#FactCheck -Viral Post Falsely Attributes Communal NEET Remark to Kangana Ranaut; Fact Check Debunks Claim

On 6 June 2025, the EU Council officially adopted the revised Cybersecurity Blueprint, marking a significant evolution from the 2017 guidance. This framework, formalised through Council Recommendation COM(2025) 66 final, responds to a transformed threat environment and reflects new legal milestones like the NIS2 Directive (Network and Information Security Directive) and the Cyber Solidarity Act.

From Fragmented Response to Cohesive Strategy

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Between 2017 and now, EU member states have built various systems to manage cyber incidents. Still, real-world events and exercises highlighted critical gaps - uncoordinated escalation procedures, inconsistent terminology, and siloed information flows. The updated Blueprint addresses these issues by focusing on a harmonised operational architecture for the EU. It defines a clear crisis lifecycle with five stages: Detection, Analysis, Escalation, Response, and Recovery. Each stage is supported by common communication protocols, decision-making processes, and defined roles. Consistency is key; standardised terminology along with a broad scope of application that eases cross-border collaboration and empowers coherent response efforts.

Legal Foundations: NIS2, ENISA & EU‑CyCLONe

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Several core pillars of EU cybersecurity directly underpin the Blueprint:

• ENISA – The European Union Agency for Cybersecurity continues to play a central role. It supports CSIRTs' Network operations, leads EU‑CyCLONe ( European cyber crisis liaison organisation network) coordination, conducts simulation exercises, and gives training on incident management
• NIS2 Directive, particularly Article 16, is a follow-up of NIS. NIS2 mandates operators of critical infrastructure and essential services to implement appropriate security measures and report incidents to the relevant authorities. Compared to NIS, NIS2 expands its EU-wide security requirements and scope of covered organisations and sectors to improve the security of supply chains, simplify reporting obligations, and enforce more stringent measures and sanctions throughout Europe. It also formally legitimises the EU‑CyCLONe network, which is the crisis liaison mechanism bridging technical teams from member states.

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These modern tools, integrated with legal backing, ensure the Blueprint isn’t just theoretical; it’s operationally enforceable.

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What’s Inside the Blueprint?

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The 2025 Blueprint enhances several critical areas:

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1. Clear Escalation Triggers - It spells out when a national cyber incident merits EU-level attention, especially those affecting critical infrastructure across borders. Civilian Military Exchange. The Blueprint encourages structured information sharing with defence institutions and NATO, recognising that cyber incidents often have geopolitical implications 
2. Recovery & Lessons Learned – A dedicated chapter ensures systematic post-incident reviews and shared learning among member states.

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Adaptive & Resilient by Design

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Rather than a static document, the Blueprint is engineered to evolve:

• Regular Exercises: Built into the framework are simulation drills that are known as Blueprint Operational Level Exercises—to test leadership response and cross-border coordination via EU‑CyCLONe
• Dynamic Reviews: The system promotes continuous iteration- this includes revising protocols, learning from real incidents, and refining role definitions.
  
  

This iterative, learning-oriented architecture aims to ensure the Blueprint remains robust amid rapidly evolving threats, including AI-boosted hacks and hybrid cyber campaigns.

Global Implications & Lessons for Others

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The EU’s Cybersecurity Blueprint sets a global benchmark in cyber resilience and crisis governance:

• Blueprint for Global Coordination: The EU’s method of defined crisis stages, empowered liaison bodies (like EU‑CyCLONe), and continuous exercise can inspire other regional blocs or national governments to build their own crisis mechanisms.
• Public–Private Synergy: The Blueprint’s insistence on cooperation between governments and private-sector operators of essential services (e.g., energy, telecom, health) provides a model for forging robust ecosystems.
• Learning & Sharing at Scale: Its requirement for post-crisis lessons and peer exchange can fuel a worldwide knowledge network, cultivating resilience across jurisdictions.

Conclusion

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The 2025 EU Cybersecurity Blueprint is more than an upgrade; it’s a strategic shift toward operational readiness, legal coherence, and collaborative resilience. Anchored in NIS2 and ENISA, and supported by EU‑CyCLONe, it replaces fragmented guidance with a well-defined, adaptive model. Its adoption signals a transformative moment in global cyber governance as for nations building crisis frameworks, the Blueprint offers a tested, comprehensive template: define clear stages, equip liaison networks, mandate drills, integrate lessons, and legislate coordination. In an era where cyber threats transcend borders, this proves to be an important development that can offer guidance and set a precedent.

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For India, the EU Cybersecurity Blueprint offers a valuable reference point as we strengthen our own frameworks through initiatives like the DPDP Act, the upcoming Digital India Act and CERT-In’s evolving mandates. It reinforces the importance of coordinated response systems, cross-sector drills, and legal clarity. As cyber threats grow more complex, such global models can complement our national efforts and enhance regional cooperation.

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References

• https://industrialcyber.co/expert/the-eus-cybersecurity-blueprint-and-the-future-of-cyber-crisis-management/
• https://www.consilium.europa.eu/en/press/press-releases/2025/06/06/eu-adopts-blueprint-to-better-manage-european-cyber-crises-and-incidents/ 
• https://www.enisa.europa.eu/topics/eu-incident-response-and-cyber-crisis-management 
• https://www.enisa.europa.eu/news/new-cyber-blueprint-to-scale-up-the-eu-cybersecurity-crisis-management 
• https://www.isc2.org/Insights/2025/01/EU-Cyber-Solidarity-Act 
• https://www.enisa.europa.eu/topics/eu-incident-response-and-cyber-crisis-management/eu-cyclone 
• https://nis2directive.eu/what-is-nis2/ 

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Executive Summary 
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A claim is circulating on social media that the U.S. military successfully rescued a missing crew member of an F-15E fighter jet in Iran. Along with this claim, a photo is being widely shared, allegedly showing the rescued U.S. airman after the high-risk operation. However, researches reveal that the viral image is not authentic and has been generated using artificial intelligence tools.

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The Claim

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On April 6, 2026, a social media user named “July Gaytan” shared the viral image with the caption: “Here is the photo of the U.S. airman being rescued yesterday in Iran.”

The post quickly gained traction, with many users believing it to be genuine.
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• https://www.facebook.com/photo/?fbid=1724007721903888&set=a.116284172676259 
• https://perma.cc/URM4-KEJA 

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Fact Check 
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Despite extensive searches, no credible media report or official source has published any real image of the rescued crew members. This raised suspicion about the authenticity of the viral photo. Hive Moderation analysis indicated a 100% probability that the image was generated using Google’s Gemini AI.
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A second scan using Undetectable AI also concluded that the image is AI-generated.

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Reports indicate that a U.S. Air Force F-15E Strike Eagle was shot down in Iran. The aircraft had two crew members on board: a pilot and a Weapon Systems Officer (WSO).
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• The pilot was rescued shortly after the incident.
• The WSO was initially missing and remained inside Iranian territory in an injured condition.
• The U.S. later carried out a high-risk rescue operation and successfully evacuated the WSO from Iran.
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U.S. President Donald Trump also confirmed the “brave and risky” rescue mission in a detailed post on his platform, Truth Social. The statement was further shared by the official White House account.
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• https://x.com/WhiteHouse/status/2040644451513598220?s=20
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Conclusion

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The viral image claiming to show a rescued U.S. airman in Iran is not real. It has been created using AI tools, likely Google’s Gemini. While it is true that the U.S. conducted a high-risk operation to rescue the missing crew member, no authentic image of the rescue or the personnel has been publicly released.

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Introduction

Search engines have become indispensable in our daily lives, allowing us to find information instantly by entering keywords or phrases. Using the prompt "search Google or type a URL" reflects just how seamless this journey to knowledge has become. With millions of searches conducted every second, and Google handling over 6.3 million searches per minute as of 2023 (Statista), one critical question arises: do search engines prioritise results based on user preferences and past behaviours, or are they truly unbiased?

Understanding AI Bias in Search Algorithms

AI bias is also known as machine learning bias or algorithm bias. It refers to the occurrence of biased results due to human biases that deviate from the original training data or AI algorithm which leads to distortion of outputs and creation of potentially harmful outcomes. The sources of this bias are algorithmic bias, data bias and interpretation bias which emerge from user history, geographical data, and even broader societal biases in training data. 

Common biases include excluding certain groups of people from opportunities because of AI bias. In healthcare, underrepresenting data of women or minority groups can skew predictive AI algorithms. While AI helps streamline the automation of resume scanning during a search to help identify ideal candidates, the information requested and answers screened out can result in biased outcomes due to a biased dataset or any other bias in the input data.

Case in Point: Google’s "Helpful" Results and Its Impact 

Google optimises results by analysing user interactions to determine satisfaction with specific types of content. This data-driven approach forms ‘filter bubbles’ by repeatedly displaying content that aligns with a user’s preferences, regardless of factual accuracy. While this can create a more personalised experience, it risks confining users to a limited view, excluding diverse perspectives or alternative viewpoints.

The personal and societal impacts of such biases are significant. At an individual level, filter bubbles can influence decision-making, perceptions, and even mental health. On a societal level, these biases can reinforce stereotypes, polarise opinions, and shape collective narratives. There is also a growing concern that these biases may promote misinformation or limit users’ exposure to diverse perspectives, all stemming from the inherent bias in search algorithms.

Policy Challenges and Regulatory Measures

Regulating emerging technologies like AI, especially in search engine algorithms, presents significant challenges due to their intricate, proprietary nature. Traditional regulatory frameworks struggle to keep up with them as existing laws were not designed to address the nuances of algorithm-driven platforms. Regulatory bodies are pushing for transparency and accountability in AI-powered search algorithms to counter biases and ensure fairness globally. For example, the EU’s Artificial Intelligence Act aims to establish a regulatory framework that will categorise AI systems based on risk and enforces strict standards for transparency, accountability, and fairness, especially for high-risk AI applications, which may include search engines. India has proposed the Digital India Act in 2023 which will define and regulate High-risk AI. 

Efforts include ethical guidelines emphasising fairness, accountability, and transparency in information prioritisation. However, a complex regulatory landscape could hinder market entrants, highlighting the need for adaptable, balanced frameworks that protect user interests without stifling innovation.

CyberPeace Insights

In a world where search engines are gateways to knowledge, ensuring unbiased, accurate, and diverse information access is crucial. True objectivity remains elusive as AI-driven algorithms tend to personalise results based on user preferences and past behaviour, often creating a biased view of the web. Filter bubbles, which reinforce individual perspectives, can obscure factual accuracy and limit exposure to diverse viewpoints. Addressing this bias requires efforts from both users and companies. Users should diversify sources and verify information, while companies should enhance transparency and regularly audit algorithms for biases. Together, these actions can promote a more equitable, accurate, and unbiased search experience for all users. 

References 

• https://www.bbc.com/future/article/20241101-how-online-photos-and-videos-alter-the-way-you-think 
• https://www.bbc.com/future/article/20241031-how-google-tells-you-what-you-want-to-hear
• https://www.ibm.com/topics/ai-bias#:~:text=In%20healthcare%2C%20underrepresenting%20data%20of,can%20skew%20predictive%20AI%20algorithms

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