#FactCheck -AI-Generated Video Falsely Shared as Leopard Dragging Passenger From Moving Train
Executive Summary
A video is being widely shared on social media claiming that a leopard dragged away a passenger from a moving train. Several users are circulating the clip as a real incident. However, CyberPeace Research Wing research found the claim to be false. Our research revealed that the viral video is not real and was generated using Artificial Intelligence (AI).
Claim
An X user (formerly Twitter) shared the viral clip with the caption:“A leopard snatched a man from a moving train.”The link, archived version, and screenshot of the post are provided below.
Fact Check
On closely examining the video, several visual inconsistencies were noticed. The leopard’s body appears distorted at multiple points in the clip. In some frames, parts of the animal’s body seem to merge into the background, while in others, sections appear incomplete or disappear entirely — something not typically seen in authentic footage. In the final part of the video, where the leopard is allegedly shown attacking a passenger, the person’s hands, limbs, and body also appear blurred and distorted. Additionally, unusual and selective blurring can be observed throughout the video, indicating possible editing or AI manipulation.
To further verify the clip, we scanned the viral video using the AI detection tool Sightengine. According to the results, the video showed an 86 percent probability of being AI-generated.
As part of the research , we also analysed the clip using another AI detection platform, UndetectableTM AI, which likewise indicated that the viral video was AI-generated.
Conclusion
Our research found that the viral video claiming to show a leopard dragging away a passenger from a moving train is fake. The clip is AI-generated and does not depict a real incident.
Related Blogs
Executive Summary:
BrazenBamboo’s DEEPDATA malware represents a new wave of advanced cyber espionage tools, exploiting a zero-day vulnerability in Fortinet FortiClient to extract VPN credentials and sensitive data through fileless malware techniques and secure C2 communications. With its modular design, DEEPDATA targets browsers, messaging apps, and password stores, while leveraging reflective DLL injection and encrypted DNS to evade detection. Cross-platform compatibility with tools like DEEPPOST and LightSpy highlights a coordinated development effort, enhancing its espionage capabilities. To mitigate such threats, organizations must enforce network segmentation, deploy advanced monitoring tools, patch vulnerabilities promptly, and implement robust endpoint protection. Vendors are urged to adopt security-by-design practices and incentivize vulnerability reporting, as vigilance and proactive planning are critical to combating this sophisticated threat landscape.
Introduction
The increased use of zero-day vulnerabilities by more complex threat actors reinforces the importance of more developed countermeasures. One of the threat actors identified is BrazenBamboo uses a zero-day vulnerability in Fortinet FortiClient for Windows through the DEEPDATA advanced malware framework. This research explores technical details about DEEPDATA, the tricks used in its operations, and its other effects.
Technical Findings
1. Vulnerability Exploitation Mechanism
The vulnerability in Fortinet’s FortiClient lies in its failure to securely handle sensitive information in memory. DEEPDATA capitalises on this flaw via a specialised plugin, which:
- Accesses the VPN client’s process memory.
- Extracts unencrypted VPN credentials from memory, bypassing typical security protections.
- Transfers credentials to a remote C2 server via encrypted communication channels.
2. Modular Architecture
DEEPDATA exhibits a highly modular design, with its core components comprising:
- Loader Module (data.dll): Decrypts and executes other payloads.
- Orchestrator Module (frame.dll): Manages the execution of multiple plugins.
- FortiClient Plugin: Specifically designed to target Fortinet’s VPN client.
Each plugin operates independently, allowing flexibility in attack strategies depending on the target system.
3. Command-and-Control (C2) Communication
DEEPDATA establishes secure channels to its C2 infrastructure using WebSocket and HTTPS protocols, enabling stealthy exfiltration of harvested data. Technical analysis of network traffic revealed:
- Dynamic IP switching for C2 servers to evade detection.
- Use of Domain Fronting, hiding C2 communication within legitimate HTTPS traffic.
- Time-based communication intervals to minimise anomalies in network behavior.
4. Advanced Credential Harvesting Techniques
Beyond VPN credentials, DEEPDATA is capable of:
- Dumping password stores from popular browsers, such as Chrome, Firefox, and Edge.
- Extracting application-level credentials from messaging apps like WhatsApp, Telegram, and Skype.
- Intercepting credentials stored in local databases used by apps like KeePass and Microsoft Outlook.
5. Persistence Mechanisms
To maintain long-term access, DEEPDATA employs sophisticated persistence techniques:
- Registry-based persistence: Modifies Windows registry keys to reload itself upon system reboot.
- DLL Hijacking: Substitutes legitimate DLLs with malicious ones to execute during normal application operations.
- Scheduled Tasks and Services: Configures scheduled tasks to periodically execute the malware, ensuring continuous operation even if detected and partially removed.
Additional Tools in BrazenBamboo’s Arsenal
1. DEEPPOST
A complementary tool used for data exfiltration, DEEPPOST facilitates the transfer of sensitive files, including system logs, captured credentials, and recorded user activities, to remote endpoints.
2. LightSpy Variants
- The Windows variant includes a lightweight installer that downloads orchestrators and plugins, expanding espionage capabilities across platforms.
- Shellcode-based execution ensures that LightSpy’s payload operates entirely in memory, minimising artifacts on the disk.
3. Cross-Platform Overlaps
BrazenBamboo’s shared codebase across DEEPDATA, DEEPPOST, and LightSpy points to a centralised development effort, possibly linked to a Digital Quartermaster framework. This shared ecosystem enhances their ability to operate efficiently across macOS, iOS, and Windows systems.
Notable Attack Techniques
1. Memory Injection and Data Extraction
Using Reflective DLL Injection, DEEPDATA injects itself into legitimate processes, avoiding detection by traditional antivirus solutions.
- Memory Scraping: Captures credentials and sensitive information in real-time.
- Volatile Data Extraction: Extracts transient data that only exists in memory during specific application states.
2. Fileless Malware Techniques
DEEPDATA leverages fileless infection methods, where its payload operates exclusively in memory, leaving minimal traces on the system. This complicates post-incident forensic investigations.
3. Network Layer Evasion
By utilising encrypted DNS queries and certificate pinning, DEEPDATA ensures that network-level defenses like intrusion detection systems (IDS) and firewalls are ineffective in blocking its communications.
Recommendations
1. For Organisations
- Apply Network Segmentation: Isolate VPN servers from critical assets.
- Enhance Monitoring Tools: Deploy behavioral analysis tools that detect anomalous processes and memory scraping activities.
- Regularly Update and Patch Software: Although Fortinet has yet to patch this vulnerability, organisations must remain vigilant and apply fixes as soon as they are released.
2. For Security Teams
- Harden Endpoint Protections: Implement tools like Memory Integrity Protection to prevent unauthorised memory access.
- Use Network Sandboxing: Monitor and analyse outgoing network traffic for unusual behaviors.
- Threat Hunting: Proactively search for indicators of compromise (IOCs) such as unauthorised DLLs (data.dll, frame.dll) or C2 communications over non-standard intervals.
3. For Vendors
- Implement Security by Design: Adopt advanced memory protection mechanisms to prevent credential leakage.
- Bug Bounty Programs: Encourage researchers to report vulnerabilities, accelerating patch development.
Conclusion
DEEPDATA is a form of cyber espionage and represents the next generation of tools that are more advanced and tunned for stealth, modularity and persistence. While Brazen Bamboo is in the process of fine-tuning its strategies, the organisations and vendors have to be more careful and be ready to respond to these tricks. The continuous updating, the ability to detect the threats and a proper plan on how to deal with incidents are crucial in combating the attacks.
References:
Introduction
In recent years, the online gaming sector has seen tremendous growth and is one of the fastest-growing components of the creative economy, contributing significantly to innovation, employment generation and export earnings. India possesses a large pool of skilled young professionals, strong technological capabilities and a rapidly growing domestic market, which together provide an opportunity for the country to assume a leadership role in the global value chain of online gaming. With this, the online gaming industry has also faced an environment of exploitation, abuse, with notable cases of fraud, money laundering, and other emerging cybercrimes. In order to protect the interests of players, ensure fair play and competition, safe and secure online gaming environment, the need for introducing and establishing dedicated gaming regulation was a need of the hour.
On 20 August 2025, the Union government introduced a new bill, ‘Promotion and Regulation of Online Gaming Bill, 2025’ in Lok Sabha that seeks to prohibit online money gaming, including advertisements and financial transactions related to such platforms. From the introduction, the said bill was passed at 5 PM on the same date. Further, the upper house of parliament (Rajya Sabha) passed the bill on 21st August 2025. The bill can be seen as a progressive step towards building safer online gaming spaces for everyone, especially for our youth and combating the emerging cybercrime threats present in the online gaming landscape.
Key Highlights of the Bill
The Bill extends to the whole of India. It also applies to any online money gaming service offered within India or operated from outside the country but accessible in India.
- Definition of E-sports:
Section 2(1)(c) of the Bill defines e-sports as:-
(i) is played as part of multi-sports events;
(ii) involves organised competitive events between individuals or teams, conducted in multiplayer formats governed by predefined rules;
(iii) is duly recognised under the National Sports Governance Act, 2025, and registered with the Authority or agency under section 3;
(iv) has outcome determined solely by factors such as physical dexterity, mental agility, strategic thinking or other similar skills of users as players;
(v) may include payment of registration or participation fees solely for the purpose of entering the competition or covering administrative costs and may include performance-based prize money by the player; and
(vi)shall not involve the placing of bets, wagers or any other stakes by any person, whether or not such person is a participant, including any winning out of such bets, wagers or any other stakes;
- Prohibition of Online Money Gaming and Advertisement thereof
The Bill prohibits the offering of online money games and online money gaming services. It also bans all forms of advertisements or promotions connected to online money games. This includes endorsements by individuals or entities. - Financial Transactions
Banks, financial institutions, and other intermediaries are barred from facilitating transactions related to online money gaming services. - Criminal Liability
Violation of the provisions on online money gaming can result in imprisonment for up to three years, or a fine of up to ₹1 crore, or both. Repeat offenders face stricter punishment with higher fines and longer jail terms. - Cognizable and Non-Bailable Offences
Offences relating to offering online money gaming services and facilitating financial transactions for such games are categorised as cognizable and non-bailable. This gives law enforcement agencies greater power to act without requiring prior approval.
In conversation with CyberPeace ~
Shailendra Vikram Singh, Former Deputy Secretary (Cyber & Information Security), Ministry of Home Affairs, GOI . He highlighted that
"The passage of the Promotion and Regulation of Online Gaming Bill, 2025 in the Lok Sabha highlights the government’s growing priority on national security, public safety, and health in digital regulation. Unfortunately, the real money gaming industry, despite its growth and promise, did not take proactive steps to address these concerns. The absence of safeguards and engagement left the government with no choice but to adopt a blanket ban."Having worked on this issue from both the government and industry side, the clear lesson is that in sensitive digital sectors, early regulatory alignment and constructive dialogue are not optional but essential. Going forward, collaboration is the only way to achieve a balance between innovation and responsibility.”
CyberPeace Outlook
The Promotion and Regulation of Online Gaming Bill, 2025, marks a decisive policy shift by simultaneously fostering the growth of e-sports, educational and social gaming, and imposing an absolute prohibition on online money games. By recognising e-sports as legitimate, skill-based competitive sports under the National Sports Governance Act, 2025, and establishing a central Authority for oversight, registration, and regulation, the Bill creates an institutional framework for safe and responsible development of the sector. The Bill completely bans real money games (RMGs), regardless of whether they are skill-based or chance-based or both, hence it poses significant questions on RMG companies' legal standing, upon which the gaming industry has raised its conundrum. Further, it addresses urgent threats such as cybercrime, gaming addiction, online betting, money laundering, and the misuse of gaming platforms for illicit activities. The move reflects a balanced approach, encouraging innovation and digital skill-building, while safeguarding public order, consumer interests, and financial integrity.
References
- https://prsindia.org/files/bills_acts/bills_parliament/2025/Bill_Text-Online_Gaming_Bill_2025.pdf
- https://prsindia.org/billtrack/the-promotion-and-regulation-of-online-gaming-bill-2025
- https://www.hindustantimes.com/india-news/rajya-sabha-clears-online-gaming-bill-a-day-after-lok-sabha-approval-101755766847840.html
Executive Summary:
The picture of a boy making sand art of Indian Cricketer Virat Kohli spreading in social media, claims to be false. The picture which was portrayed, revealed not to be a real sand art. The analyses using AI technology like 'Hive' and ‘Content at scale AI detection’ confirms that the images are entirely generated by artificial intelligence. The netizens are sharing these pictures in social media without knowing that it is computer generated by deep fake techniques.
Claims:
The collage of beautiful pictures displays a young boy creating sand art of Indian Cricketer Virat Kohli.
Fact Check:
When we checked on the posts, we found some anomalies in each photo. Those anomalies are common in AI-generated images.
The anomalies such as the abnormal shape of the child’s feet, blended logo with sand color in the second image, and the wrong spelling ‘spoot’ instead of ‘sport’n were seen in the picture. The cricket bat is straight which in the case of sand made portrait it’s odd. In the left hand of the child, there’s a tattoo imprinted while in other photos the child's left hand has no tattoo. Additionally, the face of the boy in the second image does not match the face in other images. These made us more suspicious of the images being a synthetic media.
We then checked on an AI-generated image detection tool named, ‘Hive’. Hive was found to be 99.99% AI-generated. We then checked from another detection tool named, “Content at scale”
Hence, we conclude that the viral collage of images is AI-generated but not sand art of any child. The Claim made is false and misleading.
Conclusion:
In conclusion, the claim that the pictures showing a sand art image of Indian cricket star Virat Kohli made by a child is false. Using an AI technology detection tool and analyzing the photos, it appears that they were probably created by an AI image-generated tool rather than by a real sand artist. Therefore, the images do not accurately represent the alleged claim and creator.
Claim: A young boy has created sand art of Indian Cricketer Virat Kohli
Claimed on: X, Facebook, Instagram
Fact Check: Fake & Misleading
