#FactCheck - AI Generated image of Virat Kohli falsely claims to be sand art of a child
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
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Executive Summary:
A video featuring Sara Netanyahu, wife of Israeli Prime Minister Benjamin Netanyahu, is being widely circulated on social media. In the clip, she is seen attending an online meeting and repeatedly closing her eyes. The video is being shared with claims that it is recent and shows her under the influence of drugs. Some posts also suggest that Prime Minister Netanyahu has died. However, research by the CyberPeace found that the claim is misleading. The video is not recent and has been online since 2020.
Claim:
Social media users are sharing the video claiming that Sara Netanyahu appeared intoxicated following the alleged death of Prime Minister Benjamin Netanyahu. The clip is also being falsely presented as a recent development. An X user, Christopher Montgomery (@Montgsignals), shared the video with the caption suggesting that Netanyahu may have died and that his wife appeared in a drug-influenced state during a recent court hearing via Zoom.
Fact Check:
To verify the claim, we first examined reports regarding the alleged death of Benjamin Netanyahu. There is no credible evidence supporting this claim. In fact, on March 20, Netanyahu himself addressed the media and dismissed such rumours, confirming that he is alive.
We then analyzed the viral video by extracting keyframes and conducting a reverse search. This led us to the same video posted on a Facebook account under the name Roni Schneider Malia on November 4, 2020. The Hebrew caption associated with the post translates to: “Filmed during a psychological conference on Zoom.”
This confirms that the video is old and unrelated to any recent developments.
Conclusion:
The viral claim is misleading. The video of Sara Netanyahu is not recent but has been available online since 2020. It is being falsely linked to baseless claims about Prime Minister Benjamin Netanyahu’s death
A video of Bollywood actor and Kolkata Knight Riders (KKR) owner Shah Rukh Khan is going viral on social media. The video claims that Shah Rukh Khan is reacting to opposition against Bangladeshi bowler Mustafizur Rahman playing for KKR and is allegedly calling industrialist Gautam Adani a “traitor,” while appealing to stop Hindu–Muslim politics.
Research by the CyberPeace Foundation found that the voice heard in the video is not Shah Rukh Khan’s but is AI-generated. Shah Rukh Khan has not made any official statement regarding Mustafizur Rahman’s removal from KKR. The claim made in the video concerning industrialist Gautam Adani is also completely misleading and baseless.
Claim
In the viral video, Shah Rukh Khan is allegedly heard saying: “People barking about Mustafizur Rahman playing for KKR should stop it. Adani is earning money by betraying the country by supplying electricity from India to Bangladesh. Leave Hindu–Muslim politics and raise your voice against traitors like Adani for the welfare of the country. Mustafizur Rahman will continue to play for the team.”
The post link, archive link, and screenshots can be seen below:
- Archive link: https://archive.is/XsQXp
- Facebook reel link: https://www.facebook.com/reel/1220246633365097
Research
We examined the key frames of Shah Rukh Khan’s viral video using Google Lens. During this process, we found the original video on the official YouTube channel Talks at Google, which was uploaded on 2 October 2014.
In this video, Shah Rukh Khan is seen wearing the same outfit as in the viral clip. He is seen responding to questions from Google CEO Sundar Pichai. The YouTube video description mentions that Shah Rukh Khan participated in a fireside chat held at the Googleplex, where he answered Pichai’s questions and also promoted his upcoming film “Happy New Year.”
The link to the video is given : https://www.youtube.com/watch?v=H_8UBv5bZo0
Upon closely analyzing the viral video of Shah Rukh Khan, we noticed a clear mismatch between his voice and lip movements (lip sync). Such inconsistencies usually appear when the original video or its audio has been tampered with.
We then examined the audio present in the video using the AI detection tool Aurigin. According to the tool’s results, the audio in the viral video was found to be approximately 99 percent AI-generated.
Conclusion
Our research confirmed that the voice heard in the video is not Shah Rukh Khan’s but is AI-generated. Shah Rukh Khan has not made any official comment regarding Mustafizur Rahman’s removal from KKR. Additionally, the claims made in the video about industrialist Gautam Adani are completely misleading and baseless.
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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.
