#FactCheck - Viral Photo of Dilapidated Bridge Misattributed to Kerala, Originally from Bangladesh
Executive Summary:
A viral photo on social media claims to show a ruined bridge in Kerala, India. But, a reality check shows that the bridge is in Amtali, Barguna district, Bangladesh. The reverse image search of this picture led to a Bengali news article detailing the bridge's critical condition. This bridge was built-in 2002 to 2006 over Jugia Khal in Arpangashia Union. It has not been repaired and experiences recurrent accidents and has the potential to collapse, which would disrupt local connectivity. Thus, the social media claims are false and misleading.
Claims:
Social Media users share a photo that shows a ruined bridge in Kerala, India.
Fact Check:
On receiving the posts, we reverse searched the image which leads to a Bengali News website named Manavjamin where the title displays, “19 dangerous bridges in Amtali, lakhs of people in fear”. We found the picture on this website similar to the viral image. On reading the whole article, we found that the bridge is located in Bangladesh's Amtali sub-district of Barguna district.
Taking a cue from this, we then searched for the bridge in that region. We found a similar bridge at the same location in Amtali, Bangladesh.
According to the article, The 40-meter bridge over Jugia Khal in Arpangashia Union, Amtali, was built in 2002 to 2006 and was never repaired. It is in a critical condition, causing frequent accidents and risking collapse. If the bridge collapses it will disrupt communication between multiple villages and the upazila town. Residents have made temporary repairs.
Hence, the claims made by social media users are fake and misleading.
Conclusion:
In conclusion, the viral photo claiming to show a ruined bridge in Kerala is actually from Amtali, Barguna district, Bangladesh. The bridge is in a critical state, with frequent accidents and the risk of collapse threatening local connectivity. Therefore, the claims made by social media users are false and misleading.
- Claim: A viral image shows a ruined bridge in Kerala, India.
- Claimed on: Facebook
- Fact Check: Fake & Misleading
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Executive Summary
A video circulating on social media claims that Iran’s new Supreme Leader Mojtaba Khamenei has passed away, with users attributing the claim to American sources. However, research by the CyberPeace found the claim to be false. Our research confirms that Mojtaba Khamenei is alive and in good health.
Claim
A Facebook user shared the viral video, claiming that Iran’s new Supreme Leader Mojtaba Khamenei had died.
Fact Check
To verify the claim, we conducted keyword searches on Google but found no credible media reports confirming his death. Further research led us to a report published on April 10, 2026, by ABP News. According to the report, amid discussions around a ceasefire, Mojtaba Khamenei issued a statement saying that Iran does not seek war with the United States or Israel, but as a nation, it must defend its rights.
Additionally, the image used in the viral video was analyzed using the AI detection tool HIVE Moderation. The results indicated a 99% probability that the image is AI-generated.
Conclusion
The viral claim is false and misleading. There is no credible evidence to suggest that Mojtaba Khamenei has died. On the contrary, recent verified reports confirm that he is alive and has even issued public statements on ongoing geopolitical developments. The widespread circulation of this claim appears to be driven by misinformation, amplified through social media without verification. The use of AI-generated visuals further adds to the confusion, making the content appear authentic at first glance.
Introduction
How Generative Artificial Intelligence, or GenAI, is changing the employee workday is no longer limited to writing emails or debugging code, but now also includes analysing contracts, generating reports, and much more. The use of AI tools in everyday work has become commonplace, but the speed at which companies have adopted these technologies has created a new kind of risk. Unlike threats that come from an outside attacker, Shadow AI is created inside an organisation by a legitimate employee who uses unapproved AI tools to make their work more efficient and productive. In many cases, the employee is unaware of the potential security, data privacy, and compliance risks involved in using such tools to perform their job duties.
What Is Shadow AI?
Shadow AI is when individuals use AI tools at work that aren’t provided by the company, like tools or other software programs, without the knowledge or permission of the employer. Examples of shadow AI include:
- Using personal ChatGPT or other chatbot accounts to complete tasks at the office
- Uploading business-related documents to online AI technologies for analysis or summarisation.
- Copying proprietary source code into an online AI model for debugging
- Installing browser extensions and add-ons that are not approved by IT or Security personnel.
How Shadow AI Is Harmful
1. Uncontrolled Data Exposure
When employees access or input information into their user-created AI, it becomes outside the controls of the company, such as both employee personal information and any third-party personal information, private company information (such as source code or contracts), and company internal strategies. After a user enters data into their user-created AIs, the company loses all ability to monitor how that data is stored, processed, or maintained. A data leak situation exists without a malicious cyberattack. The biggest risk of a data leak is not maliciousness but rather the loss of control and governance over sensitive data.
2. Regulatory and Legal Non-Compliance
Data protection laws like GDPR, India’s Digital Personal Data Protection (DPDP) Act, HIPAA, and other relevant sectoral laws require businesses to process data in accordance with the law, to minimise the amount of data they use, and to be accountable for their actions. Shadow AI often results in the unlawful use of personal data due to a lack of a legal basis for the processing, unauthorised cross-border data transfers, and not having appropriate contractual protections in place with their AI service providers. Regulators do not see the convenience of employees as an excuse for not complying with the law, and therefore, the organisation is ultimately responsible for any violations that occur.
3. Loss of Intellectual Property
Employees frequently use AI tools to speed up tasks involving proprietary information—debugging code, reviewing contracts, or summarising internal research. When done using unapproved AI platforms, this can expose trade secrets and intellectual property, eroding competitive advantage and creating long-term business risk.
Real-Life Example: Samsung’s ChatGPT Data Leak
In 2023, a case study exemplifying the Shadow AI risk occurred when Samsung Electronics placed a temporary ban on employee access to ChatGPT and other AI tools after reports from engineers revealed they were using ChatGPT to create debugging processes for internal source code and to summarise meeting notes. Consequently, confidential source code related to semiconductors was inadvertently uploaded onto a public AI platform. While there were no known incursions into the company’s system due to this incident, Samsung faced a significant challenge: once sensitive information is input into a public AI tool, it exists on external servers that are outside of the company’s purview or control.
As a result of this incident, Samsung restricted employee use of ChatGPT on corporate devices, issued a series of internal communications prohibiting the sharing of corporate data with public AI tools, and increased the urgency of their discussions regarding the adoption of secure, enterprise-level AI (artificial intelligence) solutions.
What Organisations Are Doing Today
Many organisations respond to Shadow AI risk by:
- Blocking access at the network level
- Circulating warning emails or policies
While these actions may reduce immediate exposure, they fail to address the root cause: employees still need AI to perform their jobs efficiently. As a result, bans often push AI usage underground, increasing Shadow AI rather than eliminating it.
Why Blocking AI Does Not Work—Governance Does
History has demonstrated that prohibition does not work - we see this when trying to block access to cloud storage, instant messaging and collaboration tools. Employees are forced to use personal devices and/or accounts when their employers block AI, which means employers do not have real-time visibility into how their employees are using these technologies, and creates friction with the security and compliance team as they try to enforce the types of tools their employees can use. Prohibiting AI adoption will not stop it from being adopted; it will just create a challenge for employers regarding how safe and responsible it is. The challenge for effective organisations is therefore to shift from denial and develop governance-first AI strategies aimed at controlling data usage, protection and security, rather than merely restricting access to a list of specific tools.
Shadow AI: A Silent Legal Liability Under the GDPR
Shadow AI isn't a problem for the Information Technology Department; it is a failure of Governance, Compliance and Law. By using AI tools that have not been approved as a result, the organisation processes personal data without a lawful basis (Article 6 of the General Data Protection Regulation (GDPR)), repurposes data for use beyond its original intent and in breach of the Purpose Limitation (Article 5(1)(b)), and routinely exceeds necessity and in breach of Data Minimisation (Article 5(1)(c)). The outcome of these actions is the use of tools that involve International Data Transfers Without Authorisation and are therefore in breach of Chapter V, and violate Article 32 because there are no enforceable safeguards in place. Most significantly, the failure to demonstrate Oversight, Logging and Control under Articles 5(2) and 24 constitutes a failure in Accountability. Therefore, from a Regulatory perspective, Shadow AI is not accidental and is not defensible.
The Right Solution: Secure and Governed AI Adoption
1. Provide Approved AI Tools
Employers have an obligation to supply business-approved AI technology for helping workers to be productive while maintaining maximum protections, like storing data separately and not using employees' data for training a model; defining how long data is kept, and the rules around deleting that data. When employees are provided with verified and secure AI options that align with their work processes, they will rely significantly less on Shadow AI.
2. Enforce Zero-Trust Data Access
The governance of AI systems must follow the principles of "zero trust," granting access to data only through the principle of "least privilege," which means that data access will only be allowed by the system user, and providing continuous verification of user-identity and context; this supports and helps establish context-aware controls to monitor and track all user activities, which will be especially important as agent-like AI systems become increasingly autonomous and are capable of operating at machine-speed where even small errors in configuration, will result in rapid and large expose to data.
3. Apply DLP and Audit Logging
It is important to have robust data loss prevention measures in place to protect sensitive data that is sent outside an organisation. The first end user or machine that accesses the data should be detailed in a comprehensive audit log that indicates when and how the data is accessed. In combination with other controls, these measures create accountability, comply with regulations, and assist with appropriately detecting and responding to incidents.
4. Maintain Visibility Across AI, Cloud, and SaaS
Security teams need unified visibility across AI tools, personal cloud applications, and SaaS platforms. Risks move across systems, and controls must follow the data wherever it flows.
Conclusion
This new threat exposes an organisation to the risk of data loss through leaks, regulatory fines, liability for the loss of intellectual property, and reputational damage, all of which can occur without any intent to cause harm. The way forward is not to block AI, but to adopt a clear framework built on governance, visibility, and secure enablement. This approach allows organisations to use AI with confidence, while ensuring trust, accountability, and effective oversight to protect data and support AI in reaching its full transformative potential. AI use is encouraged, but it must be done responsibly, ethically, and securely.
References
- https://bronson.ai/resources/shadow-ai/
- https://www.varonis.com/blog/shadow-ai
- https://www.waymakeros.com/learn/gdpr-hipaa-shadow-ai-compliance-nightmare
- https://www.forbes.com/sites/siladityaray/2023/05/02/samsung-bans-chatgpt-and-other-chatbots-for-employees-after-sensitive-code-leak/
- https://www.usatoday.com/story/special/contributor-content/2025/05/23/shadow-ai-the-hidden-risk-in-todays-workplace/83822081007
Introduction
On March 12, the Ministry of Corporate Affairs (MCA) proposed the Bill to curb anti-competitive practices of tech giants through ex-ante regulation. The Draft Digital Competition Bill is to apply to ‘Core Digital Services,’ with the Central Government having the authority to update the list periodically. The proposed list in the Bill encompasses online search engines, online social networking services, video-sharing platforms, interpersonal communications services, operating systems, web browsers, cloud services, advertising services, and online intermediation services.
The primary highlight of the Digital Competition Law Report created by the Committee on Digital Competition Law presented to the Parliament in the 2nd week of March 2024 involves a recommendation to introduce new legislation called the ‘Digital Competition Act,’ intended to strike a balance between certainty and flexibility. The report identified ten anti-competitive practices relevant to digital enterprises in India. These are anti-steering, platform neutrality/self-preferencing, bundling and tying, data usage (use of non-public data), pricing/ deep discounting, exclusive tie-ups, search and ranking preferencing, restricting third-party applications and finally advertising Policies.
Key Take-Aways: Digital Competition Bill, 2024
- Qualitative and quantitative criteria for identifying Systematically Significant Digital Enterprises, if it meets any of the specified thresholds.
- Financial thresholds in each of the immediately preceding three financial years like turnover in India, global turnover, gross merchandise value in India, or global market capitalization.
- User thresholds in each of the immediately preceding 3 financial years in India like the core digital service provided by the enterprise has at least 1 crore end users, or it has at least 10,000 business users.
- The Commission may make the designation based on other factors such as the size and resources of an enterprise, number of business or end users, market structure and size, scale and scope of activities of an enterprise and any other relevant factor.
- A period of 90 days is provided to notify the CCI of qualification as an SSDE. Additionally, the enterprise must also notify the Commission of other enterprises within the group that are directly or indirectly involved in the provision of Core Digital Services, as Associate Digital Enterprises (ADE) and the qualification shall be for 3 years.
- It prescribes obligations for SSDEs and their ADEs upon designation. The enterprise must comply with certain obligations regarding Core Digital Services, and non-compliance with the same shall result in penalties. Enterprises must not directly or indirectly prevent or restrict business users or end users from raising any issue of non-compliance with the enterprise’s obligations under the Act.
- Avoidance of favouritism in product offerings by SSDE, its related parties, or third parties for the manufacture and sale of products or provision of services over those offered by third-party business users on the Core Digital Service in any manner.
- The Commission will be having the same powers as vested to a civil court under the Code of Civil Procedure, 1908 when trying a suit.
- Penalty for non-compliance without reasonable cause may extend to Rs 1 lakh for each day during which such non-compliance occurs (max. of Rs 10 crore). It may extend to 3 years or with a fine, which may extend to Rs 25 crore or with both. The Commission may also pass an order imposing a penalty on an enterprise (not exceeding 1% of the global turnover) in case it provides incorrect, incomplete, misleading information or fails to provide information.
Suggestions and Recommendations
- The ex-ante model of regulation needs to be examined for the Indian scenario and studies need to be conducted on it has worked previously in different jurisdictions like the EU.
- The Bill should be aimed at prioritising the fostering of fair competition by preventing monopolistic practices in digital markets exclusively. A clear distinction from the already existing Competition Act, 2002 in its functioning needs to be created so that there is no overlap in the regulations and double jeopardy is not created for enterprises.
- Restrictions on tying and bundling and data usage have been shown to negatively impact MSMEs that rely significantly on big tech to reduce operational costs and enhance customer outreach.
- Clear definitions of "dominant position" and "anti-competitive behaviour" are essential for effective enforcement in terms of digital competition need to be defined.
- Encouraging innovation while safeguarding consumer data privacy in consonance with the DPDP Act should be the aim. Promoting interoperability and transparency in algorithms can prevent discriminatory practices.
- Regular reviews and stakeholder consultations will ensure the law adapts to rapidly evolving technologies.
- Collaboration with global antitrust bodies which is aimed at enhancing cross-border regulatory coherence and effectiveness.
Conclusion
The need for a competition law that is focused exclusively on Digital Enterprises is the need of the hour and hence the Committee recommended enacting the Digital Competition Act to enable CCI to selectively regulate large digital enterprises. The proposed legislation should be restricted to regulate only those enterprises that have a significant presence and ability to influence the Indian digital market. The impact of the law needs to be restrictive to digital enterprises and it should not encroach upon matters not influenced by the digital arena. India's proposed Digital Competition Bill aims to promote competition and fairness in the digital market by addressing anti-competitive practices and dominant position abuses prevalent in the digital business space. The Ministry of Corporate Affairs has received 41-page public feedback on the draft which is expected to be tabled next year in front of the Parliament.
References
- https://www.medianama.com/wp-content/uploads/2024/03/DRAFT-DIGITAL-COMPETITION-BILL-2024.pdf
- https://prsindia.org/files/policy/policy_committee_reports/Report_Summary-Digital_Competition_Law.pdf
- https://economictimes.indiatimes.com/tech/startups/meity-meets-india-inc-to-hear-out-digital-competition-law-concerns/articleshow/111091837.cms?from=mdr
- https://www.mca.gov.in/bin/dms/getdocument?mds=gzGtvSkE3zIVhAuBe2pbow%253D%253D&type=open
- https://www.barandbench.com/law-firms/view-point/digital-competition-laws-beginning-of-a-new-era
- https://www.linkedin.com/pulse/policy-explainer-digital-competition-bill-nimisha-srivastava-lhltc/
- https://www.lexology.com/library/detail.aspx?g=5722a078-1839-4ece-aec9-49336ff53b6c
