVAYA is converted into arrests before the accounts are dumped and the network reforms in another location.

Operation Mule Hunt 2.0 proves that this is feasible. 13 accounts in a small district of Gujarat. 398 crore. 228 victims. 14 arrested. The pipeline did exist, and it has been broken.

Yet, even as one network is broken, another is forming, somewhere right now. The accounts will appear legitimate. The holders of these accounts may not even realize what they have got into. That is the true danger of the mule accounts and work that cannot stop.

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Conclusion

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The Patan investigation has clearly shown that mule accounts have now moved from being a subsidiary tool of financial crime to becoming the infrastructure that underpins the economy of cyber-fraud in India. Every financial fraud, including investment fraud, digital arrest fraud, and phishing scams, is backed by a string of real bank accounts where the proceeds of crime are transferred and the trail is obscured. Though attempts such as the I4C Suspect Registry have made attempts to break down this network, it remains an overwhelming task. Robust KYC norms, real-time monitoring of transactions, and coordination between banks, police, and regulators are the key in preventing further industrialisation of cyber financial fraud in India.

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References

1. https://timesofindia.indiatimes.com/city/ahmedabad/operation-mule-hunt-2-0-gujarat-
2. police-bust-rs-398-43-crore-cyber-fraud-14-held/articleshow/131594240.cms?utm_source=contentofinterest&utm_medium=text&utm_campaign=cppst
3. https://the420.in/india-cybercrime-2024-42-percent-spike-sims-imei-mule-accounts/
4. https://www.thehansindia.com/news/national/ed-explains-how-mule-accounts-and-crypto-networks-enabled-12000-crore-cyber-fraud-1047606
5. https://www.zigram.tech/article/mule-accounts-tier-1-tier-2-cities-india/
6. https://risk.lexisnexis.com/global/en/insights-resources/article/stopping-money-mules-in-india
7. https://timesofindia.indiatimes.com/city/ahmedabad/operation-mule-hunt-2-0-gujarat-police-bust-rs-398-43-crore-cyber-fraud-14-held/articleshow/131594240.cms

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