#FactCheck – Human Helicopter or AI Illusion? The Truth Behind the Viral Flying Man Video
Executive Summary:
A viral video circulating on social media shows a man attempting to fly using a helicopter like fan attached to his body, followed by a crash onto a parked car. The clip was widely shared with humorous captions, suggesting it depicts a real life incident. Given the unusual nature of the visuals, the video was subjected to technical verification using AI content detection tools. Analysis using the AI detection platform indicates that the video is AI generated, and not a genuine real world event.
Claim:
A viral video (archive link) claims to show a person attempting to fly using a self made helicopter fan mechanism, briefly lifting off before crashing onto a car in a public setting. The video shows a man attempting to fly by strapping a helicopter like rotating fan to himself, essentially trying to imitate a human helicopter using a DIY mechanism. For a brief moment, it appears as if the device might work, but the attempt quickly fails due to lack of control, engineering support, and safety measures. Within seconds, the man loses balance and crashes down, landing on top of a parked car. The scene highlights a mix of overconfidence, unregulated experimentation, and risk taking carried out in a public space, with bystanders watching rather than intervening. The clip is shared humorously with the caption “India is not for beginners”.
Fact Check:
To verify the authenticity of the video, it was analyzed using the Hive Moderation AI detection tool, a widely used platform for identifying synthetic and AI generated media. The tool flagged the video with a high probability of AI generation, indicating that the visuals are not captured from a real physical event. Additional indicators such as unrealistic motion physics, inconsistent human object interaction further support the conclusion that the clip was artificially generated or heavily manipulated using generative AI techniques. No credible news reports or independent eyewitness sources corroborate the occurrence of such an incident.
Conclusion:
The claim that the video shows an individual attempting and failing to fly using a helicopter like device is false. Technical analysis confirms that the video is AI generated, and it should be treated as synthetic or fictional content rather than a real life incident. This case highlights how AI generated videos, when shared without context, can mislead audiences and be mistaken for real events, reinforcing the need for verification tools and critical evaluation of viral content.
- Claim: A viral video claims to show a person attempting to fly using a self made helicopter fan mechanism, briefly lifting off before crashing onto a car in a public setting
- Claimed On: X (Formally Twitter)
- Fact Check: False and Misleading
Related Blogs
Executive Summary:
A video circulating on Social media has claimed that Iran has launched a missile strike destroying Ben Gurion Airport in Tel Aviv. With rising tensions in geopolitics, the video quickly became popular. However, our research has detailed inspections through digital verification tools and visual analysis showed that the video is AI-generated. No incident or damage ever occurred.
Claim:
A viral video circulating on social media platforms claims to show Tel Aviv’s Ben Gurion Airport destroyed following an Iranian missile strike. The video is being shared with captions suggesting it is the last recorded visuals from the attack, with some users asserting it as evidence of escalating conflict between Iran and Israel.
Fact Check:
After looking into the video that purported to show the destruction of Tel Aviv's Ben Gurion Airport in an Iranian missile strike, we researched the topic whether the claim is accurate or not. The video depicts a damaged airport terminal, with debris and fires, but a visual analysis determined that there were a number of suspicious characteristics: asymmetrical layout, artificial-looking smoke patterns, and the absence of activity or humans—those are all typical indications of AI generation. Our research traced the origins of the video to an Instagram post, with a date of May 27, 2025, made by what seems to be a user who frequently shares AI-generated images.
In order to verify our conclusions, we used Hive Moderation, an AI content detection tool, which produced a result of an 80% probability that the video is altered, and this level of probability strongly supports the idea that the footage is not real. Additionally, reports from popular organizations like India Today and Reuters supported these results. All findings resulting from our research established that the video is synthetic and unrelated to any event occurring at Ben Gurion Airport, and therefore debunked a false narrative propagated on social media.
To confirm, we also compared the visuals with a real aerial image of Tel Aviv’s Ben Gurion Airport available on aviation stock sites.
Fig: Google Maps image of Tel Aviv’s Ben Gurion Airport
The visuals from the viral video are not real locations or scenes of Aviv’s Ben Gurion Airport's true location and configuration therefore it is fake and misleading.
Conclusion:
After thorough research it is concluded that the viral video is fake and it is not an actual missile strike at Ben Gurion Airport. The video is made with AI, and posted by a content creator of synthetic content well before any conflict update. There is no official confirmation or credible news coverage to substantiate the claim, with a high probability of AI-detection, and it has been proven to be digitally manipulated. Therefore, the claim is untrue and misleading.
- Claim: A video shows Iran's missile strike destroying Tel Aviv’s Ben Gurion Airport.
- Claimed On: Social Media
- Fact Check: False and Misleading
Introduction
Recently, in April 2025, security researchers at Oligo Security exposed a substantial and wide-ranging threat impacting Apple's AirPlay protocol and its use via third-party Software Development Kit (SDK). According to the research, the recently discovered set of vulnerabilities titled "AirBorne" had the potential to enable remote code execution, escape permissions, and leak private data across many different Apple and third-party AirPlay-compatible devices. With well over 2.35 billion active Apple devices globally and tens of millions of third-party products that incorporate the AirPlay SDK, the scope of the problem is enormous. Those wireless-based vulnerabilities pose not only a technical threat but also increasingly an enterprise- and consumer-level security concern.
Understanding AirBorne: What’s at Stake?
AirBorne is the title given to a set of 23 vulnerabilities identified in the AirPlay communication protocol and its related SDK utilised by third-party vendors. Seventeen have been given official CVE designations. The most severe among them permit Remote Code Execution (RCE) with zero or limited user interaction. This provides hackers the ability to penetrate home networks, business environments, and even cars with CarPlay technology onboard.
Types of Vulnerabilities Identified
AirBorne vulnerabilities support a range of attack types, including:
- Zero-Click and One-Click RCE
- Access Control List (ACL) bypass
- User interaction bypass
- Local arbitrary file read
- Sensitive data disclosure
- Man-in-the-middle (MITM) attacks
- Denial of Service (DoS)
Each vulnerability can be used individually or chained together to escalate access and broaden the attack surface.
Remote Code Execution (RCE): Key Attack Scenarios
- MacOS – Zero-Click RCE (CVE-2025-24252 & CVE-2025-24206) These weaknesses enable attackers to run code on a MacOS system without any user action, as long as the AirPlay receiver is enabled and configured to accept connections from anyone on the same network. The threat of wormable malware propagating via corporate or public Wi-Fi networks is especially concerning.
- MacOS – One-Click RCE (CVE-2025-24271 & CVE-2025-24137) If AirPlay is set to "Current User," attackers can exploit these CVEs to deploy malicious code with one click by the user. This raises the level of threat in shared office or home networks.
- AirPlay SDK Devices – Zero-Click RCE (CVE-2025-24132) Third-party speakers and receivers through the AirPlay SDK are particularly susceptible, where exploitation requires no user intervention. Upon compromise, the attackers have the potential to play unauthorised media, turn microphones on, or monitor intimate spaces.
- CarPlay Devices – RCE Over Wi-Fi, Bluetooth, or USB CVE-2025-24132 also affects CarPlay-enabled systems. Under certain circumstances, the perpetrators around can take advantage of predictable Wi-Fi credentials, intercept Bluetooth PINs, or utilise USB connections to take over dashboard features, which may distract drivers or listen in on in-car conversations.
Other Exploits Beyond RCE
AirBorne also opens the door for:
- Sensitive Information Disclosure: Exposing private logs or user metadata over local networks (CVE-2025-24270).
- Local Arbitrary File Access: Letting attackers read restricted files on a device (CVE-2025-24270 group).
- DoS Attacks: Exploiting NULL pointer dereferences or misformatted data to crash processes like the AirPlay receiver or WindowServer, forcing user logouts or system instability (CVE-2025-24129, CVE-2025-24177, etc.).
How the Attack Works: A Technical Breakdown
AirPlay sends on port 7000 via HTTP and RTSP, typically encoded in Apple's own plist (property list) form. Exploits result from incorrect treatment of these plists, especially when skipping type checking or assuming invalid data will be valid. For instance, CVE-2025-24129 illustrates how a broken plist can produce type confusion to crash or execute code based on configuration.
A hacker must be within the same Wi-Fi network as the targeted device. This connection might be through a hacked laptop, public wireless with shared access, or an insecure corporate connection. Once in proximity, the hacker has the ability to use AirBorne bugs to hijack AirPlay-enabled devices. There, bad code can be released to spy, gain long-term network access, or spread control to other devices on the network, perhaps creating a botnet or stealing critical data.
The Espionage Angle
Most third-party AirPlay-compatible devices, including smart speakers, contain built-in microphones. In theory, that leaves the door open for such devices to become eavesdropping tools. While Oligo did not show a functional exploit for the purposes of espionage, the risk suggests the gravity of the situation.
The CarPlay Risk Factor
Besides smart home appliances, vulnerabilities in AirBorne have also been found for Apple CarPlay by Oligo. Those vulnerabilities, when exploited, may enable attackers to take over an automobile's entertainment system. Fortunately, the attacks would need pairing directly through USB or Bluetooth and are much less practical. Even so, it illustrates how networks of connected components remain at risk in various situations, ranging from residences to automobiles.
How to Protect Yourself and Your Organisation
- Immediate Actions:
- Update Devices: Ensure all Apple devices and third-party gadgets are upgraded to the latest software version.
- Disable AirPlay Receiver: If AirPlay is not in use, disable it in system settings.
- Restrict AirPlay Access: Use firewalls to block port 7000 from untrusted IPs.
- Set AirPlay to “Current User” to limit network-based attack.
- Organisational Recommendations:
- Communicate the patch urgency to employees and stakeholders.
- Inventory all AirPlay-enabled hardware, including in meeting rooms and vehicles.
- Isolate vulnerable devices on segmented networks until updated.
Conclusion
The AirBorne vulnerabilities illustrate that even mature systems such as Apple's are not immune from foundational security weaknesses. The extensive deployment of AirPlay across devices, industries, and ecosystems makes these vulnerabilities a systemic threat. Oligo's discovery has served to catalyse immediate response from Apple, but since third-party devices remain vulnerable, responsibility falls to users and organisations to install patches, implement robust configurations, and compartmentalise possible attack surfaces. Effective proactive cybersecurity hygiene, network segmentation, and timely patches are the strongest defences to avoid these kinds of wormable, scalable attacks from becoming large-scale breaches.
References
- https://www.oligo.security/blog/airborne
- https://www.wired.com/story/airborne-airplay-flaws/
- https://thehackernews.com/2025/05/wormable-airplay-flaws-enable-zero.html
- https://www.securityweek.com/airplay-vulnerabilities-expose-apple-devices-to-zero-click-takeover/
- https://www.pcmag.com/news/airborne-flaw-exposes-airplay-devices-to-hacking-how-to-protect-yourself
- https://cyberguy.com/security/hackers-breaking-into-apple-devices-through-airplay/
Executive Summary:
Our research has determined that a widely circulated social media image purportedly showing astronaut Sunita Williams with U.S. President Donald Trump and entrepreneur Elon Musk following her return from space is AI-generated. There is no verifiable evidence to suggest that such a meeting took place or was officially announced. The image exhibits clear indicators of AI generation, including inconsistencies in facial features and unnatural detailing.
Claim:
It was claimed on social media that after returning to Earth from space, astronaut Sunita Williams met with U.S. President Donald Trump and Elon Musk, as shown in a circulated picture.
Fact Check:
Following a comprehensive analysis using Hive Moderation, the image has been verified as fake and AI-generated. Distinct signs of AI manipulation include unnatural skin texture, inconsistent lighting, and distorted facial features. Furthermore, no credible news sources or official reports substantiate or confirm such a meeting. The image is likely a digitally altered post designed to mislead viewers.
While reviewing the accounts that shared the image, we found that former Indian cricketer Manoj Tiwary had also posted the same image and a video of a space capsule returning, congratulating Sunita Williams on her homecoming. Notably, the image featured a Grok watermark in the bottom right corner, confirming that it was AI-generated.
Additionally, we discovered a post from Grok on X (formerly known as Twitter) featuring the watermark, stating that the image was likely AI-generated.
Conclusion:
As per our research on the viral image of Sunita Williams with Donald Trump and Elon Musk is AI-generated. Indicators such as unnatural facial features, lighting inconsistencies, and a Grok watermark suggest digital manipulation. No credible sources validate the meeting, and a post from Grok on X further supports this finding. This case underscores the need for careful verification before sharing online content to prevent the spread of misinformation.
- Claim: Sunita Williams met Donald Trump and Elon Musk after her space mission.
- Claimed On: Social Media
- Fact Check: False and Misleading
