#FactCheck - Debunking Manipulated Photos of Smiling Secret Service Agents During Trump Assassination Attempt
Executive Summary:
Viral pictures featuring US Secret Service agents smiling while protecting former President Donald Trump during a planned attempt to kill him in Pittsburgh have been clarified as photoshopped pictures. The pictures making the rounds on social media were produced by AI-manipulated tools. The original image shows no smiling agents found on several websites. The event happened with Thomas Mathew Crooks firing bullets at Trump at an event in Butler, PA on July 13, 2024. During the incident one was deceased and two were critically injured. The Secret Service stopped the shooter, and circulating photos in which smiles were faked have stirred up suspicion. The verification of the face-manipulated image was debunked by the CyberPeace Research Team.

Claims:
Viral photos allegedly show United States Secret Service agents smiling while rushing to protect former President Donald Trump during an attempted assassination in Pittsburgh, Pennsylvania.



Fact Check:
Upon receiving the posts, we searched for any credible source that supports the claim made, we found several articles and images of the incident but in those the images were different.

This image was published by CNN news media, in this image we can see the US Secret Service protecting Donald Trump but not smiling. We then checked for AI Manipulation in the image using the AI Image Detection tool, True Media.


We then checked with another AI Image detection tool named, contentatscale AI image detection, which also found it to be AI Manipulated.

Comparison of both photos:

Hence, upon lack of credible sources and detection of AI Manipulation concluded that the image is fake and misleading.
Conclusion:
The viral photos claiming to show Secret Service agents smiling when protecting former President Donald Trump during an assassination attempt have been proven to be digitally manipulated. The original image found on CNN Media shows no agents smiling. The spread of these altered photos resulted in misinformation. The CyberPeace Research Team's investigation and comparison of the original and manipulated images confirm that the viral claims are false.
- Claim: Viral photos allegedly show United States Secret Service agents smiling while rushing to protect former President Donald Trump during an attempted assassination in Pittsburgh, Pennsylvania.
- Claimed on: X, Thread
- Fact Check: Fake & Misleading
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Introduction
The AI Action Summit is a global forum that brings together world leaders, policymakers, technology experts, and industry representatives to discuss AI governance, ethics, and its role in society. This year, the week-long Paris AI Action Summit officially culminated on the 11th of February, 2025. It brought together experts from the industry, policymakers, and other dignitaries to discuss Artificial Intelligence and its challenges. The event was co-chaired by Indian Prime Minister Narendra Modi and French President Emmanuel Macron. In line with the summit, the Indian delegation actively engaged in the 2nd India-France AI Policy Roundtable, an official side event of the summit, and the 14th India-France CEOs Forum. These discussions were on diverse sectors including defense, aerospace, technology, etc. among other things.
Prime Minister Modi’s Address
During the AI Action Summit in Paris, Prime Minister Narendra Modi drew attention to the revolutionary effect of AI in politics, the economy, security, and society. Stressing the requirement of international cooperation, he promoted strong frameworks of governance to combat AI-based risks and consequently, build public confidence in new technologies. Needed efforts with respect to cybersecurity issues such as deepfakes and disinformation were also acknowledged.
Democratising AI, and sharing its benefits, particularly with the Global South not only aligned with Sustainable Development Goals (SDGs) but also affirmed India’s resolve towards sharing expertise and best practices. India’s remarkable feat of creating a Digital Public Infrastructure, that caters to a population of 1.4 billion through open and accessible technology was highlighted as well.
Among the key announcements, India revealed its plans to create its own Large Language Model (LLM) that reflects the country's linguistic diversity, strengthening its AI aspirations. Further, India will be hosting the next AI Action Summit, reaffirming its position in international AI leadership. The Prime Minister also welcomed France's initiatives, such as the launch of the "AI Foundation" and the "Council for Sustainable AI", initiated by President Emmanuel Macron. He emphasized the necessity to extend the Global Partnership for AI and to get it more representative and inclusive so that Global South voices are actually incorporated into AI innovation and governance.
Other Perspectives
Though there were 58 countries that signed the international agreement on a more open, inclusive, sustainable, and ethical approach to AI development (including India, France, and China), the UK and the US have refused to sign the international agreement at the AI Summit stating their issues with global governance and national security. While the former raised concerns about the lack of sufficient details regarding the establishment of global AI governance and AI’s effect on national security as their reason, the latter showcased its reservations about the overly wide AI regulations which had the potential to hamper a transformative industry. Meanwhile, the US is also looking forward to ‘Stargate’, its $500 billion AI infrastructure project alongside the companies- OpenAI, Softbank, and Oracle.
CyberPeace Insights
The Summit has garnered greater significance with the backdrop of the release of platforms such as DeepSeek R1, China’s AI assistant system similar to that of OpenAI’s ChatGPT. On its release, it was the top-rated free application on Apple’s app store and sent the technology stocks tumbling. Moreover, investors world over appreciated the creation of the model which was made roughly in about $5 million while other AI companies spent more in comparison (keeping in mind the restrictions caused by the chip export controls in China). This breakthrough challenges the conventional notion that massive funding is a prerequisite for innovation, offering hope for India’s burgeoning AI ecosystem. With the IndiaAI mission and fewer geopolitical restrictions, India stands at a pivotal moment to drive responsible AI advancements.
References:
- https://www.mea.gov.in/press-releases.htm?dtl/39023/Prime_Minister_cochairs_AI_Action_Summit_in_Paris_February_11_2025
- https://indianexpress.com/article/explained/explained-sci-tech/what-is-stargate-trumps-500-billion-ai-project-9793165/
- https://pib.gov.in/PressReleasePage.aspx?PRID=2102056
- https://pib.gov.in/PressReleasePage.aspx?PRID=2101947
- https://pib.gov.in/PressReleasePage.aspx?PRID=2101896
- https://www.timesnownews.com/technology-science/uk-and-us-decline-to-sign-global-ai-agreement-at-paris-ai-action-summit-here-is-why-article-118164497
- https://www.thehindu.com/sci-tech/technology/india-57-others-sign-paris-joint-statement-on-inclusive-sustainable-ai/article69207937.ece

The evolution of technology has presented both profound benefits and considerable challenges. It has benefited us with global interconnectivity, optimisation of the workforce, faster and solution-oriented approach, but at the same time increases risks of cybercrimes and the misuse of technology via online theft, fraud, and abuse. As the reliance on technology increases, it makes the users vulnerable to cyberattacks.
One way to address this nuisance is to set global standards and initiate measures for cooperation by integrating the efforts of international institutions such as UN bodies and others. The United Nations Interregional Crime and Justice Research Institute, which combats cybercrime and promotes the responsible use of technology, is making waves in these issues.
Understanding the Scope of the Problem
Crowdstrike had estimated the cybersecurity market at $207.77 billion in 2024 and expected it to reach $376.55 billion by 2029 and continue growing at a CAGR of 12.63% during the forecast period. In October of 2024, Forbes predicted that the cost of cyber attacks on the global economy would be over $10.5 trillion.
The developments in technology have provided cybercriminals with more sophisticated means to commit cybercrimes. These include cybercrimes like data breaches, which are increasingly common, such as phishing attacks, ransomware, social engineering, and IoT attacks. Their impact is evident across various domains, including economic and social spheres. The victims of cybercrimes can often suffer from stress, anxiety, fear of being victimised again, a lack of trust and social polarisation/stigmatisation.
UNICRI’s Strategic Approach
UNICRI actively combats cybercrimes and technology misuse, focusing on cybersecurity, organized crime in cyberspace, and terrorists' internet use. Since 2020, it has monitored social media misuse, analysed tools to debunk misinformation and balanced security with human rights.
The key focus areas of UNICRI’s strategic approach include cybersecurity in robotics, critical infrastructure, and SCADA systems, digital forensics, child online protection and addressing online profiling and discrimination. It further supports LEAs (judges, prosecutors, and investigators) by providing them with specialised training. Its strategies to counter cybercrime and tech misuse include capacity-building exercises for law enforcement, developing international legal frameworks, and fostering public-private collaborations.
Key Initiatives under UNICRI Strategic Programme Framework of 2023-2026
The key initiatives under UNICRI set out the strategic priority areas that will guide its work. It includes:
- Prevent and Counter Violent Extremism: By addressing the drivers of radicalisation, gender-based discrimination, and leveraging sports for prevention.
- Combat Organised Crime: Via tackling illicit financial flows, counterfeiting, and supply chain crimes while promoting asset recovery.
- Promotion of Emerging Technology Governance: Encouraging responsible AI use, mitigating cybercrime risks, and fostering digital inclusivity.
- Rule of Law and Justice Access: Enhancing justice systems for women and vulnerable populations while advancing criminal law education.
- CBRN Risk Mitigation: Leveraging expert networks and whole-of-society strategies to address chemical, biological, radiological, and nuclear risks.
The Challenges and Opportunities: CyberPeace Takeaways
The challenges that affect the regulation of cybercrimes are most often caused due to jurisdictional barriers, the lack of resources, and the rapid pace of technological change. This is due to the cross-border nature of cybercrimes and as many nations lack the expertise or infrastructure to address sophisticated cyber threats. The regulatory or legislative frameworks often get outpaced by technology developments, including quantum computing, deepfakes, or blockchain misuse. Due to this, these crimes are often unpunished.
The opportunities that have been developing for innovation in cybercrime prevention, include AI and machine learning tools to detect cybercrimes, enhanced international cooperation that can strengthen the collective defence mechanisms, like multi-stakeholder approaches. Capacity Building initiatives for continuous training and education help LEAs and judicial systems adapt to emerging threats, is a continuous effort that requires participation from all sectors, be it public or private.
Conclusion
Due to cybercrimes and the threats they induce on individuals, communities, and global security, the proactive approach by UNICRI of combining international cooperation, capacity-building and innovative strategies is pivotal in combating these challenges. By addressing the challenges of organised crime in cyberspace, child online protection, and emerging technology governance, UNICRI exemplifies the power of strategic engagement. While jurisdictional barriers and resource limitations persist, the opportunities in AI, global collaboration, and education offer a path forward. With the evolution of technology, our defences must also be dynamic and ever evolving, and UNICRI’s efforts are essential to building a safer, more inclusive digital future for all.
References
- https://unicri.it/special_topics/securing_cyberspace
- https://www.forbes.com/sites/bernardmarr/2023/10/11/the-10-biggest-cyber-security-trends-in-2024-everyone-must-be-ready-for-now/
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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.