#FactCheck: Chhatarpur Protest Video Falsely Shared as Indian Army Atrocities in Manipur

What are Deepfakes? 

A deepfake is essentially a video of a person in which their face or body has been digitally altered so that they appear to be someone else, typically used maliciously or to spread false information. Deepfake technology is a method for manipulating videos, images, and audio utilising powerful computers and deep learning. It is used to generate fake news and commit financial fraud, among other wrongdoings. It overlays a digital composite over an already-existing video, picture, or audio; cybercriminals use Artificial Intelligence technology. The term deepfake was coined first time in 2017 by an anonymous Reddit user, who called himself deepfake. 

Deepfakes works on a combination of AI and ML, which makes the technology hard to detect by Web 2.0 applications, and it is almost impossible for a layman to see if an image or video is fake or has been created using deepfakes. In recent times, we have seen a wave of AI-driven tools which have impacted all industries and professions across the globe. Deepfakes are often created to spread misinformation. There lies a key difference between image morphing and deepfakes. Image morphing is primarily used for evading facial recognition, but deepfakes are created to spread misinformation and propaganda. 

Issues Pertaining to Deepfakes in India 

Deepfakes are a threat to any nation as the impact can be divesting in terms of monetary losses, social and cultural unrest, and actions against the sovereignty of India by anti-national elements. Deepfake detection is difficult but not impossible. The following threats/issues are seen to be originating out of deep fakes: 

• Misinformation: One of the biggest issues of Deepfake is misinformation, the same was seen during the Russia-Ukraine conflict, where in a deepfake of Ukraine’s president, Mr Zelensky, surfaced on the internet and caused mass confusion and propaganda-based misappropriation among the Ukrainians. 
• Instigation against the Union of India: Deepfake poses a massive threat to the integrity of the Union of India, as this is one of the easiest ways for anti-national elements to propagate violence or instigate people against the nation and its interests. As India grows, so do the possibilities of anti-national attacks against the nation. 
• Cyberbullying/ Harassment: Deepfakes can be used by bad actors to harass and bully people online in order to extort money from them. 
• Exposure to Illicit Content: Deepfakes can be easily used to create illicit content, and oftentimes, it is seen that it is being circulated on online gaming platforms where children engage the most. 
• Threat to Digital Privacy: Deepfakes are created by using existing videos. Hence, bad actors often use photos and videos from Social media accounts to create deepfakes, this directly poses a threat to the digital privacy of a netizen.  
• Lack of Grievance Redressal Mechanism: In the contemporary world, the majority of nations lack a concrete policy to address the aspects of deepfake. Hence, it is of paramount importance to establish legal and industry-based grievance redressal mechanisms for the victims. 
• Lack of Digital Literacy: Despite of high internet and technology penetration rates in India, digital literacy lags behind, this is a massive concern for the Indian netizens as it takes them far from understanding the tech, which results in the under-reporting of crimes. Large-scale awareness and sensitisation campaigns need to be undertaken in India to address misinformation and the influence of deepfakes. 

How to spot deepfakes? 

Deepfakes look like the original video at first look, but as we progress into the digital world, it is pertinent to establish identifying deepfakes in our digital routine and netiquettes in order to stay protected in the future and to address this issue before it is too late. The following aspects can be kept in mind while differentiating between a real video and a deepfake

• Look for facial expressions and irregularities: Whenever differentiating between an original video and deepfake, always look for changes in facial expressions and irregularities, it can be seen that the facial expressions, such as eye movement and a temporary twitch on the face, are all signs of a video being a deepfake. 
• Listen to the audio: The audio in deepfake also has variations as it is imposed on an existing video, so keep a check on the sound effects coming from a video in congruence with the actions or gestures in the video. 
• Pay attention to the background: The most easiest way to spot a deepfake is to pay attention to the background, in all deepfakes, you can spot irregularities in the background as, in most cases, its created using virtual effects so that all deepfakes will have an element of artificialness in the background. 
• Context and Content: Most of the instances of deepfake have been focused towards creating or spreading misinformation hence, the context and content of any video is an integral part of differentiating between an original video and deepfake. 
• Fact-Checking: As a basic cyber safety and digital hygiene protocol, one should always make sure to fact-check each and every piece of information they come across on social media. As a preventive measure, always make sure to fact-check any information or post sharing it with your known ones.  
• AI Tools: When in doubt, check it out, and never refrain from using Deepfake detection tools like- Sentinel, Intel’s real-time deepfake detector - Fake catcher, We Verify, and Microsoft’s Video Authenticator tool to analyze the videos and combating technology with technology. 

Recent Instance 

A deepfake video of actress Rashmika Mandanna recently went viral on social media, creating quite a stir. The video showed a woman entering an elevator who looked remarkably like Mandanna. However, it was later revealed that the woman in the video was not Mandanna, but rather, her face was superimposed using AI tools. Some social media users were deceived into believing that the woman was indeed Mandanna, while others identified it as an AI-generated deepfake. The original video was actually of a British-Indian girl named Zara Patel, who has a substantial following on Instagram. This incident sparked criticism from social media users towards those who created and shared the video merely for views, and there were calls for strict action against the uploaders. The rapid changes in the digital world pose a threat to personal privacy; hence, caution is advised when sharing personal items on social media​​.

Legal Remedies

Although Deepfake is not recognised by law in India, it is indirectly addressed by Sec. 66 E of the IT Act, which makes it illegal to capture, publish, or transmit someone's image in the media without that person's consent, thus violating their privacy. The maximum penalty for this violation is ₹2 lakh in fines or three years in prison. The DPDP Act's applicability in 2023 means that the creation of deepfakes will directly affect an individual's right to digital privacy and will also violate the IT guidelines under the Intermediary Guidelines, as platforms will be required to exercise caution while disseminating and publishing misinformation through deepfakes. The indirect provisions of the Indian Penal Code, which cover the sale and dissemination of derogatory publications, songs and actions, deception in the delivery of property, cheating and dishonestly influencing the delivery of property, and forgery with the intent to defame, are the only legal remedies available for deepfakes. Deep fakes must be recognized legally due to the growing power of misinformation. The Data Protection Board and the soon-to-be-established fact-checking body must recognize crimes related to deepfakes and provide an efficient system for filing complaints.

Conclusion 

Deepfake is an aftermath of the advancements of Web 3.0 and, hence is just the tip of the iceberg in terms of the issues/threats from emerging technologies. It is pertinent to upskill and educate the netizens about the keen aspects of deepfakes to stay safe in the future. At the same time, developing and developed nations need to create policies and laws to efficiently regulate deepfake and to set up redressal mechanisms for victims and industry. As we move ahead, it is pertinent to address the threats originating out of the emerging techs and, at the same time, create a robust resilience for the same. 

References 

• https://www.drishtiias.com/daily-updates/daily-news-analysis/deepfake-technology
• https://timesofindia.indiatimes.com/gadgets-news/explained-what-are-deepfakes-and-how-to-spot-one/articleshow/90916962.cms
• https://www.unite.ai/best-deepfake-detector-tools-and-techniques/

Introduction

‍

In today’s cybersecurity landscape, ransomware has emerged as one of the most significant and rapidly growing cyber threats. What began as attacks carried out by individual hackers has evolved into a highly organised criminal enterprise, with groups operating through structured business models and global networks. The emergence of The Gentlemen ransomware group reflects this transformation, demonstrating how modern threat actors can quickly expand their operations and target organisations across multiple sectors. Their rise highlights the increasing sophistication of ransomware campaigns and the growing challenges faced by organisations in defending against them. The attribution of the group's administrator to an identified individual in Izhevsk, Russia, provides a valuable lens through which to examine three interconnected developments: the maturation of ransomware-as-a-service (RaaS) business models, the inherent operational security (OPSEC) weaknesses that emerge over the course of cybercriminal careers, and the geopolitical environments that enable such actors to operate with relative impunity. Together, these dynamics illustrate the industrialisation of modern cybercrime.

‍

The Industrialisation of Ransomware-as-a-Service

‍

The remarkable rapid rise of The Gentlemen is impossible without discussing the maturation of ransomware-as-a-service (RaaS). RaaS systems utilize network intrusion experts as affiliates who conduct networks intrusions and secure access in exchange for a cut of the total ransoms paid, while a core group builds and maintains the ransomware framework itself. Although Reveton, one of the earliest Raas providers, can be credited with bringing early iterations of RaaS to fruition in 2012, the potential scale was truly evident in the mid-2020s. By 2025 it was estimated that there were over 100 active ransomware gangs operating; this proliferation is the direct result of the franchise-like system, which has lowered the barriers to entry for cybercrime. 

The marketplace surrounding RaaS is intensely competitive, and this is clearly exemplified in the business structure of The Gentlemen: while many of the top ransomware groups provide an 80/20 profit share (with the majority of the profit going to the affiliates), The Gentlemen has an exceptionally profitable 90/10 split (affiliates keep 90% of the profit share) for affiliates, likely to draw experienced operators away from their rivals given recent decreases in victim willingness to pay and corresponding increases in the incentives RaaS platforms are required to offer. 

The operational efficiency of the group is representative of a successful enterprise. They attack vulnerable internet-facing VPNs and firewalls and generally complete the network encryption within a matter of hours, leaving defenders with very little time to respond, as confirmed by Check Point Software, a renowned cybersecurity vendor.

Additionally, PRODAFT reports that the administrator of The Gentlemen, known by the alias Zeta88 (previously known as Hastalamuerte), directly provides affiliates with SSL VPN credentials, often obtained through brutal force attacks or their own private leaked databases, indicating an unusually high level of vertical integration for RaaS groups.

‍

AI as a Force Multiplier in Ransomware Development

‍

A particularly significant aspect of the Hastalamuerte case is PRODAFT's finding that the administrator employs artificial intelligence to develop and maintain ransomware, support associated tooling, and assist post-exploitation operations. This reflects a broader trend observed across the 2025–2026 threat landscape, where AI has increasingly lowered the capability threshold for participation in organised cybercrime. Researchers have documented its role in automating stages of intrusion, accelerating malware development cycles, and simplifying the maintenance of malicious infrastructure. These capabilities have been leveraged by both nation-state actors and criminal enterprises.

The trajectory of Hastalamuerte is especially illustrative. Cybersecurity Forum posts during 2019-2020 depict a hacker who is fairly novice at fundamental penetration testing procedures. A subsequent emergence as the operator of a top-tier ransomware-as-a-service operation indicates that AI-assisted development may be responsible for dramatically reducing the skill level and time necessary to create a successful criminal enterprise in cyberspace. The evolution of these tools should make the route from novice forum user to accomplished ransomware operator more attainable for a wider array of perpetrators in the future.

‍

The OPSEC Paradox: How Cybercriminals Leave a Trail

‍

The attribution of Hastalamuerte's identity by researchers from Intel 471, Flashpoint, and Constella Intelligence demonstrates the effectiveness of modern open-source and commercial intelligence methodologies. A forum registration traceable to an IP address from Izhevsk, Russia linked a Protonmail address, which linked to an Apple account, a GitHub profile, a Telegram handle, a Russian phone number, and finally to a 36 year old marketing professional named Alexander Andreevich Yapaev who was also living in Izhevsk. Investigators did not use an advanced capability in their attribution, but rather a simple OPSEC mistake of consistently reusing credentials. Every username and email address and every phone number creates a linkage between disparate data points, eventually building into a real-world persona. 

It has also come out in the forum discussion that while training for a penetration testing course in 2020, Hastalamuerte displayed the kind of inexperience that a novice would display in traceable, recorded fashion to intelligence databases. It's an example of a broader rule about attribution; attacker mistakes provide the most value. With Russians the lack of apparent consequences may contribute to a lack of need to maintain tight OPSEC from the start.

‍

The Russian Safe Haven: Conditional Impunity and Its Limits

‍

Yapaev's base in Izhevsk is emblematic of the geostrategic situation that has allowed Russian cybercriminality to prosper. Security researchers routinely label Russia's policy as one of "controlled impunity," where the cybercriminality directed at foreign entities is ignored or implicitly condoned, while that directed at Russian interests will prompt a law enforcement response. This constitutes what has been called a "managed market" rather than an "unconditional sanctuary," where many of the named defendants could and likely will continue their illegal enterprise with little fear of reprisal, provided that they do not threaten the interests of the Russian state and do not attempt to move their operations outside of Russian control.

Yet this protection is neither absolute nor permanent. In May 2024, the transnational Operation Endgame campaign highlighted the growing global appetite for damaging the cybercrime ecosystem rooted in Russia. Russian authorities did indeed pursue and seize some assets and operators, but arrests seem largely confined to the lower-rung facilitators of these attacks (hosting providers and payment services), and it seems higher-end ransomware operators continue to evade scrutiny. Selective enforcement thus further bolsters the perception that protection is accorded according to strategic value, not legal standards. For operators such as Hastalamuerte, who possess no publicly documented intelligence connections, growing attribution capabilities, and sustained international pressure may gradually erode the security traditionally associated with operating from within Russia.

‍

Attribution as a Deterrence Instrument

‍

The public identification of Alexander Andreevich Yapaev as Hastalamuerte/Zeta88 shows the continued struggle with the utility of attribution in situations where immediate prosecution is not feasible. Its utility is far more extensive than simply an ability to make an arrest. Functionally, public naming forces a perpetrator into an open evidentiary space and can lead to alterations in their operational habits and effectiveness. Strategically, attribution provides future leverage for sanctions, indictments, financial restrictions, or extradition if the target can leave their safe haven country. The logic behind US rewards programs (paying up to $10 million for the capture and conviction of ransomware operators) relies on this principle. The analytical insight provided by the case cannot be understated either. Hastalamuerte's trajectory from a relative amateur forum participant on Nulled and Raidforums in 2019 to leading a significant ransomware operation by 2026 offers an invaluable look into the career progression of a cyber criminal. It confirms one of the lessons learned through deterrence and attribution: pseudonymity is not everlasting, and many years of OPSEC failures can be pieced together to establish a real-world identity.

‍

Conclusion

‍

The Gentlemen incident is emblematic of the three broad themes that currently characterise cyber warfare: ransomware-as-a-service through innovative competition, common OPSEC failures that enable attribution, and a new, conditional regime of protection for Russian cybercriminals. The obvious defense lesson: increasing attack surfaces require stronger identity, behavioural monitoring, and intelligence capacities. The policy lesson: effective attribution is still an essential tool for comprehension, deterrence, and disruption in an increasingly industrialised environment of criminals supporting each other's operations in ransomware-as-a-service.

‍

References

‍

1. https://krebsonsecurity.com/2026/06/who-runs-the-ransomware-group-the-gentlemen/
2. https://www.recordedfuture.com/
3. https://www.vectra.ai/topics/ransomware-as-a-service
4. https://www.trmlabs.com/es/resources/blog/new-disruption-opportunities-in-the-evolving-ransomware-ecosystem

‍

Recognizing As the Ministry of Electronic and Information Technology (MeitY) continues to invite proposals from academicians, institutions, and industry experts to develop frameworks and tools for AI-related issues through the IndiaAI Mission, it has also funded two AI projects that will deal with matters related to deepfakes as per a status report submitted on 21st November 2024. The Delhi court also ordered the nomination of the members of a nine-member Committee constituted by the MeitY on 20th November 2024 (to address deepfake issues) and asked for a report within three months.‍

Funded AI projects :

The two projects funded by MeitY are:

1. Fake Speech Detection Using Deep Learning Framework- The project was initiated in December 2021 and focuses on detecting fake speech by creating a web interface for detection software this also includes investing in creating a speech verification software platform that is specifically designed for testing fake speech detection systems. It is set to end in December 2024. 
2. Design and Development of Software for Detecting Deepfake Videos and Images- This project was funded by MeitY from January 2022 to March 2024. It also involved the Centre for Development of Advanced Computing (C-DAC), Kolkata and Hyderabad as they have developed a prototype tool capable of detecting deepfakes. Named FakeCheck, it is designed as a desktop application and a web portal aiming to detect deepfakes without the use of the internet. Reports suggest that it is currently undergoing the testing phase and awaiting feedback.

‍

Apart from these projects, MeitY has released their expression of interest for proposals in four other areas which include: 

• Tools that detect AI-generated content along with traceable markers,
• Tools that develop an ethical AI framework for AI systems to be transparent and respect human values,
• An AI risk management and assessment tool that analyses threats and precarious situations of AI-specific risks in public AI use cases and;
• Tools that can assess the resilience of AI in stressful situations such as cyberattacks, national disasters, operational failures, etc. 

CyberPeace Outlook

Deepfakes pose significant challenges to critical sectors in India, such as healthcare and education, where manipulated content can lead to crimes like digital impersonation, misinformation, and fraud. The rapid advancement of AI, with developments (regarding regulation) that can’t keep pace, continues to fuel such threats. Recognising these risks, MeitY’s IndiaAI mission, promoting investments and encouraging educational institutions to undertake AI projects that strengthen the country's digital infrastructure comes in as a guiding light. A part of the mission focuses on developing indigenous solutions, including tools for assessment and regulation, to address AI-related threats effectively. While India is making strides in this direction, the global AI landscape is evolving rapidly, with many nations advancing regulations to mitigate AI-driven challenges. Consistent steps, including inviting proposals and funding projects provide the much-needed impetus for the mission to be realized.

References

1. https://economictimes.indiatimes.com/tech/technology/meity-dot-at-work-on-projects-for-fair-ai-development/articleshow/115777713.cms?from=mdr
2. https://www.hindustantimes.com/india-news/meity-seeks-tools-to-detect-deepfakes-label-ai-generated-content-101734410291642.html
3. https://www.msn.com/en-in/news/India/meity-funds-two-ai-projects-to-detect-fake-media-forms-committee-on-deepfakes/ar-AA1vMAlJ
4. https://indiaai.gov.in/

‍