#FactCheck -AI-Generated Image Falsely Shows Kavya Maran Hugging Young Cricketer Vaibhav Suryavanshi
Executive Summary
A picture allegedly showing Sunrisers Hyderabad (SRH) owner Kavya Maran emotionally hugging young cricketer Vaibhav Suryavanshi has gone viral on social media. The image is being shared as a genuine photograph from a cricket-related event, with users claiming that Kavya Maran was seen embracing Vaibhav Suryavanshi. However, CyberPeace Research Wing research found the claim to be false. No credible news reports, official statements, or authentic photographs support the incident depicted in the viral image.
Claim
A Facebook user shared the viral image with the caption: “Kavya Maran Hug Vaibhav Suryavanshi 🥰🔥 #cricketnews #RRvsSRH” The link to the post and its screenshot are provided below.

Fact Check
During the research, we found no credible news reports, official statements, or authentic images confirming that Kavya Maran hugged Vaibhav Suryavanshi as shown in the viral picture. To further verify the image, it was analysed using AI detection tools, including Sightengine and Hive Moderation. Both tools indicated a high probability that the image was generated using Artificial Intelligence. The findings suggest that the viral photograph is not a genuine image captured at a real event but a digitally created visual.


Conclusion
Our research found that the viral image showing Kavya Maran emotionally hugging Vaibhav Suryavanshi is not authentic. The picture was generated using AI and does not depict a real incident.
Related Blogs

Executive Summary:
Amid the ongoing tensions in West Asia, a video is being widely circulated on social media with the claim that Iran has seized a US ship in the Strait of Hormuz. However, a research by the CyberPeace found that the claim is false. The video is from 2019 and is unrelated to the current situation. It actually shows Iran’s Islamic Revolutionary Guard Corps (IRGC) seizing a British-flagged tanker, Stena Impero. The ongoing conflict involving the United States, Israel and Iran since late February has raised concerns over global energy supply. The Strait of Hormuz, located between Iran and Oman, is a key route for global oil and maritime trade. Rising tensions in the region have impacted this route, although Iran has stated that it has not been completely closed.
Claim:
Users on X (formerly Twitter) are sharing the video as breaking news, claiming that Iran has captured a US ship in the Strait of Hormuz. The posts suggest that the move is a direct warning to the United States.

Fact Check:
To verify the claim, we extracted keyframes from the viral video and conducted a reverse image search. This led us to the same video posted on the X handle of Iran’s Press TV on July 20, 2019.
Link:
- https://x.com/PressTV/status/1152597789362262016?s=20
- https://x.com/PressTV/status/1152597789362262016?s=20

The caption of the post stated that the footage showed the moment when IRGC forces seized the British oil tanker Stena Impero in the Strait of Hormuz. Further, we found a July 2019 report by Al Jazeera that included visuals matching the viral video. According to the report, Iran’s IRGC had intercepted the British-flagged tanker on July 19, 2019, after which the footage was released.
https://www.aljazeera.com/news/2019/7/20/iran-releases-video-showing-capture-of-british-oil-tanker

Conclusion:
The viral claim is misleading. The video is not recent and does not show Iran capturing a US ship. It is from 2019 and depicts the seizure of the British tanker Stena Impero by Iran’s IRGC.

Introduction
Due to the rapid growth of high-capability AI systems around the world, growing concerns regarding safety, accountability, and governance have arisen throughout the world; thus, California has responded by passing the Transparency in Frontier Artificial Intelligence Act (TFAIA), the first state statute focused on "frontier" (highly capable) AI models. This statute is unique in that it does not only target harms caused by AI models in the form of consumer protection as compared to the majority of state statutes; rather, this statute addresses the catastrophic and systemic risks to society associated with large-scale AI systems. As California is a global technology leader, the TFAIA is positioned to have a significant impact on both domestic regulation and the evolution of international legal frameworks for AI technology (and as such has the potential to influence corporate compliance practices and the establishment of global norms related to the use of AI).
Understanding the Transparency in Frontier Artificial Intelligence Act
The Transparency in Frontier Artificial Intelligence Act provides a specific regulatory process for companies that create sophisticated AI systems with societal, economic, or national security implications. Covered developers are required to publish an extensive safety and transparency policy that details how they navigate risk throughout the artificial intelligence lifecycle. The act requires developers to notify the government of any significant incidents or failures with their deployed frontier models on a timely basis.
A significant aspect of the TFAIA is that it establishes the concept of "process transparency", which does not explicitly control how AI developers create their models, but rather holds them accountable for their internal safety governance by mandating that they develop Documented safety frameworks that outline risk assessment, mitigation, and monitoring processes. The act allows developers to protect their trade secrets, patents, and national defense concerns by providing them with limited opportunities for exemption and/or redaction of their documents so that they can maintain a balance between data openness and safeguarding sensitive information..
Extraterritorial Impact on Global AI Developers
While the Act is a state law, its implementation has far-reaching effects. Many of the largest AI companies have facilities, research labs or customers in California. Therefore, to be compliant with the TFAIA, these companies are required to do so commercially. The ability to develop a unified compliance model across regions enables companies to avoid developing duplicate compliance models.
This same pattern has occurred in other regulatory areas, like data protection regulations; where a region's regulations effectively became global compliance benchmarks for that regulatory area. The TFAIA could similarly serve as a global standard for transparency in frontier AI and shape how companies build their governance structure globally even if they don't have explicit regulations in the regions where they operate.
Influence on International AI Regulatory Models
The TFAIA offers a unique perspective on global discussions about regulating AI. In contrast to other legislation which defines different levels of risk depending on the type of AI, the TFAIA targets specifically high-impact or emerging technologies. Other nations may see value in this model of tiered regulations based on capability and apply it for their own regulation of AI, with the strictest obligations placed on those with the most critical potential harm.
The TFAIA may serve as a guide for international public policy makers by showing how they can reference existing standards and best practices in developing regulations, thus improving interoperability and potentially lessening regulatory barriers to cross-border AI innovations.
Corporate Governance, Compliance Costs, and Competition
From an industry perspective, the Act revolutionizes the way companies govern themselves. Developers are now required to create thorough risk assessments, red-teaming exercises, incident response protocols, and have board oversight for AI safety and regulation. The number of people involved in this process increases accountability but at the same time the increases will create a burden of cost for all involved.
The burden of compliance will be easier for large tech companies than for smaller or start-ups, and thus large tech companies may solidify their position of dominance over the development of frontier AI. Smaller and newer developers may be blocked from entering the market unless some form of proportional or scaled compliance mechanism for where they operate emerges. These developments certainly raise issues surrounding innovation policy and competition law at a global scale that will need to be addressed by regulators in conjunction with AI safety concerns.
Transparency, Public Trust, and Accountability
The TFAIA bolsters the capability of citizens, researchers and journalists to oversee the development and the use of artificial intelligence (AI) through its requirement for public disclosure of the safety framework of AI systems. The disclosures will allow citizens, researchers and journalists to critically evaluate corporate claims of responsible AI development. Over time, this evaluation could increase trust in publically regulated AI systems and would expose businesses that exhibit a poor risk management process.
However, how useful this transparency is depends on the quality and comparability of the information being disclosed. Many current disclosures are either too vague or too complex, thus limiting the ability to conduct meaningful oversight. There should be a push for clearer guidance and/or the establishment of standardised disclosure forms for the purposes of public accountability (i.e., citizens) and uniformity between countries.
Conclusion
The Transparency in Frontier Artificial Intelligence Act is a transformative development in the regulation of Artificial Intelligence Technology, specifically, a whole new risk profile of this new generation of AI / (Advanced High-Powered) Technologies such as Autonomous Vehicles. This new California law will create global impact because it Be will change how technology companies operate, create regulatory frameworks and develop standards to govern/oversee the use of Autonomous Vehicles. The Act creates a “transparent” means for regulating (or governing) Autonomous Vehicles as opposed to relying solely on “technical” means for these systems. As other regions experience similar challenges that US Government is facing with respect to this new generation of AI (written laws), California's approach will likely be used as an example for how AI laws are written in the future and develop a more unified and responsible international AI regulatory framework.
References
- https://www.whitecase.com/insight-alert/california-enacts-landmark-ai-transparency-law-transparency-frontier-artificial
- https://www.gov.ca.gov/2025/09/29/governor-newsom-signs-sb-53-advancing-californias-world-leading-artificial-intelligence-industry/
- https://www.mofo.com/resources/insights/251001-california-enacts-ai-safety-transparency-regulation-tfaia-sb-53
- https://www.dlapiper.com/en/insights/publications/2025/10/california-law-mandates-increased-developer-transparency-for-large-ai-models

For years, Malaysia governed artificial intelligence the way most countries did before they had to, with guidelines nobody could be fined for ignoring. The National Guidelines on AI Governance and Ethics, published by Malaysia's Ministry of Science, Technology and Innovation back in September 2024, told developers and deployers what "responsible AI" should look like. It just never made anyone legally responsible for anything.
Malaysia is now attempting to change that. On 10 July 2026, the National AI Office (NAIO), operating under the Ministry of Digital, released a Public Consultation Paper for what would become Malaysia's first horizontal AI statute: a single law covering AI across every sector, rather than a patchwork of guidelines, data protection rules, and whatever a particular regulator happens to think about algorithms this year. Written submissions closed on 31 July 2026, and the government has said it wants the Bill tabled and completed before the year is out. That is an aggressive timeline for a law this broad, and it tells you something about how urgently Putrajaya wants this on the books.
Why "horizontal" matters here
Most of the world's AI rules so far have been vertical. A banking regulator handles AI in banking, a health authority handles AI in diagnostics, and everything in between is grey space. Malaysia's own consultation paper is refreshingly candid about the problem this creates: it warns of "differing standards and approaches" building up across sectors, and notes that existing tools only really respond after something has already gone wrong.
The Bill tries to fix that by sitting above the sector specific rules rather than replacing them. It rests on three pillars.
- First, a Central AI Authority, which would still lean on existing regulators (think Bank Negara Malaysia for financial services or the Securities Commission for capital markets) through what the paper calls "Sectoral Leads."
- Second, a set of baseline principles written into law rather than left as suggestions: human dignity, transparency and explainability, accountability, safety and security, and data governance.
- Third, a structure that scales obligations to how dangerous a given AI system actually is, instead of regulating a spam filter and a hospital triage algorithm with the same rulebook.
The mechanics: three tiers, two roles, one authority
The risk framework itself splits into three tiers: Tier 1 for unacceptable risk, Tier 2 for high risk, and Tier 3 for low risk, with obligations scaling up as the potential for harm does. Obligations fall on two kinds of actors: Developers, who materially shape what a system can do, and Deployers, who actually run it in the real world. A single company can be both. This split deliberately echoes the controller and processor distinction from Malaysia's Personal Data Protection Act, though not perfectly, a point several legal commentators have already flagged as a source of future confusion, since a Deployer processing personal data will usually be a controller under the PDPA, while a Developer offering a hosted model might only be a processor.
The Central AI Authority itself is proposed to run three functions: an AI Safety function that maintains the risk framework and oversees testing and incident reporting; an Investigation and Enforcement function with power to demand fact finding and issue directions after incidents; and an AI Enablement function that produces guidance, templates, training, and runs the AI Sandbox, a controlled testing environment meant to let companies experiment before the full weight of compliance lands on them. For smaller businesses without in house compliance teams, that enablement mandate may end up mattering more day to day than the enforcement powers do.
Two more features round out the design. An incident reporting mechanism would require Developers and Deployers to flag not just failures but near misses and unexpected effects, with the public also able to lodge complaints directly. And the Bill's territorial reach is broad by design: it would apply to any AI system designed, developed, or used in Malaysia, regardless of where the underlying infrastructure sits, carving out exemptions only for personal use and national security matters.
How this stacks up against the EU AI Act
Malaysia's drafters have clearly been reading Brussels' homework, and it shows in the structure: a tiered risk model, a central authority, mandatory obligations tied to risk level. But the resemblance is more skeletal than skin deep once you look at the details.
The EU AI Act is a fully codified regulation running to hundreds of pages, with named prohibited practices spelled out in an annex, specific high risk categories listed by sector, and detailed conformity assessment procedures before a system ever reaches the market. Malaysia's Bill, at consultation stage, is still working from principles and a harm list rather than an exhaustive catalogue of prohibited or high risk use cases, closer in spirit to a framework law that leaves the granular detail to subsidiary guidelines and Sectoral Leads. That's partly a function of timeline: the EU spent roughly three years negotiating its Act before adoption, while Malaysia is trying to move from consultation paper to finished statute inside a single year.
Enforcement philosophy differs too. Brussels built the AI Act around compliance that happens before deployment: conformity assessments, technical documentation, and sign off procedures similar to product safety certification, particularly for high risk systems. Malaysia's design leans more on an enablement first posture, with sandboxes, guidance, and incident reporting sitting alongside enforcement powers rather than in front of them, at least as currently framed. Whether that survives contact with the final legislative text is an open question. The consultation drew real pushback from law firms wanting harsher penalty ranges and clearer thresholds, so the version tabled in Parliament may look tougher than the one made public in July.
There's also a jurisdictional difference worth flagging. The EU AI Act has genuine extraterritorial teeth backed by the largest single market in the developed world, which is why companies far outside Europe still comply with it. Malaysia's Bill claims similarly broad reach on paper, covering any system used in Malaysia regardless of where it's hosted, but the practical leverage to enforce that against a foreign Developer is a different question entirely, and one the Edwin Lee and Partners (Law firm based in malaysia) submission specifically raised as a gap needing an international cooperation mechanism.
India and AI Regulation
India has spent the past year deliberately walking in the evolving direction. Through MeitY's India AI Governance Guidelines, released in November 2025 ahead of the India AI Impact Summit, explicitly reject a standalone AI statute in favour of what officials have repeatedly called a "light touch" model: seven guiding principles, trust, people first, innovation, fairness, accountability, transparency, and safety, layered on top of existing law rather than a new one. The Digital Personal Data Protection Act, 2023 and the IT Act, 2000 with amendment rules, do most of the actual legal work, with sector regulators like the RBI and SEBI handling the specifics for their own industries.
The contrast with Malaysia is almost a case study in two governance philosophies. Where Malaysia is building a central authority with enforcement teeth from day one, India has so far preferred advisory bodies, an AI Governance Group and a proposed AI Safety Institute, that shape norms without imposing binding cross sectoral obligations.
Where Malaysia's Bill would be justiciable law with penalties attached, India's framework is closer to a philosophy statement with sandboxes and a national incident database bolted on. That is not a weaker approach so much as a different, and arguably shrewd, bet. India is the world's largest testing ground for AI adoption at scale, from welfare delivery to vernacular language tools, and a heavy compliance regime risks slowing exactly the kind of grassroots experimentation the government is trying to encourage. Betting on existing law and institutional judgment, at least for now, keeps that door open, and it has let India move fast without waiting for a perfect law first.
That said, India's position has been visibly shifting. In July 2026, MeitY Secretary S. Krishnan signalled the government is now exploring dedicated AI legislation after all, a notable departure from the "no early regulation" stance the ministry had held in 2023, and this is likely accelerated by growing concern over deepfakes and synthetic media, which already prompted binding traceability and labelling obligations under amended intermediary rules earlier this year.
The stakes for the next few months
None of this is finished. Malaysia's Bill is still a consultation paper, not enacted law, and the gap between what NAIO proposed in July and what Parliament eventually passes could be significant. Several submissions are already pushing for a wider harm list, sharper enforcement thresholds, and clearer rules for foreign Developers who never set foot in Kuala Lumpur. But the direction is set. Malaysia has decided AI governance can no longer run on goodwill and voluntary guidelines, and it now attempts to write enforceable AI law on a real deadline rather than settling for guidelines. However, the final Bill lives up to that ambition, or gets watered down in the process, is something only the next few months will show.
References
- Ministry of Digital. "Kementerian Digital Mulakan Libat Urus Cadangan Rang Undang Undang Tadbir Urus Kecerdasan Buatan (AI)." 10 July 2026. https://www.digital.gov.my/en-GB/siaran/Kementerian-Digital-Mulakan-Libat-Urus-Cadangan-Rang-Undang-Undang-Tadbir-Urus-Kecerdasan-Buatan-(AI)
- Digital Watch Observatory. "Malaysia launches consultations on AI Governance Bill." July 2026. https://dig.watch/updates/malaysia-ai-governance-bill-consultation
- Baker McKenzie, Wong and Partners. "Malaysia: Public Consultation on the AI Governance Bill." July 2026. https://www.bakermckenzie.com/en/insight/publications/2026/07/malaysia-public-consultation-on-the-ai-governance-bill
- Digital Policy Alert. "Testing requirements in AI Governance Bill" and related entries on the National AI Office consultation. https://digitalpolicyalert.org
- Rahmat Lim and Partners. "National AI Office issues public consultation paper on proposed Artificial Intelligence (AI) Governance Bill." https://www.rahmatlim.com/perspectives/articles/33264/mykh-national-ai-office-issues-public-consultation-paper-on-proposed-artificial-intelligence-ai-governance-bill
- Edwin Lee and Partners. "Malaysia's AI Governance Bill: Our Submission to the Consultation." https://lpplaw.my/ai-governance-malaysia/
- Kiizen. "Overview of the Proposed Malaysia's AI Governance Bill." https://www.kiizen.com.my/proposed-malaysias-ai-governance-bill/
- Zicelegal. "Consultation Alert: Public Consultation on Malaysia's AI Governance Bill." https://www.ziclegal.com/resources/consultation-alert-public-consultation-on-malaysias-ai-governance-bill
- Welcome.AI. "Malaysia's AI Governance Bill Expands Regulation and Accountability for Businesses." July 2026. https://www.welcome.ai/content/malaysias-ai-governance-bill-expands-regulation-and-accountability-for-businesses
- Regulations.ai. "Malaysia AI Regulation Overview." https://regulations.ai/regulations/RAI-MY-NA-SUMMARY-2026
- w.media. "Malaysia to enact AI law." https://w.media/malaysia-to-enact-ai-law/
- VisionIAS. "India's New AI Governance Guidelines Push Hands Off Approach." November 2025. https://visionias.in/blog/current-affairs/indias-new-ai-governance-guidelines-push-hands-off-approach
- EY India. "AI governance guidelines: A bet on innovation." https://www.ey.com/en_in/insights/ai/ai-governance-guidelines-a-bet-on-innovation
- TechnoSports. "Airegulation: Indian Government Finalizes AI Regulation." May 2026. https://technosports.co.in/airegulation-india-framework/
- The AI Track. "India AI Governance Guidelines Released for 2025 to 26." https://theaitrack.com/india-ai-governance-guidelines-2025/
- Lexology, contributed by a law firm. "India's AI Governance Model: MeitY's AI Guidelines and The Evolving Copyright Landscape." March 2026. https://www.lexology.com/library/detail.aspx?g=ffc0c58c-3727-4472-9914-5fa6a33ffffd
- Srishti IAS. "India's First AI Governance Framework 2026: Principles, Oversight, and Inclusive Growth Strategy." February 2026. https://srishtiias.com/india-first-ai-governance-framework-ahead-of-impact-summit-2026/
- Whalesbook. "India Plans Dedicated AI Law, Shifting From Light Touch Approach." July 2026. https://www.whalesbook.com/news/English/other/India-Plans-Dedicated-AI-Law-Shifting-From-Light-Touch-Approach/6a4811c9c7db2a6cf1650f24
- Saikrishna and Associates. "Decoding the India AI Governance Guidelines." November 2025. https://www.saikrishnaassociates.com/decoding-the-india-ai-governance-guidelines/
- News on Air. "MeitY Unveils India AI Governance Guidelines to Promote Safe and Responsible AI Adoption." 5 November 2025. https://www.newsonair.gov.in/meity-unveils-india-ai-governance-guidelines-to-promote-safe-and-responsible-ai-adoption
Contributors
- Maj. Vineet Kumar, Founder & Global President, CyberPeace
- Mr. Neeraj Soni, Senior Research Analyst, Policy & Advocacy, CyberPeace