#FactCheck -Fake Viral Poster Falsely Attributes Political Endorsement of Rahul Gandhi to Sachin Tendulkar
Executive Summary
A post claiming that former Indian cricketer Sachin Tendulkar praised Congress leader Rahul Gandhi and urged people to elect him as Prime Minister is being widely circulated on social media.The viral poster falsely attributes a political statement to Sachin Tendulkar, suggesting that he has endorsed Rahul Gandhi for the post of Prime Minister. However, CyberPeace Research Wing research found the claim to be fake. Sachin Tendulkar has not made any such appeal or statement supporting Rahul Gandhi for Prime Minister.
Claim
On X (formerly Twitter), a verified user “Queen” shared a viral poster claiming:“Sachin Tendulkar has always supported education and never promoted superstition. Rahul Gandhi always predicts what Narendra Modi will do next. It is time to choose Rahul Gandhi again.”

Fact Check
To verify the claim, we first searched for any news reports, interviews, or credible references linking Sachin Tendulkar to such a political statement. However, we found no evidence in any reliable media source or public record suggesting that he made any such remark about Rahul Gandhi or the Prime Ministership. We also reviewed Sachin Tendulkar’s official social media accounts, but found no post, video, or statement endorsing any political leader in this manner.

Finally, the viral poster was analysed using the AI detection tool Hive Moderation. The analysis indicated a 96.8% probability that the poster was digitally created or manipulated, suggesting possible AI-generated or edited content.

Conclusion
CyberPeace Research Wing research found the claim to be fake. Sachin Tendulkar has not made any appeal to elect Rahul Gandhi as Prime Minister. The viral poster appears to be digitally fabricated and is being shared to spread misinformation.
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Introduction
In April 2026, Anthropic revealed Claude Mythos, an artificial intelligence application capable of finding security flaws in computer networks more effectively than human beings. The corporation claimed to have found hundreds of thousands of substantially serious vulnerabilities in established desktop operating systems and web-based browsers that have not been used for at least 20 years. This news has greatly alarmed those responsible for leading financial organisations, banks, and governments throughout the world. Nevertheless, this news demonstrates a much larger problem: we do not have enough cybersecurity professionals trained to do this kind of work. At the current estimate, there are 4.8 million cyber security professionals short of what is needed globally. There is a need to develop different kinds of workforce training programs to help prepare these professionals as we continue to see the emergence of new AI technologies.
What Is Claude Mythos ?
Anthropic created Claude Mythos as part of its Claude AI system, competing against ChatGPT and Google Gemini. In April 2026, expert testing revealed Mythos excelled at identifying problems in legacy code and suggested exploitation methods. It found a vulnerability that had existed for 27 years. Because of these advanced capabilities, Anthropic restricted access through “Project Glasswing,” giving it only to 12 major tech companies and 40 organizations managing critical software. Canadian Finance Minister François-Philippe Champagne called it an “unknown unknown.” Andrew Bailey of the Bank of England said regulators needed to examine what Mythos could mean for financial attacks. The European Union raised concerns. India’s Finance Minister Nirmala Sitharaman warned at SEBI’s Foundation Day on April 25, 2026, that cybersecurity is the single most pressing challenge facing markets today. She stated a single successful cyberattack on a major exchange or large broker could disrupt markets nationally and shake public confidence for years. Sitharaman emphasized that AI tools make attacks faster, more adaptive, and autonomous, capable of discovering system vulnerabilities and manipulating code.
The Real Problem: Discovery Versus Fixing
Mythos highlights a fundamental mismatch in cybersecurity. Finding a vulnerability does not guarantee it will be fixed. Organizations face challenges patching systems. Many use obsolete technology, and updates can break dependent components. Organizations in developing nations often lack financial resources for repairs or downtime. Critical systems like hospitals, banks, and power grids cannot go offline. Before Mythos, human hackers found vulnerabilities slowly. Now AI tools find weaknesses faster than they can be fixed, creating a dangerous gap. Ciaran Martin, former head of the UK’s National Cyber Security Centre, explained that Mythos is “a really good hacker” against unprotected systems. Organizations following basic security practices—regular updates, strong passwords, network protection, trained staff can likely defend against it. The UK AI Safety Institute concluded Mythos poses the biggest threat to poorly defended systems, noting: “We cannot say for sure whether Mythos Preview would be able to attack well-defended systems.”
The Workforce Challenge
The Mythos announcement exposes the real problem: we lack enough trained cybersecurity workers. There is a global shortage of 4.8 million workers against a current workforce of 5.5 million. In AI security specifically, 34 percent of needed skills are missing. But the harder problem is that AI is changing needed skills. Entry-level jobs monitoring security alerts are being automated. These were traditional career starting points. Young people learned basic skills and moved to advanced roles. Now these positions disappear while new AI security jobs emerge for which nobody has training. Organizations cannot hire fast enough for new AI roles because few people have these skills. This leads to a vicious cycle. With fewer entry-level positions available, there will be fewer young adults entering the job market which results in even fewer workers with this skill set; thus, the shortage of qualified applicants increases; this thereby increases organizations’ vulnerability. Without action taken immediately, this issue will continue to worsen
Way Forward
- Clarify What Skills We Need
Governments and industry must work together to define what cybersecurity workers need in an AI world. Currently, aspiring professionals study networking, software, and vulnerability finding, but AI security training barely exists. Governments should work with universities and companies to clarify needed skills: understanding what AI tools can and cannot do in security, finding and fixing AI system problems.
- Support Workers Who Lose Jobs To Automation
Workers who find themselves losing their jobs due to automation will require government support. All too often without an alternative, these skilled and trained workers will leave their profession forever. The government will need to provide funding for training of displaced employees, support for those changing careers to become cyber security professionals.
- Create Clear Rules For AI Security Tools
When companies create powerful security tools, governments must understand their capabilities and risks. Companies should be required to thoroughly test tools before release, clearly explain what tools can do and their limitations, and explain safety and misuse prevention plans. Governments should monitor actual tool usage, not simply trust voluntary compliance.
- Focus On Basic Security First
Most attacks do not need advanced AI tools. They succeed because organizations have not implemented basic security. Some never update software, train employees, use strong passwords, protect data properly, or test defenses. Governments should require organizations, especially those managing critical systems, to implement these basics.
Conclusion
Claude Mythos matters not because it is a weapon of destruction, but because it forces hard questions: Do we have enough skilled workers? Are our systems well-protected? The answer is no. We face a shortage of 4.8 million cybersecurity workers and lack AI security training. Yet this is also an opportunity. Governments can invest in training, strengthen defenses, and create clear rules for AI security tools. Governments, organizations and educational institutions must collaborate to create viable Cybersecurity career pathways. We can act through either creating panic or creating a trained and prepared workforce to meet today’s challenges. The time is now.
References
- https://www.bbc.com/news/articles/crk1py1jgzko
- https://red.anthropic.com/2026/mythos-preview/
- https://www.anthropic.com/project/glasswing
- https://www.aisi.gov.uk/blog/our-evaluation-of-claude-mythos-previews-cyber-capabilities
- https://www.bsg.ox.ac.uk/people/ciaran-martin
- https://www.isc2.org/Insights/2024/10/Cybersecurity-Workforce-INSIGHTS-October-2024
- https://decrypt.co/364141/anthropic-claude-mythos-serious-threat-overhyped-ai-security-institute
- https://www.businesstoday.in/latest/economy/story/fm-nirmala-sitharaman-wants-sebi-regulated-entities-to-remain-exceptionally-vigilant-heres-why-527437-2026-04-25
- https://www.theweek.in/news/biz-tech/2026/04/25/sebi-38th-anniversary-cybersecurity-concerns.html

Introduction
AI has penetrated most industries and telecom is no exception. According to a survey by Nvidia, enhancing customer experiences is the biggest AI opportunity for the telecom industry, with 35% of respondents identifying customer experiences as their key AI success story. Further, the study found nearly 90% of telecom companies use AI, with 48% in the piloting phase and 41% actively deploying AI. Most telecom service providers (53%) agree or strongly agree that adopting AI would provide a competitive advantage. AI in telecom is primed to be the next big thing and Google has not ignored this opportunity. It is reported that Google will soon add “AI Replies” to the phone app’s call screening feature.
How Does The ‘AI Call Screener’ Work?
With the busy lives people lead nowadays, Google has created a helpful tool to answer the challenge of responding to calls amidst busy schedules. Google Pixel smartphones are now fitted with a new feature that deploys AI-powered calling tools that can help with call screening, note-making during an important call, filtering and declining spam, and most importantly ending the frustration of being on hold.
In the official Google Phone app, users can respond to a caller through “new AI-powered smart replies”. While “contextual call screen replies” are already part of the app, this new feature allows users to not have to pick up the call themselves.
- With this new feature, Google Assistant will be able to respond to the call with a customised audio response.
- The Google Assistant, responding to the call, will ask the caller’s name and the purpose of the call. If they are calling about an appointment, for instance, Google will show the user suggested responses specific to that call, such as ‘Confirm’ or ‘Cancel appointment’.
Google will build on the call-screening feature by using a “multi-step, multi-turn conversational AI” to suggest replies more appropriate to the nature of the call. Google’s Gemini Nano AI model is set to power this new feature and enable it to handle phone calls and messages even if the phone is locked and respond even when the caller is silent.
Benefits of AI-Powered Call Screening
This AI-powered call screening feature offers multiple benefits:
- The AI feature will enhance user convenience by reducing the disruptions caused by spam calls. This will, in turn, increase productivity.
- It will increase call privacy and security by filtering high-risk calls, thereby protecting users from attempts of fraud and cyber crimes such as phishing.
- The new feature can potentially increase efficiency in business communications by screening for important calls, delegating routine inquiries and optimising customer service.
Key Policy Considerations
Adhering to transparent, ethical, and inclusive policies while anticipating regulatory changes can establish Google as a responsible innovator in AI call management. Some key considerations for AI Call Screener from a policy perspective are:
- The AI screen caller will process and transcribe sensitive voice data, therefore, the data handling policies for such need to be transparent to reassure users of regulatory compliance with various laws.
- AI has been at a crossroads in its ethical use and mitigation of bias. It will require the algorithms to be designed to avoid bias and reflect inclusivity in its understanding of language.
- The data that the screener will be using is further complicated by global and regional regulations such as data privacy regulations like the GDPR, DPDP Act, CCPA etc., for consent to record or transcribe calls while focussing on user rights and regulations.
Conclusion: A Balanced Approach to AI in Telecommunications
Google’s AI Call Screener offers a glimpse into the future of automated call management, reshaping customer service and telemarketing by streamlining interactions and reducing spam. As this technology evolves, businesses may adopt similar tools, balancing customer engagement with fewer unwanted calls. The AI-driven screening will also impact call centres, shifting roles toward complex, human-centred interactions while automation handles routine calls. They could have a potential effect on support and managerial roles. Ultimately, as AI call management grows, responsible design and transparency will be in demand to ensure a seamless, beneficial experience for all users.
References
- https://resources.nvidia.com/en-us-ai-in-telco/state-of-ai-in-telco-2024-report
- https://store.google.com/intl/en/ideas/articles/pixel-call-assist-phone-screen/
- https://www.thehindu.com/sci-tech/technology/google-working-on-ai-replies-for-call-screening-feature/article68844973.ece
- https://indianexpress.com/article/technology/artificial-intelligence/google-ai-replies-call-screening-9659612/

Introduction
In 2025, the internet is entering a new paradigm and it is hard not to witness it. The internet as we know it is rapidly changing into a treasure trove of hyper-optimised material over which vast bot armies battle to the death, thanks to the amazing advancements in artificial intelligence. All of that advancement, however, has a price, primarily in human lives. It turns out that releasing highly personalised chatbots on a populace that is already struggling with economic stagnation, terminal loneliness, and the ongoing destruction of our planet isn’t exactly a formula for improved mental health. This is the truth of 75% of the kids and teen population who have had chats with chatbot-generated fictitious characters. AI, or artificial intelligence, Chatbots are becoming more and more integrated into our daily lives, assisting us with customer service, entertainment, healthcare, and education. But as the impact of these instruments grows, accountability and moral behaviour become more important. An investigation of the internal policies of a major international tech firm last year exposed alarming gaps: AI chatbots were allowed to create content with child romantic roleplaying, racially discriminatory reasoning, and spurious medical claims. Although the firm has since amended aspects of these rules, the exposé underscores an underlying global dilemma - how can we regulate AI to maintain child safety, guard against misinformation, and adhere to ethical considerations without suppressing innovation?
The Guidelines and Their Gaps
The tech giants like Meta and Google are often reprimanded for overlooking Child Safety and the overall increase in Mental health issues in children and adolescents. According to reports, Google introduced Gemini AI kids, a kid-friendly version of its Gemini AI chatbot, which represents a major advancement in the incorporation of generative artificial intelligence (Gen-AI) into early schooling. Users under the age of thirteen can use supervised accounts on the Family Link app to access this version of Gemini AI Kids.
AI operates on the premise of data collection and analysis. To safeguard children’s personal information in the digital world, the Digital Personal Data Protection Act, 2023 (DPDP Act) introduces particular safeguards. According to Section 9, before processing the data of children, who are defined as people under the age of 18, Data Fiduciaries, entities that decide the goals and methods of processing personal data, must get verified consent from a parent or legal guardian. Furthermore, the Act expressly forbids processing activities that could endanger a child’s welfare, such as behavioural surveillance and child-targeted advertising. According to court interpretations, a child's well-being includes not just medical care but also their moral, ethical, and emotional growth.
While the DPDP Act is a big start in the right direction, there are still important lacunae in how it addresses AI and Child Safety. Age-gating systems, thorough risk rating, and limitations specific to AI-driven platforms are absent from the Act, which largely concentrates on consent and damage prevention in data protection. Furthermore, it ignores the threats to children’s emotional safety or the long-term psychological effects of interacting with generative AI models. Current safeguards are self-regulatory in nature and dispersed across several laws, such as the Bhartiya Nyaya Sanhita, 2023. These include platform disclaimers, technology-based detection of child-sexual abuse content, and measures under the IT (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021.
Child Safety and AI
- The Risks of Romantic Roleplay - Enabling chatbots to engage in romantic roleplaying with youngsters is among the most concerning discoveries. These interactions can result in grooming, psychological trauma, and relaxation to inappropriate behaviour, even if they are not explicitly sexual. Having illicit or sexual conversations with kids in cyberspace is unacceptable, according to child protection experts. However, permitting even "flirtatious" conversation could normalise risky boundaries.
- International Standards and Best Practices - The concept of "safety by design" is highly valued in child online safety guidelines from around the world, including UNICEF's Child Online Protection Guidelines and the UK's Online Safety Bill. This mandating of platforms and developers to proactively remove risks, not reactively to respond to harms, is the bare minimum standard that any AI guidelines must meet if they provide loopholes for child-directed roleplay.
Misinformation and Racism in AI Outputs
- The Disinformation Dilemma - The regulations also allowed AI to create fictional narratives with disclaimers. For example, chatbots were able to write articles promulgating false health claims or smears against public officials, as long as they were labelled as "untrue." While disclaimers might give thin legal cover, they add to the proliferation of misleading information. Indeed, misinformation tends to spread extensively because users disregard caveat labels in favour of provocative assertions.
- Ethical Lines and Discriminatory Content - It is ethically questionable to allow AI systems to generate racist arguments, even when requested. Though scholarly research into prejudice and bias may necessitate such examples, unregulated generation has the potential to normalise damaging stereotypes. Researchers warn that such practice brings platforms from being passive hosts of offensive speech to active generators of discriminatory content. It is a difference that makes a difference, as it places responsibility squarely on developers and corporations.
The Broader Governance Challenge
- Corporate Responsibility and AI Material generated by AI is not equivalent to user speech—it is a direct reflection of corporate training, policy decisions, and system engineering. This fact requires a greater level of accountability. Although companies can update guidelines following public criticism, that there were such allowances in the first place indicates a lack of strong ethical regulation.
- Regulatory Gaps Regulatory regimes for AI are currently in disarray. The EU AI Act, the OECD AI Principles, and national policies all emphasise human rights, transparency, and accountability. The few, though, specify clear guidelines for content risks such as child roleplay or hate narratives. This absence of harmonised international rules leaves companies acting in the shadows, establishing their own limits until contradicted.
An active way forward would include
- Express Child Protection Requirements: AI systems must categorically prohibit interactions with children involving flirting or romance.
- Misinformation Protections: Generative AI must not be allowed to generate knowingly false material, disclaimers being irrelevant.
- Bias Reduction: Developers need to proactively train systems against generating discriminatory accounts, not merely tag them as optional outputs.
- Independent Regulation: External audit and ethics review boards can supply transparency and accountability independent of internal company regulations.
Conclusion
The guidelines that are often contentious are more than the internal folly of just one firm; they point to a deeper systemic issue in AI regulation. The stakes rise as generative AI becomes more and more integrated into politics, healthcare, education, and social interaction. Racism, false information, and inadequate child safety measures are severe issues that require quick resolution. Corporate regulation is only one aspect of the future; other elements include multi-stakeholder participation, stronger global systems, and ethical standards. In the end, rather than just corporate interests, trust in artificial neural networks will be based on their ability to preserve the truth, protect the weak, and represent universal human values.
References
- https://www.esafety.gov.au/newsroom/blogs/ai-chatbots-and-companions-risks-to-children-and-young-people
- https://www.lakshmisri.com/insights/articles/ai-for-children/#
- https://the420.in/meta-ai-chatbot-guidelines-child-safety-racism-misinformation/
- https://www.unicef.org/documents/guidelines-industry-online-child-protection
- https://www.oecd.org/en/topics/sub-issues/ai-principles.html
- https://artificialintelligenceact.eu/