#FactCheck - Viral Video Claiming Iran’s Attack on US Airbase Debunked as 9/11 Footage
Executive Summary
A video showing thick smoke rising from a building and people running in panic is being shared on social media. The video is being circulated with the claim that it shows Iran launching a missile attack on the United States.CyberPeace’s research found the claim to be misleading. Our probe revealed that the video is not related to any recent incident. The viral clip is actually from the September 11, 2001 terrorist attacks on the World Trade Center in the United States and is being falsely shared as footage of an alleged Iranian missile strike on the US.
Claim:
An Instagram user shared the video claiming, “Iran has attacked a US airbase in Qatar. Iran has fired six ballistic missiles at the Al Udeid Airbase in Qatar. Al Udeid Airbase is the largest US military base in West Asia.”
Links to the post and its archived version are provided below.
Fact Check:
To verify the claim, we extracted key frames from the viral video and ran a reverse image search using Google Lens. During the search, we found visuals matching the viral clip in a report published by Wion on September 11, 2021. The report, titled “In pics | A look back at the scenes from the 9/11 attacks,” included an image that closely resembled the visuals seen in the viral video. The caption of the image stated that it was a file photo from September 11, 2001, showing pedestrians running as one of the World Trade Center towers collapsed in New York City.
Further research led us to the same footage on the YouTube channel CBS 8 San Diego. At the 01:11 timestamp of the video, visuals matching the viral clip can be clearly seen.
We also found an Al Jazeera report dated June 23, 2025, which confirmed that Iran had attacked US forces stationed at the Al Udeid airbase in Qatar in retaliation for US strikes on Iran’s uclear facilities. However, the visuals used in the viral video do not correspond to this incident.
Conclusion
The viral video does not show a recent Iranian attack on a US airbase in Qatar. The clip actually dates back to the September 11, 2001 terrorist attacks on the World Trade Center in the United States. Old 9/11 footage has been falsely shared with a misleading claim linking it to Iran’s alleged missile strike on the US.
Related Blogs
Executive Summary
A video circulating widely on social media claims to show a pilot of the Indian Air Force (IAF) crying and expressing fear about flying fighter jets, allegedly citing poor maintenance and frequent crashes. The clip is being linked to the crash of an IAF Sukhoi-30 fighter jet in Assam on March 5, in which two pilots lost their lives. In the viral video, a man dressed like a pilot is seen speaking emotionally, saying that flying fighter jets has become frightening due to lack of maintenance and repeated accidents. Several users are sharing the clip claiming that the man in the video is an IAF pilot revealing the reality behind aircraft crashes. However, research by the CyberPeace found the claim to be false. The video does not depict a real pilot or an actual incident. Instead, it appears to be an AI-generated clip created and circulated with the intent to spread misinformation.
Claim:
An Instagram user, ‘samacharsaar0’, shared the viral video on March 10, 2026, with the English caption: “2300 aircraft crashes, 1300 pilots dead: A major challenge before the IAF.”
- Source: :https://www.instagram.com/reel/DVqa4lNiYJQ
- Archived link::https://perma.cc/EUZ8-DHE3
Fact Check:
The claim was also debunked by PIB Fact Check. While verifying the viral video, PIB clarified that the clip is artificially generated and not related to any real IAF personnel.
To further verify the authenticity of the video, we analyzed it using AI detection tools. The tool Hive Moderation indicated a 99.9% probability that the video was generated using artificial intelligence.
We also examined the clip using another AI detection platform, Undetectable. The analysis suggested an 82% likelihood that the video was created with AI tools. The tool also indicated the possibility that the footage may have been generated using the Sora AI video generation tool.
Conclusion
Our research concludes that the viral video of a crying “pilot” is not authentic. The clip has been created using artificial intelligence and is being misleadingly shared as a real Indian Air Force pilot speaking about aircraft crashes. The government has also denied the claim associated with the video.
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
Executive Summary:
A viral image circulating on social media claims it to be a natural optical illusion from Epirus, Greece. However, upon fact-checking, it was found that the image is an AI-generated artwork created by Iranian artist Hamidreza Edalatnia using the Stable Diffusion AI tool. CyberPeace Research Team found it through reverse image search and analysis with an AI content detection tool named HIVE Detection, which indicated a 100% likelihood of AI generation. The claim of the image being a natural phenomenon from Epirus, Greece, is false, as no evidence of such optical illusions in the region was found.
Claims:
The viral image circulating on social media depicts a natural optical illusion from Epirus, Greece. Users share on X (formerly known as Twitter), YouTube Video, and Facebook. It’s spreading very fast across Social Media.
Similar Posts:
Fact Check:
Upon receiving the Posts, the CyberPeace Research Team first checked for any Synthetic Media detection, and the Hive AI Detection tool found it to be 100% AI generated, which is proof that the Image is AI Generated. Then, we checked for the source of the image and did a reverse image search for it. We landed on similar Posts from where an Instagram account is linked, and the account of similar visuals was made by the creator named hamidreza.edalatnia. The account we landed posted a photo of similar types of visuals.
We searched for the viral image in his account, and it was confirmed that the viral image was created by this person.
The Photo was posted on 10th December, 2023 and he mentioned using AI Stable Diffusion the image was generated . Hence, the Claim made in the Viral image of the optical illusion from Epirus, Greece is Misleading.
Conclusion:
The image claiming to show a natural optical illusion in Epirus, Greece, is not genuine, and it's False. It is an artificial artwork created by Hamidreza Edalatnia, an artist from Iran, using the artificial intelligence tool Stable Diffusion. Hence the claim is false.
