#FactCheck- AI-Generated Video Falsely Claims Iran Shot Down US F-35 Fighter Jet

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:

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.

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Introduction

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In today’s digital era, warfare is being redefined. Defence Minister Rajnath Singh recently stated that “we are in the age of Grey Zone and hybrid warfare where cyber-attacks, disinformation campaigns and economic warfare have become tools to achieve politico-military aims without a single shot being fired.” The crippling cyberattacks on Estonia in 2007, Russia’s interference in the 2016 US elections, and the ransomware strike on the Colonial Pipeline in the United States in 2021 all demonstrate how states are now using cyberspace to achieve strategic goals while carefully circumventing the threshold of open war.

Legal Complexities: Attribution, Response, and Accountability

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Grey zone warfare challenges the traditional notions of security and international conventions on peace due to inherent challenges such as :

• Attribution
  The first challenge in cyber warfare is determining who is responsible. Threat actors hide behind rented botnets, fake IP addresses, and servers scattered across the globe. Investigators can follow digital trails, but those trails often point to machines, not people. That makes attribution more of an educated guess than a certainty. A wrong guess could lead to misattribution of blame, which could beget a diplomatic crisis, or worse, a military one.
• Proportional Response
  Even if attribution is clear, designing a response can be a challenge. International law does give room for countermeasures if they are both ‘necessary’ and ‘proportionate’. But defining these qualifiers can be a long-drawn, contested process. Effectively, governments employ softer measures such as protests or sanctions, tighten their cyber defences or, in extreme cases, strike back digitally.
• Accountability
  States can be held responsible for waging cyber attacks under the UN’s Draft Articles on State Responsibility. But these are non-binding and enforcement depends on collective pressure, which can be slow and inconsistent. In cyberspace, accountability often ends up being more symbolic than real, leaving plenty of room for repeat offences.

International and Indian Legal Frameworks

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Cyber law is a step behind cyber warfare since existing international frameworks are often inadequate. For example, the Tallinn Manual 2.0, the closest thing we have to a rulebook for cyber conflict, is just a set of guidelines. It says that if a cyber operation can be tied to a state, even through hired hackers or proxies, then that state can be held responsible. But attribution is a major challenge. Similarly, the United Nations has tried to build order through its Group of Governmental Experts (GGE) that promotes norms like “don’t attack. However, these norms are not binding, effectively leaving practice to diplomacy and trust.

India is susceptible to routine attacks from hostile actors, but does not yet have a dedicated cyber warfare law.  While Section 66F of the IT ACT, 2000, talks about cyber terrorism, and Section 75 lets Indian courts examine crimes committed abroad if they impact India,  grey-zone tactics like fake news campaigns, election meddling, and influence operations fall into a legal vacuum.

Way Forward

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• Strengthen International Cooperation
  Frameworks like the Tallinn Manual 2.0 can form the basis for future treaties. Bilateral and multilateral agreements between countries are essential to ensure accountability and cooperation in tackling grey zone activities.
• Develop Grey Zone Legislation
  India currently relies on the IT Act, 2000, but this law needs expansion to specifically cover grey zone tactics such as election interference, propaganda, and large-scale disinformation campaigns.
• Establish Active Monitoring Systems
  India must create robust early detection systems to identify grey zone operations in cyberspace. Agencies can coordinate with social media platforms like Instagram, Facebook, X (Twitter), and YouTube, which are often exploited for propaganda and disinformation, to improve monitoring frameworks.
• Dedicated Theatre Commands for Cyber Operations
  Along with the existing Defence Cyber Agency, India should consider specialised theatre commands for grey zone and cyber warfare. This would optimise resources, enhance coordination, and ensure unified command in dealing with hybrid threats.

Conclusion

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Grey zone warfare in cyberspace is no longer an optional tactic used by threat actors but a routine activity. India lacks the early detection systems, robust infrastructure, and strong cyber laws to counter grey-zone warfare. To counter this, India needs sharper attribution tools for early detection and must actively push for stronger international rules in this global landscape. More importantly, instead of merely blaming without clear plans, India should focus on preparing for solid retaliation strategies. By doing so, India can also learn to use cyberspace strategically to achieve politico-military aims without firing a single shot.

References

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• Tallinn Manual 2.0 on the International Law Applicable to Cyber Operations (Michael N. Schmitt)
• UN Document on International Law in Cyberspace (UN Digital Library)
• NATO Cyber Defence Policy
• Texas Law Review: State Responsibility and Attribution of Cyber Intrusions
• Deccan Herald: Defence Minister on Grey Zone Warfare
• VisionIAS: Grey Zone Warfare
• Sachin Tiwari, The Reality of Cyber Operations in the Grey Zone

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Executive Summary:

A video of Prime Minister Narendra Modi is going viral across multiple social media platforms. In the clip, PM Modi is purportedly heard praising Christianity and stating that only Jesus Christ can lead people to heaven.Several users are sharing and commenting on the video, believing it to be genuine. The CyberPeace researched the viral claim and found it to be false. The circulating video has been created using artificial intelligence (AI).

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Claim:

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On January 29, 2026, a Facebook user named ‘Khaju Damor’ posted the viral video of PM Modi. The post gained traction, with many users sharing and commenting on it as if it were authentic. (Links and archived versions provided)

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• https://www.facebook.com/reel/1683238026381611 
• https://perma.cc/58VU-CHN5 

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Fact Check:

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As part of our research , we first closely examined the viral video. Upon careful observation, several inconsistencies were noticed. The Prime Minister’s facial expressions and hand movements appeared unnatural. The lip-sync and overall visual presentation also raised suspicions about the clip being digitally manipulated. To verify this further, we analyzed the video using the AI detection tool Hive Moderation. The tool’s analysis indicated a 99% probability that the video was AI-generated.

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To independently confirm the findings, we also ran the clip through another detection platform, Undetectable.ai. Its analysis likewise indicated a very high likelihood that the video was created using artificial intelligence.

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Conclusion:

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Our research confirms that the viral video of Prime Minister Narendra Modi praising Christianity and making the alleged statement about heaven is fake. The clip has been generated using AI tools and does not depict a real statement made by the Prime Minister.

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