#FactCheck - MS Dhoni Sculpture Falsely Portrayed as Chanakya 3D Recreation
Executive Summary:
A widely used news on social media is that a 3D model of Chanakya, supposedly made by Magadha DS University matches with MS Dhoni. However, fact-checking reveals that it is a 3D model of MS Dhoni not Chanakya. This MS Dhoni-3D model was created by artist Ankur Khatri and Magadha DS University does not appear to exist in the World. Khatri uploaded the model on ArtStation, calling it an MS Dhoni similarity study.

Claims:
The image being shared is claimed to be a 3D rendering of the ancient philosopher Chanakya created by Magadha DS University. However, people are noticing a striking similarity to the Indian cricketer MS Dhoni in the image.



Fact Check:
After receiving the post, we ran a reverse image search on the image. We landed on a Portfolio of a freelance character model named Ankur Khatri. We found the viral image over there and he gave a headline to the work as “MS Dhoni likeness study”. We also found some other character models in his portfolio.



Subsequently, we searched for the mentioned University which was named as Magadha DS University. But found no University with the same name, instead the name is Magadh University and it is located in Bodhgaya, Bihar. We searched the internet for any model, made by Magadh University but found nothing. The next step was to conduct an analysis on the Freelance Character artist profile, where we found that he has a dedicated Instagram channel where he posted a detailed video of his creative process that resulted in the MS Dhoni character model.

We concluded that the viral image is not a reconstruction of Indian philosopher Chanakya but a reconstruction of Cricketer MS Dhoni created by an artist named Ankur Khatri, not any University named Magadha DS.
Conclusion:
The viral claim that the 3D model is a recreation of the ancient philosopher Chanakya by a university called Magadha DS University is False and Misleading. In reality, the model is a digital artwork of former Indian cricket captain MS Dhoni, created by artist Ankur Khatri. There is no evidence of a Magadha DS University existence. There is a university named Magadh University in Bodh Gaya, Bihar despite its similar name, we found no evidence in the model's creation. Therefore, the claim is debunked, and the image is confirmed to be a depiction of MS Dhoni, not Chanakya.
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How to expand law firms and the corporate world with the help of technology?
If we talk about how lawyers’ lives will be impacted by technology then I would explain about law students first. Students are the one who is utilizing the technology at its best for their work, tech could be helpful in students’ lives. as law students use SCC online and manupatra, which are used for case laws. And during their law internships, they use it to help their seniors to find appropriate cases for them. and use it as well for their college research work. SCC and manupatra are very big platforms by which we can say if students use technology for their careers, it will impact their law career in the best ways.
A lawyer running a law firm is not a small task, and there are plenty of obstacles to that, such as a lack of tech solutions, failure to fulfil demands, and inability to innovate, these obstacles prevent the growth of some firms. The right legal tech can grow an organization or a law firm and there will be fewer obstacles.
Technology can be proven as a good mechanism to grow the law firm, as everything depends on tech, from court work to corporate. If we talk about covid during 2020, everything shifted towards the virtual world, court hearings switched to online mode due to covid which proved as a bone to the legal system as the case hearings were speedy and there was no physical contact due to that.
Legal automation is also helping law firms to grow in a competitive world. And it has other benefits also like shifting tedious tasks from humans to machines, allowing the lawyer to work on more valuable work. I would say that small firms should also need to embrace automation for competition in the corporate sector. Today, artificial intelligence offers a solution to solve or at least make the access-to-justice issue better and completely transform our traditional legal system.
There was a world-cited author, Richard Susskind, OBE, who talked about the future of law and lawyers and he wrote a book, Online Courts and the Future of Justice. Richard argues that technology is going to bring about a fascinating decade of change in the legal sector and transform our court system. Although automating our old ways of working plays a part in this, even more, critical is that artificial intelligence and technology will help give more individuals access to justice.
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During covid, there were e-courts services in courts, and lawyers and judges were taking cases online. After the covid, the use of technology increased in the law field also from litigation to corporate. As technology can also safeguard confidential information between parties and lawyers. There was ODR, (online dispute resolution) happening meetings that were taking place online mode.
File sharing is inevitable in the practice of law. Yet sometimes the most common ways of sharing (think email) are not always the most secure. With the remote office, the boom has come an increased need for alternate file-sharing solutions. There is data encryption to protect data as it is a reliable method to protect confidential data and information.
Conclusion-
Technology has been playing a vital role in the legal industry and has increased the efficiency of legal offices and the productivity of clerical workers. With the advent of legal tech, there is greater transparency between legal firms and clients. Clients know how many fees they must pay and can keep track of the day-to-day progress of the lawyer on their case. Also, there is no doubt that technology, if used correctly, is fast and efficient – more than any human individual. This can prove to be of great assistance to any law firm. Lawyers of the future will be the ones who create the systems that will solve their client’s problems. These legal professionals will include legal knowledge engineers, legal risk managers, system developers, design thinking experts, and others. These people will use technology to create new ways of solving legal problems. In many ways, the legal sector is experiencing the same digitization that other industries have, and because it is so document-intensive, it is actually an industry that stands to benefit greatly from what technology has to offer.
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Introduction
Artificial Intelligence (AI) driven autonomous weapons are reshaping military strategy, acting as force multipliers that can independently assess threats, adapt to dynamic combat environments, and execute missions with minimal human intervention, pushing the boundaries of modern warfare tactics. AI has become a critical component of modern technology-driven warfare and has simultaneously impacted many spheres in a technology-driven world. Nations often prioritise defence for significant investments, supporting its growth and modernisation. AI has become a prime area of investment and development for technological superiority in defence forces. India’s focus on defence modernisation is evident through initiatives like the Defence AI Council and the Task Force on Strategic Implementation of AI for National Security.
The main requirement that Autonomous Weapons Systems (AWS) require is the “autonomy” to perform their functions when direction or input from a human actor is absent. AI is not a prerequisite for the functioning of AWSs, but, when incorporated, AI could further enable such systems. While militaries seek to apply increasingly sophisticated AI and automation to weapons technologies, several questions arise. Ethical concerns have been raised for AWS as the more prominent issue by many states, international organisations, civil society groups and even many distinguished figures.
Ethical Concerns Surrounding Autonomous Weapons
The delegation of life-and-death decisions to machines is the ethical dilemma that surrounds AWS. A major concern is the lack of human oversight, raising questions about accountability. What if AWS malfunctions or violates international laws, potentially committing war crimes? This ambiguity fuels debate over the dangers of entrusting lethal force to non-human actors. Additionally, AWS poses humanitarian risks, particularly to civilians, as flawed algorithms could make disastrous decisions. The dehumanisation of warfare and the violation of human dignity are critical concerns when AWS is in question, as targets become reduced to mere data points. The impact on operators’ moral judgment and empathy is also troubling, alongside the risk of algorithmic bias leading to unjust or disproportionate targeting. These ethical challenges are deeply concerning.
Balancing Ethical Considerations and Innovations
It is immaterial how advanced a computer becomes in simulating human emotions like compassion, empathy, altruism, or other emotions as the machine will only be imitating them, not experiencing them as a human would. A potential solution to this ethical predicament is using a 'human-in-the-loop' or 'human-on-the-loop' semi-autonomous system. This would act as a compromise between autonomy and accountability.
A “human-on-the-loop” system is designed to provide human operators with the ability to intervene and terminate engagements before unacceptable levels of damage occur. For example, defensive weapon systems could autonomously select and engage targets based on their programming, during which a human operator retains full supervision and can override the system within a limited period if necessary.
In contrast, a ‘human-in-the-loop” system is intended to engage individual targets or specific target groups pre-selected by a human operator. Examples would include homing munitions that, once launched to a particular target location, search for and attack preprogrammed categories of targets within the area.
International Debate and Regulatory Frameworks
The regulation of autonomous weapons that employ AI, in particular, is a pressing global issue due to the ethical, legal, and security concerns it contains. There are many ongoing efforts at the international level which are in discussion to regulate such weapons. One such example is the initiative under the United Nations Convention on CertainConventional Weapons (CCW), where member states, India being an active participant, debate the limits of AI in warfare. However, existing international laws, such as the Geneva Conventions, offer legal protection by prohibiting indiscriminate attacks and mandating the distinction between combatants and civilians. The key challenge lies in achieving global consensus, as different nations have varied interests and levels of technological advancement. Some countries advocate for a preemptive ban on fully autonomous weapons, while others prioritise military innovation. The complexity of defining human control and accountability further complicates efforts to establish binding regulations, making global cooperation both essential and challenging.
The Future of AI in Defence and the Need for Stronger Regulations
The evolution of autonomous weapons poses complex ethical and security challenges. As AI-driven systems become more advanced, a growing risk of its misuse in warfare is also advancing, where lethal decisions could be made without human oversight. Proactive regulation is crucial to prevent unethical use of AI, such as indiscriminate attacks or violations of international law. Setting clear boundaries on autonomous weapons now can help avoid future humanitarian crises. India’s defence policy already recognises the importance of regulating the use of AI and AWS, as evidenced by the formation of bodies like the Defence AI Project Agency (DAIPA) for enabling AI-based processes in defence Organisations. Global cooperation is essential for creating robust regulations that balance technological innovation with ethical considerations. Such collaboration would ensure that autonomous weapons are used responsibly, protecting civilians and combatants, while encouraging innovation within a framework prioritising human dignity and international security.
Conclusion
AWS and AI in warfare present significant ethical, legal, and security challenges. While these technologies promise enhanced military capabilities, they raise concerns about accountability, human oversight, and humanitarian risks. Balancing innovation with ethical responsibility is crucial, and semi-autonomous systems offer a potential compromise. India’s efforts to regulate AI in defence highlight the importance of proactive governance. Global cooperation is essential in establishing robust regulations that ensure AWS is used responsibly, prioritising human dignity and adherence to international law, while fostering technological advancement.
References
● https://indianexpress.com/article/explained/reaim-summit-ai-war-weapons-9556525/
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Executive Summary:
In late 2024 an Indian healthcare provider experienced a severe cybersecurity attack that demonstrated how powerful AI ransomware is. This blog discusses the background to the attack, how it took place and the effects it caused (both medical and financial), how organisations reacted, and the final result of it all, stressing on possible dangers in the healthcare industry with a lack of sufficiently adequate cybersecurity measures in place. The incident also interrupted the normal functioning of business and explained the possible economic and image losses from cyber threats. Other technical results of the study also provide more evidence and analysis of the advanced AI malware and best practices for defending against them.
1. Introduction
The integration of artificial intelligence (AI) in cybersecurity has revolutionised both defence mechanisms and the strategies employed by cybercriminals. AI-powered attacks, particularly ransomware, have become increasingly sophisticated, posing significant threats to various sectors, including healthcare. This report delves into a case study of an AI-powered ransomware attack on a prominent Indian healthcare provider in 2024, analysing the attack's execution, impact, and the subsequent response, along with key technical findings.
2. Background
In late 2024, a leading healthcare organisation in India which is involved in the research and development of AI techniques fell prey to a ransomware attack that was AI driven to get the most out of it. With many businesses today relying on data especially in the healthcare industry that requires real-time operations, health care has become the favourite of cyber criminals. AI aided attackers were able to cause far more detailed and damaging attack that severely affected the operation of the provider whilst jeopardising the safety of the patient information.
3. Attack Execution
The attack began with the launch of a phishing email designed to target a hospital administrator. They received an email with an infected attachment which when clicked in some cases injected the AI enabled ransomware into the hospitals network. AI incorporated ransomware was not as blasé as traditional ransomware, which sends copies to anyone, this studied the hospital’s IT network. First, it focused and targeted important systems which involved implementation of encryption such as the electronic health records and the billing departments.
The fact that the malware had an AI feature allowed it to learn and adjust its way of propagation in the network, and prioritise the encryption of most valuable data. This accuracy did not only increase the possibility of the potential ransom demand but also it allowed reducing the risks of the possibility of early discovery.
4. Impact
- The consequences of the attack were immediate and severe: The consequences of the attack were immediate and severe.
- Operational Disruption: The centralization of important systems made the hospital cease its functionality through the acts of encrypting the respective components. Operations such as surgeries, routine medical procedures and admitting of patients were slowed or in some cases referred to other hospitals.
- Data Security: Electronic patient records and associated billing data became off-limit because of the vulnerability of patient confidentiality. The danger of data loss was on the verge of becoming permanent, much to the concern of both the healthcare provider and its patients.
- Financial Loss: The attackers asked for 100 crore Indian rupees (approximately 12 USD million) for the decryption key. Despite the hospital not paying for it, there were certain losses that include the operational loss due to the server being down, loss incurred by the patients who were affected in one way or the other, loss incurred in responding to such an incident and the loss due to bad reputation.
5. Response
As soon as the hotel’s management was informed about the presence of ransomware, its IT department joined forces with cybersecurity professionals and local police. The team decided not to pay the ransom and instead recover the systems from backup. Despite the fact that this was an ethically and strategically correct decision, it was not without some challenges. Reconstruction was gradual, and certain elements of the patients’ records were permanently erased.
In order to avoid such attacks in the future, the healthcare provider put into force several organisational and technical actions such as network isolation and increase of cybersecurity measures. Even so, the attack revealed serious breaches in the provider’s IT systems security measures and protocols.
6. Outcome
The attack had far-reaching consequences:
- Financial Impact: A healthcare provider suffers a lot of crashes in its reckoning due to substantial service disruption as well as bolstering cybersecurity and compensating patients.
- Reputational Damage: The leakage of the data had a potential of causing a complete loss of confidence from patients and the public this affecting the reputation of the provider. This, of course, had an effect on patient care, and ultimately resulted in long-term effects on revenue as patients were retained.
- Industry Awareness: The breakthrough fed discussions across the country on how to improve cybersecurity provisions in the healthcare industry. It woke up the other care providers to review and improve their cyber defence status.
7. Technical Findings
The AI-powered ransomware attack on the healthcare provider revealed several technical vulnerabilities and provided insights into the sophisticated mechanisms employed by the attackers. These findings highlight the evolving threat landscape and the importance of advanced cybersecurity measures.
7.1 Phishing Vector and Initial Penetration
- Sophisticated Phishing Tactics: The phishing email was crafted with precision, utilising AI to mimic the communication style of trusted contacts within the organisation. The email bypassed standard email filters, indicating a high level of customization and adaptation, likely due to AI-driven analysis of previous successful phishing attempts.
- Exploitation of Human Error: The phishing email targeted an administrative user with access to critical systems, exploiting the lack of stringent access controls and user awareness. The successful penetration into the network highlighted the need for multi-factor authentication (MFA) and continuous training on identifying phishing attempts.
7.2 AI-Driven Malware Behavior
- Dynamic Network Mapping: Once inside the network, the AI-powered malware executed a sophisticated mapping of the hospital's IT infrastructure. Using machine learning algorithms, the malware identified the most critical systems—such as Electronic Health Records (EHR) and the billing system—prioritising them for encryption. This dynamic mapping capability allowed the malware to maximise damage while minimising its footprint, delaying detection.
- Adaptive Encryption Techniques: The malware employed adaptive encryption techniques, adjusting its encryption strategy based on the system's response. For instance, if it detected attempts to isolate the network or initiate backup protocols, it accelerated the encryption process or targeted backup systems directly, demonstrating an ability to anticipate and counteract defensive measures.
- Evasive Tactics: The ransomware utilised advanced evasion tactics, such as polymorphic code and anti-forensic features, to avoid detection by traditional antivirus software and security monitoring tools. The AI component allowed the malware to alter its code and behaviour in real time, making signature-based detection methods ineffective.
7.3 Vulnerability Exploitation
- Weaknesses in Network Segmentation: The hospital’s network was insufficiently segmented, allowing the ransomware to spread rapidly across various departments. The malware exploited this lack of segmentation to access critical systems that should have been isolated from each other, indicating the need for stronger network architecture and micro-segmentation.
- Inadequate Patch Management: The attackers exploited unpatched vulnerabilities in the hospital’s IT infrastructure, particularly within outdated software used for managing patient records and billing. The failure to apply timely patches allowed the ransomware to penetrate and escalate privileges within the network, underlining the importance of rigorous patch management policies.
7.4 Data Recovery and Backup Failures
- Inaccessible Backups: The malware specifically targeted backup servers, encrypting them alongside primary systems. This revealed weaknesses in the backup strategy, including the lack of offline or immutable backups that could have been used for recovery. The healthcare provider’s reliance on connected backups left them vulnerable to such targeted attacks.
- Slow Recovery Process: The restoration of systems from backups was hindered by the sheer volume of encrypted data and the complexity of the hospital’s IT environment. The investigation found that the backups were not regularly tested for integrity and completeness, resulting in partial data loss and extended downtime during recovery.
7.5 Incident Response and Containment
- Delayed Detection and Response: The initial response was delayed due to the sophisticated nature of the attack, with traditional security measures failing to identify the ransomware until significant damage had occurred. The AI-powered malware’s ability to adapt and camouflage its activities contributed to this delay, highlighting the need for AI-enhanced detection and response tools.
- Forensic Analysis Challenges: The anti-forensic capabilities of the malware, including log wiping and data obfuscation, complicated the post-incident forensic analysis. Investigators had to rely on advanced techniques, such as memory forensics and machine learning-based anomaly detection, to trace the malware’s activities and identify the attack vector.
8. Recommendations Based on Technical Findings
To prevent similar incidents, the following measures are recommended:
- AI-Powered Threat Detection: Implement AI-driven threat detection systems capable of identifying and responding to AI-powered attacks in real time. These systems should include behavioural analysis, anomaly detection, and machine learning models trained on diverse datasets.
- Enhanced Backup Strategies: Develop a more resilient backup strategy that includes offline, air-gapped, or immutable backups. Regularly test backup systems to ensure they can be restored quickly and effectively in the event of a ransomware attack.
- Strengthened Network Segmentation: Re-architect the network with robust segmentation and micro-segmentation to limit the spread of malware. Critical systems should be isolated, and access should be tightly controlled and monitored.
- Regular Vulnerability Assessments: Conduct frequent vulnerability assessments and patch management audits to ensure all systems are up to date. Implement automated patch management tools where possible to reduce the window of exposure to known vulnerabilities.
- Advanced Phishing Defences: Deploy AI-powered anti-phishing tools that can detect and block sophisticated phishing attempts. Train staff regularly on the latest phishing tactics, including how to recognize AI-generated phishing emails.
9. Conclusion
The AI empowered ransomware attack on the Indian healthcare provider in 2024 makes it clear that the threat of advanced cyber attacks has grown in the healthcare facilities. Sophisticated technical brief outlines the steps used by hackers hence underlining the importance of ongoing active and strong security. This event is a stark message to all about the importance of not only remaining alert and implementing strong investments in cybersecurity but also embarking on the formulation of measures on how best to counter such incidents with limited harm. AI is now being used by cybercriminals to increase the effectiveness of the attacks they make and it is now high time all healthcare organisations ensure that their crucial systems and data are well protected from such attacks.