#FactCheck: Viral Video of Armless Woman Performing Gymnastics Is AI-Generated
Executive Summary
A video of a young woman without arms performing gymnastics has been widely shared on social media. In the video, the woman can be seen without both arms, yet she performs several difficult gymnastics moves with remarkable ease and confidence. Her impressive physical balance and practice have left viewers amazed. Users sharing the video are praising not only her talent but also her courage, confidence and determination. Many users are also describing it as an inspiring example of overcoming challenges and pursuing one's dreams with unwavering spirit.
However, a probe by the Research Wing of CyberPeace found that the video being shared on social media is not genuine but was generated using Artificial Intelligence (AI). The video shows the young woman performing difficult gymnastics moves with apparent ease, but a technical analysis revealed signs of AI-generated content. Therefore, sharing the video as a real incident or as the performance of an actual gymnast is misleading.
Claim:
A video circulating on social media shows a young woman without arms performing gymnastics, with users hailing her courage and determination.
https://www.facebook.com/reel/1793394471856936

Fact Check
During our research of the viral video, we first conducted a reverse image search of its different keyframes. We also searched Google using relevant keywords. However, we could not find the viral video in any credible media report.
During the reverse search, we found the same viral video on the Instagram account @arenaathletics1, where it was posted on September 13. The post also carries an “AI-generated content” label. The video has garnered more than 20 million views. Several users in the comment section have also identified the video as AI-generated.

We then checked the viral video using the AI detection tool Hive Detect. In its analysis, the tool identified the video as likely AI-generated, assigning it a 93.1 percent score for AI-generated content.

Additionally, six detectors on Deepfake-O-Meter identified the viral video as AI-generated with a high probability.

Conclusion
Our research found sufficient evidence to establish that the viral video showing a young woman without arms performing gymnastics is not genuine. The video was found on an Instagram account carrying an “AI-generated content” label, while analysis using AI detection tools, including Hive Detect and Deepfake-O-Meter, also indicated a high likelihood of AI-generated content. Therefore, the video is AI-generated and is being misleadingly shared as a real-life performance, rather than an authentic video of a gymnast.
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SVIMS Director and Vice-Chancellor B. Vengamma lighting a lamp to formally launch the cybercrime awareness programme conducted by the police department for the medical students in Tirupati on Wednesday.
An awareness meet on safe Internet practices was held for the students of Sri Venkateswara University University (SVU) and Sri Venkateswara Institute of Medical Sciences (SVIMS) here on Wednesday.
“Cyber criminals on the prowl can easily track our digital footprint, steal our identity and resort to impersonation,” cyber expert I.L. Narasimha Rao cautioned the college students.
Addressing the students in two sessions, Mr. Narasimha Rao, who is a Senior Manager with CyberPeace Foundation, said seemingly common acts like browsing a website, and liking and commenting on posts on social media platforms could be used by impersonators to recreate an account in our name.
Turning to the youth, Mr. Narasimha Rao said the incognito mode and Virtual Private Network (VPN) used as a protected network connection do not ensure total privacy as third parties could still snoop over the websites being visited by the users. He also cautioned them tactics like ‘phishing’, ‘vishing’ and ‘smishing’ being used by cybercriminals to steal our passwords and gain access to our accounts.
“After cracking the whip on websites and apps that could potentially compromise our security, the Government of India has recently banned 232 more apps,” he noted.
Additional Superintendent of Police (Crime) B.H. Vimala Kumari appealed to cyber victims to call 1930 or the Cyber Mitra’s helpline 9121211100. SVIMS Director B. Vengamma stressed the need for caution with smartphones becoming an indispensable tool for students, be it for online education, seeking information, entertainment or for conducting digital transactions.

Biological data includes biometric information such as fingerprints, facial recognition, DNA sequences, and behavioral traits. Genetic data can be extracted from an individual’s remains long after their death and can continue to identify both that individual and an expanding pool of their living relatives. This persistent identification can significantly reduce privacy over time, revealing genetic characteristics and familial relationships across successive generations.
Key Developments in Privacy Protection for Biological Data:
Legal texts have been created relating to personal data protection and privacy broadly, and can sometimes prove to be poor adaptations specifically for ‘biometric data’ and its safety. Some examples are mentioned below:
- EU and UK- GDPR
GDPR focuses primarily on biometrics in Biological Data while deciphering the technology's immense potential. The EU describes “personal data” under the General Data Protection Regulation (GDPR) including any identifiable information about a particular person. For example, this can include names, identification numbers, location data, and other structured and unstructured data. In addition, the GDPR has more specific requirements around processing sensitive or “special categories of personal data.” These “special categories” include things like genetic and biometric data. For biometric security to work well, citizens' rights must be protected appropriately, and the data collected by private and public concerns must be managed carefully and sensibly.
- USA
California Consumer Privacy Act (CCPA) grants Californian consumers the right to protect their personal information and biometric data including the right to disclosure or access, the right to be forgotten, and data portability. The sale of personal information and the option of opt-out is also given to consumers. Additionally, it contains the right to take legal action, with penalties imposed for violations.
The California Privacy Rights Act was passed on November 3, 2020, and took effect on January 1, 2023, with a lookback period starting January 1, 2022. It introduces sensitive personal information which includes biometric data and other sensitive details.
Virginia's Consumer Data Protection Act, effective from January 1, 2023, designates genetic and biometric data as sensitive data that must be protected.
Illinois' Biometric Information Privacy Act is recognised as the most robust biometric privacy law in the United States. The significance of the Rosenbach v. Six Flags case lies in the Illinois Supreme Court's ruling that a plaintiff does not need to demonstrate additional harm to impose penalties on a BIPA violator. A mere loss of statutory biometric privacy rights is sufficient to warrant penalties.
- India
As per Rule 2(1)(b) of the SPDI Rules, Sensitive Personal Data or Information, including biometric data is included under its meaning. The term ‘biometric data’ has not been defined in the Digital Personal Data Protection Act, 2023. The need for data privacy under the DPDP Act emerges only if such data is subsequently digitised under extraction and manipulation, including notice and consent requirements and penalties.
The Biotech-PRIDE (Promotion of Research and Innovation through Data Exchange) Guidelines of 2021 are aimed at fostering an exchange of information which would thereby enhance research and innovation among various research groups nationwide. These guidelines do not deal with the generation of biological data but are a mechanism to share and exchange information and knowledge generated according to existing laws, rules, regulations and norms of the country. They will ensure data-sharing benefits, maximise use, avoid duplication, maximise integration, ownership of information, better decision-making and equity of access
How is Biological Data vulnerable?
- Biological data is often immutable, meaning it cannot be altered once compromised. Unlike other authentications that can be changed, compromised biometric data poses a permanent risk, making its protection paramount.
- The use of facial recognition technology by law enforcement agencies and the creation of databases by the same also highlights the urgent need for stringent privacy protections.
- Advances in technology, particularly AI and ML, make it easier to collect, analyse, and utilise biometric data by manipulating biometric data. This in turn is leading to new forms of identity theft and fraud that make it necessary to enhance security measures and ethical considerations to prevent abuse.
- Cross-border data transfers raise serious privacy concerns, especially as countries have varying levels and standards of data protection.
- Wearable health-related biometric devices lack the required privacy protections which ends up making the data they collect vulnerable to misuse and breaches.
Future Outlook
With the growing use of biological data, there is likely to be increased pressure on regulatory bodies to strengthen privacy protections. This necessitates a need for enhanced security measures to protect users' identities and further prevent any form of unauthorised access. Future developments should be aimed at including strict consent requirements, and enhanced data security measures, especially for wearable devices. A new legal framework specifically designed to address the challenges posed by biometric data would be welcome. Biological data protection is an emerging need in the digital environment that we live in today.
References
- https://www.cnbc.com/2024/08/17/new-privacy-battle-is-underway-as-tech-gadgets-capture-our-brain-waves.html
- https://www.snrlaw.in/sense-and-sensitivity-sensitive-information-under-indias-new-data-regime/
- https://www.thalesgroup.com/en/markets/digital-identity-and-security/government/biometrics/biometric-data
- https://www.business-standard.com/article/economy-policy/govt-releases-guideline-to-provide-framework-for-sharing-of-biological-data-121073001467_1.html

In Delhi there is a bank branch where a lot of money was stolen from people over the country. This bank branch is where all the money disappeared. The people who did this did not wear masks. Break in at midnight. They just used a passbook a rubber stamp and a form that nobody checked carefully. This is the truth that the people who investigate cybercrime keep finding. The way that cybercriminals get away with the money is not by using a computer it is by using a bank account. The police in Delhi who investigate cybercrime have found that a lot of accounts were opened at bank branches. These accounts were opened using identity documents that were borrowed bought or stolen. Then these accounts were rented out to groups of criminals. One bank branch keeps coming up in complaints. This is not bad luck it is a sign of a bigger problem with how banks check who is opening an account.
These fake accounts, which are called " accounts" are controlled by criminal groups, not the people whose names are on the accounts. These accounts are a part of the cybercrime problem in India. The mistakes that bank branches make which allow these accounts to be opened raise a lot of questions. These questions are about how banks check who is opening an account how they prevent money laundering and how they work with groups to stop cybercrime. The bank accounts are the way that cybercriminals in India get away with the money they steal from people. The cybercrime investigators keep finding bank accounts like the ones at the bank branch, in Delhi, where the money was stolen.
The Anatomy of a Mule Account Network
The pattern is now familiar to investigators. A fraud complaint on the National Cyber Crime Reporting Portal traces a victim's stolen money to a beneficiary account. When police pull the account-opening file, the person named on the KYC documents often denies ever visiting the branch or signing the forms; signature verification frequently shows a mismatch. In one recent Delhi case, a cooperative bank's deputy manager was arrested after a single account he had helped open surfaced in 159 separate cyber fraud complaints from across the country, with transactions worth nearly Rs 68 crore routed through it before detection. Similar investigations have uncovered supply gangs that procure dozens of accounts at a time using POS machines, stacks of ATM cards, and cheque books belonging to different people and rent them out to fraudsters as ready-made conduits for stolen money.
What makes a single branch or a small cluster of accounts significant is what it reveals about entry-point failure. Investigators do not describe these as sophisticated hacking operations; they describe them as verification failures as are accounts opened without the mandatory in-person checks, video KYC, or document authentication that RBI rules require. When 96, or 700, or 8.5 lakh mule accounts are traced back through a handful of branches and intermediaries, the story is not really about the fraudsters at the far end of the chain. It is about the choke point where honest oversight should have stopped the account from ever existing.
Where the KYC Framework Is Breaking Down
The RBI's Know Your Customer Master Direction requires banks to establish customer identity, verify a genuine business relationship, and apply risk-based due diligence before allowing an account to operate. In practice, investigators have repeatedly found accounts opened through complicit or negligent bank staff, business correspondents, and third-party agents who bypass these checks entirely. Analysts note that mule accounts systematically exploit gaps in customer onboarding, KYC verification, transaction monitoring, and dormant-account surveillance, with criminals using forged or stolen identity documents and layering funds across multiple accounts to escape detection. Economically vulnerable individuals who are daily-wage workers, students, the unemployed are frequently paid a small commission to hand over their documents or existing accounts, often without understanding that they could face criminal liability for transactions they never authorised.
This is compounded by a financial-inclusion paradox that regulators themselves acknowledge: India has expanded banking access faster than it has expanded financial and digital literacy, leaving a population that is easy to recruit knowingly or unknowingly into mule networks. The result is a KYC regime that looks robust on paper but is only as strong as its weakest branch-level implementation, and weak implementation has proved trivially easy for organised networks to locate and exploit at scale.
The Regulatory and Institutional Response
RBI: From Static Compliance to Active Detection
The Reserve Bank of India has moved beyond periodic KYC audits toward technology-driven detection. It has directed banks to tighten onboarding controls, strengthen transaction monitoring, and report suspicious activity more proactively, and it has proposed additional safeguards, including limits on aggregate credits into accounts where a satisfactory business relationship has not yet been established. Its most significant intervention is MuleHunter.ai, an AI and machine-learning system built to flag suspected mule accounts from transaction-behaviour patterns rather than static KYC data alone; the platform is already operational across roughly two dozen banks and is being expanded. The RBI Innovation Hub has also begun working directly with the Indian Cyber Crime Coordination Centre (I4C) to share fraud-risk intelligence and coordinate detection in near real time.
FIU-IND and the PMLA Framework
The Prevention of Money Laundering Act, 2002 (PMLA) is the backbone of India's AML architecture. It mandates KYC verification, Customer Due Diligence, record maintenance, and timely reporting of suspicious transactions to the Financial Intelligence Unit–India (FIU-IND). Banks are required to file Suspicious Transaction Reports (STRs) and Cash Transaction Reports with FIU-IND, which in turn analyses financial intelligence and shares it with law enforcement and regulators. On paper, this creates a feedback loop between banks, the RBI, and enforcement agencies; in practice, the sheer volume of mule-linked transactions are hundreds of thousands of accounts flagged nationally has strained the capacity of this reporting chain to generate timely, actionable freezes before funds are withdrawn or converted to cryptocurrency.
The IT Act, CERT-In, and Cyber Enforcement
The Information Technology Act, 2000, together with provisions of the Bharatiya Nyaya Sanhita, provides the criminal-law basis for prosecuting mule account operators, aggregators, and the fraudsters who direct them. CERT-In's role sits slightly upstream of the banking layer: it issues advisories on phishing, fake payment gateways, and compromised digital infrastructure that fraud syndicates use to recruit mule account holders and move money. The Ministry of Home Affairs' I4C coordinates the National Cyber Crime Reporting Portal and the 1930 helpline, which allow victims to report fraud and trigger a limited window for freezing beneficiary accounts. I4C has also issued direct public alerts against illegal payment gateways built on mule accounts, warning citizens not to rent or sell their bank credentials to intermediaries.
The Coordination Gap
None of these institutions is short of legal authority. The gap is operational: banks, the RBI, FIU-IND, state police cyber cells, the CBI, and I4C each hold a piece of the picture, but no single agency has a real-time, end-to-end view of an account from opening to fraud to freeze. A mule account can be flagged by one bank's internal monitoring, reported through a completely different victim's complaint in another state, and investigated by a third jurisdiction's cyber police with each step introducing delay. The Indian Banks' Association has publicly pushed for the RBI to be given clearer power to directly freeze accounts flagged as mule accounts, rather than requiring each bank to act unilaterally or wait for a police request, precisely because this fragmentation lets fraudsters withdraw or launder funds within hours of a transaction.
Policy Recommendations
1. Mandatory video-KYC and biometric re-verification for all new accounts opened through business correspondents and third-party agents, with personal liability for verifying bank officials found complicit.
2. A statutory, RBI-backed mechanism allowing banks to freeze accounts flagged by MuleHunter.ai-type systems or FIU-IND intelligence within hours, rather than only after a formal police complaint.
3. A unified, interoperable case database linking the National Cyber Crime Reporting Portal, FIU-IND's STR system, and state cyber cells, so that an account flagged once is visible to every agency instantly.
4. Stronger due-diligence audits of banking correspondents and cooperative banks, which recur disproportionately in mule account cases relative to their share of total accounts.
5. Public financial-literacy campaigns targeted at the economically vulnerable groups most often recruited as unwitting mule account holders, paired with clear legal guidance distinguishing victims from willing participants.
Conclusion
The branch-level mule account cases surfacing across Delhi and other cities are not isolated policing stories; they are a live audit of India's AML and KYC architecture. The RBI, FIU-IND, CERT-In, and law enforcement agencies each have credible tools and legal mandates like MuleHunter.ai, PMLA reporting, IT Act prosecutions, and I4C's coordination portal chief among them but fraud syndicates continue to outpace the system by exploiting the seams between institutions rather than any single point of failure. Closing that gap requires less new law and more operational integration: faster account freezes, verified accountability at the point of account opening, and a shared, real-time picture of mule networks across every agency involved. Until banks, regulators, and investigators can act as one system rather than several disconnected ones, every dismantled racket will simply be replaced by the next.
References
- https://aninews.in/news/national/general-news/delhi-police-arrests-bank-deputy-manager-in-83776792-crore-mule-account-case-linked-to-159-cyber-fraud-complaints20260610130737/
- https://the420.in/delhi-bank-manager-mule-account-cyber-fraud-case/
- https://www.business-standard.com/finance/news/what-are-mule-accounts-cybercrime-banking-layer-india-fraud-rbi-126062400855_1.html
- https://www.business-standard.com/india-news/centre-freezes-450-000-mule-bank-accounts-used-in-cyber-fraud-schemes-124111200320_1.html
- https://www.medianama.com/2025/04/223-iba-rbi-cyber-fraud-measures-freeze-bank-accounts-cybercrime/
- https://www.deccanherald.com/amp/story/india%2Fcentre-warns-of-illegal-payment-gateways-and-mule-accounts-3252723
- https://www.deccanherald.com/india/over-85-lakh-mule-accounts-in-700-bank-branches-used-by-cyber-criminals-cbi-3604229
- https://website.rbi.org.in/en/web/rbi/-/notifications/master-direction-know-your-customer-kyc-direction-2016-updated-as-on-may-04-2023-lt-span-gt-11566
- https://www.indiacode.nic.in/bitstream/123456789/15402/1/moneylaunderingact2002.pdf
- https://www.indiacode.nic.in/bitstream/123456789/13116/1/it_act_2000_updated.pdf
- https://www.mha.gov.in/en/division_of_mha/cyber-and-information-security-cis-division/Details-about-Indian-Cybercrime-Coordination-Centre-I4C-Scheme