#FactCheck - Virat Kohli's Ganesh Chaturthi Video Falsely Linked to Ram Mandir Inauguration

Disclaimer:

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This report is the collaborative outcome of insights derived from the CyberPeace Helpline’s operational statistics and the CyberPeace Research Team, covering the monthly helpline case trends of May 2025, the report identifies recurring trends, operational challenges, and strategic opportunities. The objective is to foster research-driven solutions that enhance the overall efficacy of the helpline. 

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Executive Summary:

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This report summarizes the cybercrime cases reported in May, offering insights into case types, gender distribution, resolution status, and geographic trends.

As per our analysis, out of various Cyber Frauds Financial Fraud was the most reported issue, making up 43% of cases, followed by Cyberbullying (26%) and Impersonation (14%). Less frequent but serious issues included Sexual Harassment, Sextortion, Hacking, Data Tampering, and Cyber Defamation, each accounting for 3–6%, highlighting a mix of financial and behavioral threats.The gender distribution was fairly balanced, with 51% male and 49% female respondents. While both genders were affected by major crimes like financial fraud and cyber bullying, some categories—such as sexual harassment—reflected more gender-specific risks, indicating the need for gender-responsive policies and support.

Regarding case status, 60% remain under follow-up while 40% have been resolved, reflecting strong case-handling efforts by the team.

The location-wise data shows higher case concentrations in Uttar Pradesh, Andhra Pradesh, Karnataka, and West Bengal, with significant reports also from Delhi, Telangana, Maharashtra, and Odisha. Reports from the northeastern and eastern states confirm the nationwide spread of cyber incidents.In conclusion, the findings point to a growing need for enhanced cybersecurity awareness, preventive strategies, and robust digital safeguards to address the evolving cyber threat landscape across India.

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Cases Received in May:

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As per the given dataset, the following types of cases were reported to our team during the month of May:

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• 💰 Financial Fraud – 43%
• 💬 Cyber Bullying – 26%
• 🕵️‍♂️ Impersonation – 14%
• 🚫 Sexual Harassment – 6%
• 📸 Sextortion – 3%
• 💻 Hacking – 3%
• 📝 Data Tampering – 3%
• 🗣️ Cyber Defamation – 3%

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The chart illustrates various cybercrime categories and their occurrence rates. Financial Fraud emerges as the most common, accounting for 43% of cases, highlighting the critical need for stronger digital financial security. This is followed by Cyber Bullying at 26%, reflecting growing concerns around online harassment, especially among youth. Impersonation ranks third with 14%, involving identity misuse for deceitful purposes. Less frequent but still serious crimes such as Sexual Harassment (6%), Sextortion, Hacking, Data Tampering, and Cyber Defamation (each 3%) also pose significant risks to users’ privacy and safety. Overall, the data underscores the need for improved cybersecurity awareness, legal safeguards, and preventive measures to address both financial and behavioral threats in the digital space.

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Gender-Wise Distribution:

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• 👨 Male – 51%
• 👩 Female – 49%

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The chart illustrates the distribution of respondents by gender. The data shows that Male participants make up 51% of the total, while Female participants account for 49%. This indicates a fairly balanced representation of both genders, with a slight majority of male respondents.

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Gender-Wise Case Distribution:

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1. The chart presents a gender-wise distribution of various cybercrime cases, offering a comparative view of how different types of cyber incidents affect males and females.
2. It highlights that both genders are significantly impacted by cybercrimes such as financial fraud and cyber bullying, indicating a widespread risk across the board.
3. Certain categories, including sexual harassment, cyber defamation, and hacking, show more gender-specific patterns of victimization, pointing to differing vulnerabilities.
4. The data suggests the need for gender-sensitive policies and preventive measures to effectively address the unique risks faced by males and females in the digital space.
5. These insights can inform the design of tailored awareness programs, support services, and intervention strategies aimed at improving cybersecurity for all individuals.

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‍Major Location Wise Distribution:

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The map visualization displays location-wise distribution of reported cases across India. The cases reflect the cyber-related incidents or cases mapped geographically.

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The map highlights the regional distribution of cybercrime cases across Indian states, with a higher concentration in Uttar Pradesh, Andhra Pradesh, Karnataka, and West Bengal. States like Delhi, Telangana, Maharashtra, and Odisha also show notable activity, indicating widespread cyber threats. Regions including Assam, Tripura, Bihar, Jharkhand, and Jammu & Kashmir further reflect the pan-India spread of such incidents. This distribution stresses the need for targeted cybersecurity awareness and stronger digital safeguards nationwide

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CyberPeace Advisory:

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• Use Strong and Unique Passwords: Create complex passwords using a mix of letters, numbers, and symbols. Avoid reusing the same password across multiple platforms.
  
• Enable Multi-Factor Authentication (MFA): Add an extra layer of security by using a second verification step like an OTP or authentication app.
  
• Keep Software Updated: Regularly update your operating system, apps, and security tools to protect against known vulnerabilities.
  
• Install Trusted Security Software: Use reliable antivirus and anti-malware programs to detect and block threats.
  
• Limit Information Sharing: Be cautious about sharing personal or sensitive details, especially on social media or public platforms.
  
• Secure Your Network: Protect your Wi-Fi with a strong password and encryption. Avoid accessing confidential information on public networks.
  
• Back Up Important Data: Regularly save copies of important files in secure storage to prevent data loss in case of an attack.
  
• Stay Informed with Cybersecurity Training: Learn how to identify scams, phishing attempts, and other online threats through regular awareness sessions.
  
• Control Access to Data: Give access to sensitive information only to those who need it, based on their job roles.
• ‍Monitor and Respond to Threats: Continuously monitor systems for unusual activity and have a clear response plan for handling security incidents.

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• CyberPeace Helpline mail ID:  helpline@cyberpeace.net
• CyberPeace Helpline Number:  9570000066
• Central Government Helpline: https://cybercrime.gov.in/
• Central Government Helpline Number: 1930

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Conclusion

The cybercrime cases reported in May highlight a diverse and evolving threat landscape across India. Financial fraud, cyber bullying, and impersonation are the most prevalent, affecting both genders almost equally, though some crimes like sexual harassment call for targeted gender-sensitive measures. With 60% of cases still under follow-up, the team’s efforts in investigation and resolution remain strong. Geographically, cyber incidents are widespread, with higher concentrations in several key states, demonstrating that no region is immune. These findings underscore the urgent need to enhance cybersecurity awareness, strengthen preventive strategies, and build robust digital safeguards. Proactive and inclusive approaches are essential to protect individuals and communities and to address the growing challenges posed by cybercrime nationwide.

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Introduction

Misinformation is a major issue in the AI age, exacerbated by the broad adoption of AI technologies. The misuse of deepfakes, bots, and content-generating algorithms have made it simpler for bad actors to propagate misinformation on a large scale. These technologies are capable of creating manipulative audio/video content, propagate political propaganda, defame individuals, or incite societal unrest. AI-powered bots may flood internet platforms with false information, swaying public opinion in subtle ways. The spread of misinformation endangers democracy, public health, and social order. It has the potential to affect voter sentiments, erode faith in the election process, and even spark violence. Addressing misinformation includes expanding digital literacy, strengthening platform detection capabilities, incorporating regulatory checks, and removing incorrect information.

AI's Role in Misinformation Creation

AI's growth in its capabilities to generate content have grown exponentially in recent years. Legitimate uses or purposes of AI many-a-times take a backseat and result in the exploitation of content that already exists on the internet. One of the main examples of misinformation flooding the internet is when AI-powered bots flood social media platforms with fake news at a scale and speed that makes it impossible for humans to track and figure out whether the same is true or false.

The netizens in India are greatly influenced by viral content on social media. AI-generated misinformation can have particularly negative consequences. Being literate in the traditional sense of the word does not automatically guarantee one the ability to parse through the nuances of social media content authenticity and impact. Literacy, be it social media literacy or internet literacy, is under attack and one of the main contributors to this is the rampant rise of AI-generated misinformation. Some of the most common examples of misinformation that can be found are related to elections, public health, and communal issues. These issues have one common factor that connects them, which is that they evoke strong emotions in people and as such can go viral very quickly and influence social behaviour, to the extent that they may lead to social unrest, political instability and even violence. Such developments lead to public mistrust in the authorities and institutions, which is dangerous in any economy, but even more so in a country like India which is home to a very large population comprising a diverse range of identity groups. 

Misinformation and Gen AI

Generative AI (GAI) is a powerful tool that allows individuals to create massive amounts of realistic-seeming content, including imitating real people's voices and creating photos and videos that are indistinguishable from reality. Advanced deepfake technology blurs the line between authentic and fake. However, when used smartly, GAI is also capable of providing a greater number of content consumers with trustworthy information, counteracting misinformation. 

Generative AI (GAI) is a technology that has entered the realm of autonomous content production and language creation, which is linked to the issue of misinformation. It is often difficult to determine if content originates from humans or machines and if we can trust what we read, see, or hear. This has led to media users becoming more confused about their relationship with media platforms and content and highlighted the need for a change in traditional journalistic principles.

We have seen a number of different examples of GAI in action in recent times, from fully AI-generated fake news websites to fake Joe Biden robocalls telling the Democrats in the U.S. not to vote. The consequences of such content and the impact it could have on life as we know it are almost too vast to even comprehend at present. If our ability to identify reality is quickly fading, how will we make critical decisions or navigate the digital landscape safely? As such, the safe and ethical use and applications of this technology needs to be a top global priority. 

Challenges for Policymakers

AI's ability to generate anonymous content makes it difficult to hold perpetrators accountable due to the massive amount of data generated. The decentralised nature of the internet further complicates regulation efforts, as misinformation can spread across multiple platforms and jurisdictions. Balancing the need to protect the freedom of speech and expression with the need to combat misinformation is a challenge. Over-regulation could stifle legitimate discourse, while under-regulation could allow misinformation to propagate unchecked. India's multilingual population adds more layers to already-complex issue, as AI-generated misinformation is tailored to different languages and cultural contexts, making it harder to detect and counter. Therefore, developing strategies catering to the multilingual population is necessary.

Potential Solutions

To effectively combat AI-generated misinformation in India, an approach that is multi-faceted and multi-dimensional is essential. Some potential solutions are as follows:

• Developing a framework that is specific in its application to address AI-generated content. It should include stricter penalties for the originator and spreader and dissemination of fake content in proportionality to its consequences. The framework should establish clear and concise guidelines for social media platforms to ensure that proactive measures are taken to detect and remove AI-generated misinformation.
• Investing in tools that are driven by AI for customised detection and flagging of misinformation in real time. This can help in identifying deepfakes, manipulated images, and other forms of AI-generated content. 

• The primary aim should be to encourage different collaborations between tech companies, cyber security orgnisations, academic institutions and government agencies to develop solutions for combating misinformation. 
• Digital literacy programs will empower individuals by training them to evaluate online content. Educational programs in schools and communities teach critical thinking and media literacy skills, enabling individuals to better discern between real and fake content.

Conclusion

AI-generated misinformation presents a significant threat to India, and it is safe to say that the risks posed are at scale with the rapid rate at which the nation is developing technologically. As the country moves towards greater digital literacy and unprecedented mobile technology adoption, one must be cognizant of the fact that even a single piece of misinformation can quickly and deeply reach and influence a large portion of the population. Indian policymakers need to rise to the challenge of AI-generated misinformation and counteract it by developing comprehensive strategies that not only focus on regulation and technological innovation but also encourage public education. AI technologies are misused by bad actors to create hyper-realistic fake content including deepfakes and fabricated news stories, which can be extremely hard to distinguish from the truth. The battle against misinformation is complex and ongoing, but by developing and deploying the right policies, tools, digital defense frameworks and other mechanisms, we can navigate these challenges and safeguard the online information landscape.

References:

• https://economictimes.indiatimes.com/news/how-to/how-ai-powered-tools-deepfakes-pose-a-misinformation-challenge-for-internet-users/articleshow/98770592.cms?from=mdr 
• https://www.dw.com/en/india-ai-driven-political-messaging-raises-ethical-dilemma/a-69172400 
• https://pure.rug.nl/ws/portalfiles/portal/975865684/proceedings.pdf#page=62 

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Introduction

Web applications are essential in various sectors, including online shopping, social networks, banking, and healthcare systems. However, they also pose numerous security threats, including Cross-Site Scripting (XSS), a client-side code injection vulnerability. XSS attacks exploit the trust relationship between users and websites, allowing them to change web content, steal private information, hijack sessions, and gain full control of user accounts without breaking into the core server. This vulnerability is part of the OWASP Top 10 Web Application Security Risks.

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What is Cross-Site Scripting (XSS)?

An XSS attack occurs when an attacker injects client-side scripts into web pages viewed by other users. When users visit the affected pages, their browsers naively execute the inserted scripts. The exploit takes advantage of web applications that allow users to submit content without properly sanitising inputs or encoding outputs. These scripts can cause a wide range of damage, including but not limited to stealing session cookies for session hijacking, redirecting users to malicious sites, logging keystrokes to capture credentials, and altering the DOM to display fake or phishing content.

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How Does XSS Work?

1. Injection: A malicious user submits code through a website input, like a comment or form.
2. Execution: The submitted code runs automatically in the browsers of other users who view the page.
3. Exploitation:The attacker can steal session information, capture credentials, redirect users, or modify the page content.

The fundamental cause behind the XSS vulnerabilities is the application of:

• Accepting trusted input from the users.  
• After users' input, web pages have the strings embedded without any sanitisation.  
• Not abiding by security policies like Content Security Policy (CSP).  

With such vulnerabilities, attackers can generate malicious payloads like:  <script>alert('XSS');</script>  

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This code might seem simple, but its execution provides the attacker with the possibility to do the following:  

• Copy session tokens through hidden HTTP requests.  
• From attacker-controlled domains, load attacker scripts.  
• Change the DOM structure to show fake login forms for phishing.

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Types of XSS Attacks: XSS (Cross-Site Scripting) attacks can occur in three main variations: 

1. Stored XSS: This type of attack occurs when an attacker injects an administered payload into the database or a message board. The script then runs whenever a user visits the affected board.
2. Reflected XSS: In this attack, the danger lies in a parameter of the URL. Its social engineering techniques are attacks, in which it requires tricking people to click on a specially designed link. For example:
3. DOM-Based XSS: This technique injects anything harmful without the need for server-side scripts, in contrast to other approaches. It targets JavaScript client-side scripts such as `document.write` and `innerHTML`. Without carrying out any safety checks, these scripts will alter the page's look (DOM stands for Document Object Model). If the hash is given a malicious string, it is run directly within the browser.

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What Makes XSS a Threat?  

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A Cross-Site Scripting attack is only a primary attack vector, and can lead to significant damage that includes the following: 

• Statement Hijacking. This uses scripts to steal cookies, which are then used to pose as authorized users.  
• Theft of Credentials. Users’ passwords and usernames are wrenched from keystroke trackers.  
• Phishing. Users are prompted with deceitful login forms that are used to capture sensitive details.  
• Website Vandalism. Modified website material lowers the esteem of the brand.  
• Monetary and Legal Consequences. There are compounding effects to GDPR and DPDP Act compliance in case of Data breaches, which incur penalties and fines.  ‍

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Incidents in the Real World  

In 2021, an XSS Stored attack occurred on a famous e-commerce platform eBay, through their product review system. The malicious JavaScript code was set to trigger every time an infected product page was accessed by customers. This caused a lot of problems, including account takeovers, unauthorised purchases, and damage to the company’s reputation. This example further worsens the fact that even reputed platforms can be targeted by XSS attacks.

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How to Prevent XSS?

Addressing XSS vulnerabilities demands attention to detail and coordinated efforts across functions, as illustrated in the steps below:

 Input Validation and Output Encoding:

• Ensure input validation is in place on the client and server.
• Perform output encoding relative to context: HTML: <, >, &.
• JavaScript: Escape quotes and slashes

Content Security Policy (CSP): CSP allows scripts to be executed only from the verified sources, which helps diminish the odds of harmful scripts running on your website. For example, the Header in the code could look to some degree like this: Content-Security-Policy: script-src 'self';

Unsafe APIs should be dodged: Avoid the use of document.write(), innerHTML, and eval(), and make sure to use:

• TextContent for inserting text.
• CreateElement() and other DOM creation methods for structured content.

Secure Cookies: Apply the HttpOnly and Secure cookie flags to block JavaScript access. 

Framework Protections: Use the protective features in frameworks such as:

• React, which escapes data embedded in JSX automatically.
• Angular, which uses context-aware sanitisation.

Periodic Security Assessment:

• Use DAST tools to test the security posture of an application.
• Perform thorough penetration testing and security-oriented code reviews.

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‍Best Practices for Developers: Assume a Secure Development Lifecycle (SDLC) integrating XSS stoppage at each point.

• Educate developers on OWASP secure coding guidelines.
• Automate scanning for vulnerabilities in CI/CD pipelines.

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‍Conclusion:

To reduce the potential danger of XSS, both developers and companies must be diligent in their safety initiatives, ranging from using Content Security Policies (CSP) to verifying user input. Web applications can shield consumers and the company from the subtle but long-lasting threat of Cross-Site Scripting if security controls are implemented during the web application development stage and regular vulnerability scans are conducted.

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References

• https://owasp.org/www-community/attacks/xss/
• https://www.paloaltonetworks.com/cyberpedia/xss-cross-site-scripting
• https://developer.mozilla.org/en-US/docs/Glossary/Cross-site_scripting
• https://www.cloudflare.com/learning/security/threats/cross-site-scripting/

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