#FactCheck- Viral Zipline Accident Video from Karnaprayag is AI-Generated, Claim is False

Introduction

AI-generated fake videos are proliferating on the Internet indeed becoming more common by the day. There is a use of sophisticated AI algorithms that help manipulate or generate multimedia content such as videos, audio, and images. As a result, it has become increasingly difficult to differentiate between genuine, altered, or fake content, and these AI-manipulated videos look realistic. A recent study has shown that 98% of deepfake-generated videos have adult content featuring young girls, women, and children, with India ranking 6th among the nations that suffer from misuse of deepfake technology. This practice has dangerous consequences and could harm an individual's reputation, and criminals could use this technology to create a false narrative about a candidate or a political party during elections.

The working of deepfake videos is based on algorithms that refine the fake content, and the generators are built and trained in such a way as to get the desired output. The process is repeated several times, allowing the generator to improve the content until it seems realistic, making it more flawless. Deepfake videos are created by specific approaches some of them are: -

• Lip syncing: This is the most common technique used in deepfake. Here, the voice recordings of the video, make it appear as to what was originally said by the person appearing in the video.
• Audio deepfake:  For Audio-generated deepfake, a generative adversarial network (GAN) is used to colon a person’s voice, based on the vocal patterns and refine it till the desired output is generated.

• Deepfake has become so serious that the technology could be used by bad actors or by cyber-terrorist squads to set their Geo-political agendas.  Looking at the present situation in the past few the number of cases has just doubled, targeting children, women and popular faces. 

• Greater Risk: in the last few years the cases of deep fake have risen. by the end of the year 2022, the number of cases has risen to 96% against women and children according to a survey.
• Every 60 seconds, a deepfake pornographic video is created, now quicker and more affordable than ever, it takes less than 25 minutes and costs using just one clean face image.  
• The connection to deepfakes is that people can become targets of "revenge porn" without the publisher having sexually explicit photographs or films of the victim. They may be made using any number of random pictures or images collected from the internet to obtain the same result. This means that almost everyone who has taken a selfie or shared a photograph of oneself online faces the possibility of a deepfake being constructed in their image.

Deepfake-related security concerns

As deepfakes proliferate, more people are realising that they can be used not only to create non-consensual porn but also as part of disinformation and fake news campaigns with the potential to sway elections and rekindle frozen or low-intensity conflicts.

Deepfakes have three security implications: at the international level, strategic deepfakes have the potential to destroy precarious peace; at the national level, deepfakes may be used to unduly influence elections, and the political process, or discredit opposition, which is a national security concern, and at the personal level, the scope for using Women suffer disproportionately from exposure to sexually explicit content as compared to males, and they are more frequently threatened. 

Policy Consideration

Looking at the present situation where the cases of deepfake are on the rise against women and children, the policymakers need to be aware that deepfakes are utilized for a variety of valid objectives, including artistic and satirical works, which policymakers should be aware of. Therefore, simply banning deepfakes is not a way consistent with fundamental liberties. One conceivable legislative option is to require a content warning or disclaimer. Deepfake is an advanced technology and misuse of deepfake technology is a crime.

What are the existing rules to combat deepfakes?

It's worth noting that both the IT Act of 2000 and the IT Rules of 2021 require social media intermediaries to remove deep-fake videos or images as soon as feasible. Failure to follow these guidelines can result in up to three years in jail and a Rs 1 lakh fine. Rule 3(1)(b)(vii) requires social media intermediaries to guarantee that its users do not host content that impersonates another person, and Rule 3(2)(b) requires such content to be withdrawn within 24 hours of receiving a complaint. Furthermore, the government has stipulated that any post must be removed within 36 hours of being published online. Recently government has also issued an advisory to social media intermediaries to identify misinformation and deepfakes.

Conclusion

It is important to foster ethical and responsible consumption of technology. This can only be achieved by creating standards for both the creators and users, educating individuals about content limits, and providing information. Internet-based platforms should also devise techniques to deter the uploading of inappropriate information. We can reduce the negative and misleading impacts of deepfakes by collaborating and ensuring technology can be used in a better manner.  

References

• https://timesofindia.indiatimes.com/life-style/parenting/moments/how-social-media-scandals-like-deepfake-impact-minors-and-students-mental-health/articleshow/105168380.cms?from=mdr
• https://www.aa.com.tr/en/science-technology/deepfake-technology-putting-children-at-risk-say-experts/2980880
• https://wiisglobal.org/deepfakes-as-a-security-issue-why-gender-matters/

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

1. 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/
2. https://the420.in/delhi-bank-manager-mule-account-cyber-fraud-case/
3. https://www.business-standard.com/finance/news/what-are-mule-accounts-cybercrime-banking-layer-india-fraud-rbi-126062400855_1.html
4. https://www.business-standard.com/india-news/centre-freezes-450-000-mule-bank-accounts-used-in-cyber-fraud-schemes-124111200320_1.html
5. https://www.medianama.com/2025/04/223-iba-rbi-cyber-fraud-measures-freeze-bank-accounts-cybercrime/
6. https://www.deccanherald.com/amp/story/india%2Fcentre-warns-of-illegal-payment-gateways-and-mule-accounts-3252723
7. https://www.deccanherald.com/india/over-85-lakh-mule-accounts-in-700-bank-branches-used-by-cyber-criminals-cbi-3604229
8. 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
9. https://www.indiacode.nic.in/bitstream/123456789/15402/1/moneylaunderingact2002.pdf
10. https://www.indiacode.nic.in/bitstream/123456789/13116/1/it_act_2000_updated.pdf
11. https://www.mha.gov.in/en/division_of_mha/cyber-and-information-security-cis-division/Details-about-Indian-Cybercrime-Coordination-Centre-I4C-Scheme

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Executive Summary

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A video is being widely shared on social media showing what appears to be a missile attack over a densely populated city at night. The footage, seemingly recorded from inside a passenger aircraft, shows multiple explosions and missiles lighting up the sky.The video is being circulated with the claim that a Kuwaiti pilot filmed Iranian missiles being launched towards a US military base in the Middle East from the cockpit of an aircraft.

CyberPeace Research Wing’s research found the viral claim to be false. Our research confirmed that while Iran has launched attacks on US military installations in the Middle East, the viral footage is not related to those incidents. The video was found to be AI-generated and is being shared with a false and misleading narrative.

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Claim

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An Instagram user shared the viral video on July 11, 2026, claiming that it was recorded by a Kuwaiti pilot from an aircraft and shows Iranian missiles targeting a US military base in the Middle East.

Post Link: https://www.instagram.com/reel/DanymEDIdp2/?utm_source=ig_web_button_share_sheet

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Fact Check

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To verify the claim, we conducted a keyword-based search on Google. During the research, we did not find any credible news report or authentic source linking the viral video to the alleged Iranian missile attack. We did find a Navbharat Times report covering Iran's strikes on US military bases in the Middle East. However, the report did not contain the viral footage or any reference suggesting that such a video had been recorded by a Kuwaiti pilot. https://navbharattimes.indiatimes.com/video/news/america-iran-war-retaliation-for-us-attacks-begins-iran-strikes-at-trumps-allies-and-its-neighbour/videoshow/132370583.cms

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In the next stage of the research, we analysed the viral video using the AI detection tool Hive Moderation. The tool indicated that the video had a 74.8% probability of being AI-generated.

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For additional verification, we also analysed the footage using another AI detection tool, DetectVideo AI. Its analysis showed a 61% probability that the video was AI-generated.

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Conclusion

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Our research found that the viral claim is false. Although Iran has carried out missile strikes on US military facilities in the Middle East, the viral video is not authentic and has no connection to those attacks. The footage was found to be AI-generated and is being circulated on social media with a misleading claim that it was recorded by a Kuwaiti pilot from an aircraft.

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