#FactCheck -AI-Generated Video Falsely Shows Giorgia Meloni Storming Out After Ending Agreements With Israel
Executive Summary
A video purportedly showing Italian Prime Minister Giorgia Meloni angrily addressing a room full of delegates before throwing a bundle of papers and storming out has gone viral on social media. The clip is being shared alongside claims that Meloni terminated all agreements with Israel following growing tensions over the conflict in the Middle East. However, CyberPeace Research Wing research found that the viral video is not authentic. The clip was generated using Artificial Intelligence (AI).
Claim
On April 24, 2026, an X user shared the viral video with the caption:“Italy's woman Prime Minister has terminated all agreements with Israel!! Italy's woman Prime Minister is far more courageous and fearless than the leaders of 56 Islamic nations.”
- https://x.com/middle_East_up/status/2047597154257297878?s=20
- https://perma.cc/4EM9-5GS4
Fact Check
To verify the claim, we examined official records related to agreements between Italy and Israel. Data available from the Italian Ministry of Foreign Affairs and International Cooperation shows that multiple bilateral agreements between the two countries remain in force in 2026.
- https://atrio.esteri.it/Home/Search
Further research found reports related to discussions within the European Union regarding the suspension of certain cooperation arrangements with Israel. During a meeting of EU foreign ministers in Luxembourg, Spain and Ireland renewed calls to review the EU-Israel Association Agreement. However, Italian Foreign Minister Antonio Tajani reportedly stated that no decision would be taken that day. A closer examination of the viral clip revealed several visual inconsistencies commonly associated with AI-generated content, including unnatural facial movements, irregular body gestures, and unrealistic scene transitions.
To further verify the footage, we analysed it using the DeepFake-o-Meter tool. Results from three separate detection models indicated that the video was likely generated using artificial intelligence.
Conclusion
CyberPeace Research Wing research found that the viral video allegedly showing Italian Prime Minister Giorgia Meloni angrily terminating agreements with Israel is AI-generated. There is no evidence that the incident shown in the clip actually occurred.
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Introduction:
Welcome to the second edition of our blog on Digital forensics series. In our previous blog we discussed what digital forensics is, the process followed by the tools, and the subsequent challenges faced in the field. Further, we looked at how the future of Digital Forensics will hold in the current scenario. Today, we will explore differences between 3 particular similar sounding terms that vary significantly in functionality when implemented: Copying, Cloning and Imaging.
In Digital Forensics, the preservation and analysis of electronic evidence are important for investigations and legal proceedings. Replication of the data and devices is one of the fundamental tasks in this domain, without compromising the integrity of the original evidence.
Three primary techniques -- copying, cloning, and imaging -- are used for this purpose. Each technique has its own strengths and is applied according to the needs of the investigation.
In this blog, we will examine the differences between copying, cloning and imaging. We will talk about the importance of each technique, their applications and why imaging is considered the best for forensic investigations.
Copying
Copying means duplicating data or files from one location to another. When one does copying, it implies that one is using standard copy commands. However, when dealing with evidence, it might be hard to use copy only. It is because the standard copy can alter the metadata and change the hidden or deleted data .
The characteristics of copying include:
- Speed: copying is simpler and faster,compared to cloning or imaging.
- Risk: The risk involved in copying is that the metadata might be altered and all the data might be captured.
Cloning
It is the process where the transfer of the entire contents of a hard drive or a storage device is done on another storage device. This process is known as cloning . This way, the cloning process captures both the active data and the unallocated space and hidden partitions, thus containing the whole structure of the original device. Cloning is generally used at the sector level of the device. Clones can be used as the working copy of a device .
Characteristics of cloning:
- bit-for-bit replication: cloning keeps the exact content and the whole structure of the original device.
- Use cases: cloning is used when it is needed to keep the original device intact for further examination or a legal affair.
- Time consuming: Cloning is usually longer in comparison to simple copying since it involves the whole detailed replication. Though it depends on various factors like the size of the storage device, the speed of the devices involved, and the method of cloning.
Imaging:
It is the process of creating a forensic image of a storage device. A forensic image is a replica copy of every bit of data that was on the source device, this including the allocated, unallocated, and the available slack space .
The image is then used for analysis and investigation, and the original evidence is left untouched. Images can’t be used as the working copies of a device. Unlike cloning, which produces working copies, forensic images are typically used for analysis and investigation purposes and are not intended for regular use as working copies.
Characteristics of Imaging:
- Integrity: Imaging ensures the integrity and authenticity of the evidence produced
- Flexibility: Forensic image replicas can be mounted as a virtual drive to create image-specific mode for analysis of data without affecting the original evidence .
- Metadata: Imaging captures metadata associated with the data, thus promoting forensic analysis.
Key Differences
- Purpose: Copying is for everyday use but not good for forensic investigations requiring data integrity. Cloning and imaging are made for forensic preservation.
- Depth of Replication: Cloning and imaging captures the entire storage device including hidden, unallocated, and deleted data whereas copying may miss crucial forensic data.
- Data Integrity: Imaging and cloning keep the integrity of the original evidence thus making them suitable for legal and forensic use. Which is a critical aspect of forensic investigations.
- Forensic Soundness: Imaging is considered the best in digital forensics due to its comprehensive and non-invasive nature.
- Cloning is generally from one hard disk to another, where as imaging creates a compressed file that contains a snapshot of the entire hard drive or a specific partitions
Conclusion
Therefore, copying, cloning, and imaging all deal with duplication of data or storage devices with significant variations, especially in digital forensic. However, for forensic investigations, imaging is the most selected approach due to the correct preservation of the evidence state for any analysis or legal use . Therefore, it is essential for forensic investigators to understand these rigorous differences to avail of real and uncontaminated digital evidence for their investigation and legal argument.
Introduction
We inhabit an era where digital connectivity, while empowering, has also unleashed a relentless tide of cyber vulnerabilities, where personal privacy is constantly threatened, and crimes like sextortion are the perfect example of the sinister side of our hyperconnected world. Social media platforms, instant messaging apps, and digital content-sharing tools have all grown rapidly, changing how people communicate with one another and making it harder to distinguish between the private and public domains. The rise of sophisticated cybercrimes that use the very tools meant to connect us is the price paid for this unparalleled convenience. Sextortion, a portmanteau of “sex’ and “extortion”, stands out among them as a particularly pernicious kind of internet exploitation. Under the threat of disclosing their private information, photos, or videos, people are forced to engage in sexual behaviours or provide intimate content. Sextortion’s psychological component is what makes it particularly harmful, it feeds on social stigma, shame, and fear, which discourage victims from reporting the crime and feed the cycle of victimisation and silence. This cybercrime targets vulnerable people from all socioeconomic backgrounds and is not limited by age, gender, or location.
The Economy of Shame: Sextortion as a Cybercrime Industry
A news report from June 03, 2025, reveals a sextortion racket busted in Delhi, where a money trail of over Rs. 5 crore was identified by different teams of the Crime branch. From synthetic financial identities to sextortion and other cyber frauds, a recipe for a sophisticated cybercrime chain was found. To believe this is an aberration is to overlook the reality that it is symptomatic of a much wider and largely uncharted criminal framework. According to the FBI’s 2024 IC3 report, “extortion (including sextortion)” has skyrocketed to 86,415 complaints with losses of $143 million reported in the United States (US) alone. This indicates that coercive image-based threats are no longer an isolated cybercrime but an everyday occurrence. Sextortion is no longer an isolated cybercrime; it has metamorphosed into a systematic, industrialised criminal enterprise. Another news report dated 19th July, 2025, where Delhi Police has detained four people suspected of participating in a sextortion scheme that targeted a resident of the Bhagwanpur Khera neighbourhood of Shahdara. The suspected people were allegedly arrested on a complaint wherein the victim was manipulated and fell prey to a dating site.
The threat is amplified by the usage of deepfake technology, which allows offenders to create obscene content that looks believable. The approach, which relies on the stigma attached to sexual imagery in conservative societies like India, is that victims frequently give in to requests out of fear of damaging their reputations. The combination of cybercrime and cutting-edge technology highlights the lopsided power that criminals possess, leaving victims defenceless and law enforcement unable to keep up.
Legal Remedies and the Evolving Battle Against Sextortion
Given the complexity of these crimes, India has recognised sextortion and similar cyber-enabled financial crimes under a number of legal frameworks. A change to recognising cyber-enabled sexual exploitation as an organised criminal business is shown by the introduction of specific provisions like Section 111 in the Bhartiya Nyaya Sanhita (BNS), 2023, which classifies organised cybercrimes including extortion and frauds which fall under its expansive interpretation, as a serious offence. Similarly, Section 318 (2) criminalises cheating with a maximum sentence of three years in prison or a fine, whereas Section 336 (2) makes digital forgery a crime with a maximum sentence with a maximum sentence of two years in prison or a fine. In addition to these regulations, cheating by personation through computer resources is punishable by the Information Technology Act, 2000, specifically Section 66D, which carries a maximum sentence of three years in prison and a maximum fine of Rs. 1 lakh. Due to issues with attribution, cross-border jurisdiction, and the discreet nature of digital evidence, enforcement is still inconsistent even with current statutory restrictions.
The government and its agencies recognise that laws achieve real impact only when backed by awareness initiatives and accessible, localised mechanisms for redressal. Several Indian states and the Department of Telecommunications launched numerous campaigns to educate the public about and safeguard their mobile communication assets against identity theft, financial fraud, and cyberscams. Initiatives like Cyber Saathi Initiative and Cyber Dost by MHA, with the goal of improving forensic and victim reporting skills.
Conclusion
At CyberPeace, we understand that the best defence against online abuse is prevention. Our goal is to provide people with the information and resources to identify, avoid and report sextortion attempts like CyberPeace Helpline and organise awareness campaigns on safe digital habits. In order to remain updated with the constantly looming danger, our research and policy advocacy also focus on developing more robust legal and technological safeguards.
To every reader: think before you share, secure your accounts, and never let shame silence you. If you or someone you know becomes a victim, report it immediately, help is available, and justice is possible. Together we can reclaim the internet as a space of trust, not terror.
References
- https://www.hindustantimes.com/india-news/delhi-police-busts-sextortion-cyberfraud-rackets-6-held-101748959601825.html
- https://timesofindia.indiatimes.com/city/delhi/delhi-police-arrests-four-for-sextortion-and-blackmail-in-shahdara/articleshow/122767656.cms
- https://cdn.ncw.gov.in/wp-content/uploads/2025/05/CyberSaheli.pdf
Introduction
China is on the verge of unveiling a new policy that will address how Artificial Intelligence (AI) influences employment. On January 27, 2026, the Ministry of Human Resources and Social Security (MOHRSS) announced it would publish a paper on the contribution of AI to the labour and employment markets. The policy will include provisions to help impacted industries, expand assistance to young workers and graduates, and come up with interdisciplinary training programmes to equip individuals with jobs in an AI-enabled economy. The authorities have stressed that AI does not kill jobs but changes them, and education will be needed to assist employees in adjusting to the changes.
This announcement reflects a more proactive policy on AI-based changes in labour, showing that China intends to sustain economic modernisation through AI, as well as social stability. It also depicts wider international issues concerning the rate of automation and the necessity of considering labour and training policy.
AI and the Changing Nature of Work
AI is transforming work content and nature in industries. AI systems enhance the productivity of various functions, including data processing, logistics, and customer service, although they alter the nature of tasks carried out by humans. Extant studies indicate that although AI can automate routine activities, new occupations that require complex thinking, management of artificial intelligence, and skills related to people, including empathy, creativity, and problem-solving, may be generated.
This is the key nuance in the policy framing of China. Authorities point out that AI does not always result in massive unemployment. Instead, it transforms jobs and necessitates workers to change to new task profiles. This perspective is in line with the recent reports of the world research organisations, which predict the effects of AI as transformational and not necessarily destructive. As an example, the World Economic Forum Future Jobs Report 2023 observes that the change in technology will introduce new jobs that were not there 10 years ago, and retraining and upskilling will be instrumental in accessing those opportunities.
Key Components of China’s Policy Response
China’s forthcoming policy is expected to focus on three main areas that address both current workforce needs and future readiness.
Support for Key Industries
The policy will offer targeted assistance to sectors where artificial intelligence is gaining pace. Industries like advanced manufacturing, high-tech services, and online logistics will also get specialised assistance to assist companies in using AI to complement human labour and not just to replace it. The Chinese government tries to balance industrial upgrading with employment by channelling resources to the growth areas.
Assistance for Youth and Graduates
The youth and the recent graduates are entering a labour market that is changing rapidly. The policy aims to increase the support services to this population by career counselling, internships, and training programmes correlated with changing employer demands. According to a study by McKinsey Global Institute, the young workforce all over the globe can face disproportionate disruption in case the prospects of training are scarce, making initial career backing imperative.
Interdisciplinary Talent Development
The Chinese strategy focuses on interdisciplinary training that blends knowledge of domains and AI literacy and digital illiteracy. This is indicative of the realisation that hybrid skills are required in the future. The Organisation for Economic Cooperation and Development suggests that workers who can make it through the technical and non-technical elements of work will stand a better chance of winning in the AI age.
These components show that China’s strategy is not simply to protect existing jobs but to help workers transition to roles that leverage AI’s strengths.
Economy, Stability and Strategic Modernisation
The policy is an attempt to control technological transition as part of wider economic planning. It is an indication that the government regards AI as a structural change rather than an external shock that can be predicted and influenced by policy.
This is in contrast to some other reactions to labour markets in other countries, where the reactionary approach has been seen as a reaction to the job losses that have already become reality. The initiative by China implies that there should be a change in the manner in which one can expect change instead of reacting to change.
Global Comparisons and Shared Challenges
Governments worldwide are testing the options to adapt to the work effects of AI. The European Union is considering the individual learning account and portable training benefits, which would assist workers to gain access to reskilling opportunities in the course of their careers. In the US, there is a concerted effort by the public-private partnerships to match the development of the workforce with technological implementation.
The strategy of China has some of these components, but it stands out due to its incorporation with national planning processes. China wants the adoption of AI to help it achieve the common good and not division by connecting the workforce policy to the overall innovation and economic purpose.
Meanwhile, the issue of balancing the supply of labour with the demand of technology is a challenge of its own to countries with older populations and relatively smaller working forces. The timing and design of policy are particularly significant in China, as there is a large labour force and continuous changes in demography.
Practical Challenges and Risks
The success of China’s emerging policy will depend on effective implementation. Several practical issues will require careful attention:
Ensuring Equitable Access to Training
The labour force in China is diversified, and it goes through technology zones in cities and other rural areas. It will be paramount to make sure that the opportunity of upskilling is extended to all workers across the spectrum to prevent the further worsening of regional inequalities. Research conducted on reskilling across the globe shows that rural and low-income groups tend to lack access to training, despite the availability of programmes.
Aligning Training with Labour Demand
The programme of upskilling should be related to the market requirements. Disconnected training is prone to resulting in the production of skills that are obsolete or not applicable in actual work settings. Experience in emerging economies indicates that the involvement of employers in the training design enhances placement success on the part of the learner.
Private Sector Participation
The policy needs to be translated into employment outcomes with the help of private companies. Incentives to make firms invest in worker training, internships, and apprenticeships will enable workers to shift to AI-augmented jobs with ease.
A Model for AI Workforce Policy
The Chinese policy can serve as an example for other countries that want to balance technological advancement and labour market security. It acknowledges the fact that the effect of AI on employment is not only a technical or an economic problem but also a social challenge. Through foregrounding training, support, and coordinated action, China aims to create a future where people are ready to change and not lose their jobs to this change.
This strategy can be agreed with the suggestions of international organisations like the World Bank and the OECD, which insist on the idea of lifelong learning and flexibility of labour markets, as well as proactive investment in human capital as the main aspects of the labour policy in the future.
Conclusion
Artificial intelligence will continue to reshape work around the world. China’s forthcoming policy, which emphasises support, training and strategic integration of AI into labour markets, reflects a proactive and holistic view of technological transition. Other countries could benefit from studying this approach, especially in terms of linking workforce development with innovation goals.
By anticipating disruption and investing in people as well as technology, policymakers can help ensure that AI becomes a driver of shared economic opportunity rather than a source of exclusion. The balance between innovation and employment will shape not only economic outcomes but also social cohesion in the years ahead.
References
