#FactCheck- Old Bangladesh Clip Misused as West Bengal Election Incident

A photo circulating on social media claims to show Indian cricketer Mohammed Siraj offering namaz during net practice, while teammates Rohit Sharma, Virat Kohli and Shubman Gill are seen taking a selfie with him. Several users are sharing the image as a “beautiful moment,” portraying it as a symbol of faith, unity and sportsmanship. However, research by the Cyber Peace Foundation has found that the viral image is not genuine and has been AI-generated.

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Claim

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On January 14, 2026, multiple Facebook users shared the viral image with captions describing it as a touching scene from Rajkot’s Saurashtra Stadium. The posts claim that Mohammed Siraj took time out during net practice to offer prayers, reflecting his strong faith, while fellow cricketers Rohit Sharma, Virat Kohli and Shubman Gill respectfully captured the moment on camera.

Users praised the image as a rare blend of spirituality, discipline, teamwork and mutual respect, calling it a “beautiful confluence of sport and faith.”(Links to the post, archived version and screenshots are provided below.)

• https://www.facebook.com/photo/?fbid=4437845333095160&set=a.1510003369212719 

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Fact Check:

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On closely examining the viral image, several visual inconsistencies and unnatural elements were observed, raising suspicion that the picture may not be authentic.To verify this, the Cyber Peace Foundation analysed the image using the AI detection tool Hive Moderation. According to the tool’s assessment, the image showed a 99% likelihood of being AI-generated.

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To further strengthen the verification, the image was also scanned using another AI detection platform, Sightengine. The results indicated a 96% probability that the image was generated using artificial intelligence.

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Conclusion:

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The research confirms that the viral image claiming to show Mohammed Siraj offering namaz during net practice, with Rohit Sharma, Virat Kohli and Shubman Gill taking a selfie, is not real.The photograph has been created using AI tools and falsely shared on social media, misleading users by presenting a fabricated scene as an authentic moment.

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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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Introduction

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In the hyperconnected world, cyber incidents can no longer be treated as sporadic disruptions; such incidents have become an everyday occurrence. The attack landscape today is very consequential and shows significant multiplication in its frequency, with ransomware attacks incapacitating a health system, phishing attacks hitting a financial institution, or state-sponsored attacks on critical infrastructures. Towards counteracting such threats, traditional ways alone are not enough, they gravely rely on manual research and human intellect. Attackers exercise speed, scale, and stealth, and defenders are always four steps behind. With such a widening gap, it is deemed necessary to facilitate incident response and crisis management with the intervention of automation and artificial intelligence (AI) for faster detection, context-driven decision-making, and collaborative response beyond human capabilities.

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Incident Response and Crisis Management

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Incident response is the structured way in which organisations deal with responding to detecting, segregating, and recovering from security incidents. Crisis management takes this even further, dealing not only with the technical fallout of a breach but also its business, reputation, and regulatory implications. Echelon used to depend on manual teams of people sorting through logs, cross-correlating alarms, and generating responses, a paradigm effective for small numbers but quickly inadequate in today's threat climate. Today's opponents attack at machine speed, employing automation to launch attacks. Under such circumstances, responding with slow, manual methods means delay and draconian consequences. The AI and automation introduction is a paradigm change that allows organisations to equate the pace and precision with which attackers initiate attacks in responding to incidents.

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How Automation Reinvents Response

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Cybercrime automation liberates cybercrime analysts from boring and repetitive tasks that consume time. An analyst manually detects potential threats from a list of hundreds each day, while automated systems sift through noise and focus only on genuine threats. Malware can automatically cause infected computers to be disconnected from the network to avoid spreading or may automatically have its suspicious account permissions removed without human intervention. The security orchestration systems move further by introducing playbooks, predefined steps describing how incidents of a certain type (e.g., phishing attempts or malware infections) should be handled. This ensures fast containment while ensuring consistency and minimising human error amid the urgency of dealing with thousands of alerts.

Automation takes care of threat detection, prioritisation, and containment, allowing human analysts to refocus on more complex decision-making. Instead of drowning in the sea of trivial alerts, security teams can now devote their efforts to more strategic areas: threat hunting and longer-term resilience. Automation is a strong tool of defence, cutting response times down from hours to minutes.

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The Intelligence Layer: AI in Action

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If automation provides speed, then AI is what allows the brain to be intelligent and flexible. Working with old and fixed-rule systems, AI-enabled solutions learn from experiences, adapt to changes in threats, and discover hidden patterns of which human analysts themselves would be unaware. For instance, machine learning algorithms identify normal behaviour on a corporate network and raise alerts on any anomalies that could indicate an insider attack or an advanced persistent threat. Similarly, AI systems sift through global threat intelligence to predict likely attack vectors so organisations can have their vulnerabilities fixed before they are exploited.

AI also boosts forensic analysis. Instead of searching forever for clues, analysts let AI-driven systems trace back to the origin of an event, identify vulnerabilities exploited by attackers, and flag systems that are still under attack. During a crisis, AI is a decision support that predicts outcomes of different scenarios and recommends the best response. In response to a ransomware attack, for example, based on context, AI might advise separating a single network segment or restoring from backup or alerting law enforcement. 

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Real-World Applications and Case Studies

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Already, this mitigation has been provided in the form of real-world applications of automation and AI. Consider, for example, IBM Watson for Cybersecurity, which has been applied in analysing unstructured threat intelligence and providing analysts with actionable results in minutes, rather than days. Like this, systems driven by AI in DARPA's Cyber Grand Challenge demonstrated the ability to automatically identify an instant vulnerability, patch it, and reveal the potential of a self-healing system. AI-powered fraud detection systems stop suspicious transactions in the middle of their execution and work all night to prevent losses. What is common in all these examples is that automation and AI lessen human effort, increase accuracy, and in the event of a cyberattack, buy precious time.

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Challenges and Limitations

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While promising, the technology is still not fully mature. The quality of an AI system is highly dependent on the training data provided; poor training can generate false positives that drown teams or worse false negatives that allow attackers to proceed unabated. Attackers have also started targeting AI itself by poisoning datasets or designing malware that does not get detected. Aside from risks that are more technical, the operational and financial costs involved in implementing advanced AI-based systems present expensive threats to any company. Organisations will have to make expenditures not only on technology but also for the training of staff to best utilise these tools. There are some ethical and privacy issues to consider as well because systems may be processing sensitive personal data, so global data protection laws such as the GDPR or India's DPDP Act could come into conflict.

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Creating a Human-AI Collaboration

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The future is not going to be one of substitution by machines but of creating human-AI synergy. Automation can do the drudgery, AI can provide smarts, and human professionals can use judgment, imagination, and ethical decisions. One would want to build AI-fuelled Security Operations Centres where technology and human experts work in tandem. Continuous training must be provided to AI models to reduce false alarms and make them most resistant against adversarial attacks. Regular conduct of crisis drills that combine AI tools and human teams can ensure preparedness for real-time events. Likewise, it is worth integrating ethical AI guidelines into security frameworks to ensure a stronger defence while respecting privacy and regulatory compliance.

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Conclusion

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Cyber-attacks are an eventuality in this modern time, but the actual impact need not be so harsh. The organisations can maintain the programmatic method of integrating automation and AI into incident response and crisis management so that the response against the very threat can be shifted from reactive firefighting to proactive resilience. Automation gives speed and efficiency while AI gives intelligence and foresight, hence putting the defenders on par and possibly exceeding the speed and sophistication of the attackers. But an utmost system without human inquisitiveness, ethical reasoning, and strategic foresight would remain imperfect. The best defence is in that human-machine relationship symbiotic system wherein automation and AI take care of how fast and how many cyber threats come in, whereas human intellect ensures that every response is aligned with larger organizational goals. This synergy is where cybersecurity resiliency will reside in the future-the defenders won't just be reacting to emergencies but will rather be driving the way.

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References

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• https://www.sisainfosec.com/blogs/incident-response-automation/
• https://stratpilot.ai/role-of-ai-in-crisis-management-and-its-critical-importance/
• https://www.juvare.com/integrating-artificial-intelligence-into-crisis-management/
• https://www.motadata.com/blog/role-of-automation-in-incident-management/

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