#FactCheck-Old Yogi Adityanath video falsely linked to Bihar encounter case
Executive Summary
A video of Uttar Pradesh Chief Minister Yogi Adityanath is being widely circulated on social media with the claim that he supported the Bihar police and justified the encounter of Bharat Bhushan Tiwari in Bhojpur district’s Bilouti village on June 17, 2026. CyberPeace Research Wing research found the claim to be misleading. The viral video is not related to the Bihar encounter case. It is an old video from February 2026, in which the Chief Minister was speaking in the context of law and order and police action in Uttar Pradesh.
Claim:
A Facebook user shared the video claiming it shows CM Yogi Adityanath’s reaction supporting the Bihar encounter of Bharat Tiwari. https://www.facebook.com/reel/1712174420025092 ,https://archive.ph/wip/yUsou
Fact Check:
A keyword search led to the same video being found on the ‘ET Now Swadesh’ YouTube channel in the form of a short video, uploaded on February 4, 2026, indicating that it predates the Bihar incident. https://www.youtube.com/watch?v=Dj7ySFsnkqk
Further verification led to a Dainik Jagran report published on February 3, 2026, which carried visuals from the same statement. The report confirmed that the remarks were made in the context of Uttar Pradesh’s law and order situation and police response. https://www.jagran.com/uttar-pradesh/lucknow-city-cm-yogi-on-up-crime-zero-tolerance-and-police-action-justified-40129630.html
The report quoted CM Yogi Adityanath saying that if police do not act, criminals would dominate the situation, and that police are empowered to respond in the language criminals understand. He also emphasized that police training is designed to ensure effective response to crime. An Aaj Tak report on the Bihar encounter case stated that 28-year-old Bharat Tiwari was killed in an encounter on June 17, 2026, in Bhojpur district. Following the incident, an FIR was registered against police personnel, and the victim’s mother demanded strict action and justice.
Conclusion:
The research confirms that the viral video of CM Yogi Adityanath is old and unrelated to the Bihar encounter case. It is from February 2026 and pertains to a law-and-order statement in Uttar Pradesh. The video is being falsely shared by linking it to the Bihar encounter incident.
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Introduction
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.
Incident Response and Crisis Management
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.
How Automation Reinvents Response
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.
The Intelligence Layer: AI in Action
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.
Real-World Applications and Case Studies
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.
Challenges and Limitations
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.
Creating a Human-AI Collaboration
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.
Conclusion
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.
References
- 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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Introduction
Artificial Intelligence (AI) driven autonomous weapons are reshaping military strategy, acting as force multipliers that can independently assess threats, adapt to dynamic combat environments, and execute missions with minimal human intervention, pushing the boundaries of modern warfare tactics. AI has become a critical component of modern technology-driven warfare and has simultaneously impacted many spheres in a technology-driven world. Nations often prioritise defence for significant investments, supporting its growth and modernisation. AI has become a prime area of investment and development for technological superiority in defence forces. India’s focus on defence modernisation is evident through initiatives like the Defence AI Council and the Task Force on Strategic Implementation of AI for National Security.
The main requirement that Autonomous Weapons Systems (AWS) require is the “autonomy” to perform their functions when direction or input from a human actor is absent. AI is not a prerequisite for the functioning of AWSs, but, when incorporated, AI could further enable such systems. While militaries seek to apply increasingly sophisticated AI and automation to weapons technologies, several questions arise. Ethical concerns have been raised for AWS as the more prominent issue by many states, international organisations, civil society groups and even many distinguished figures.
Ethical Concerns Surrounding Autonomous Weapons
The delegation of life-and-death decisions to machines is the ethical dilemma that surrounds AWS. A major concern is the lack of human oversight, raising questions about accountability. What if AWS malfunctions or violates international laws, potentially committing war crimes? This ambiguity fuels debate over the dangers of entrusting lethal force to non-human actors. Additionally, AWS poses humanitarian risks, particularly to civilians, as flawed algorithms could make disastrous decisions. The dehumanisation of warfare and the violation of human dignity are critical concerns when AWS is in question, as targets become reduced to mere data points. The impact on operators’ moral judgment and empathy is also troubling, alongside the risk of algorithmic bias leading to unjust or disproportionate targeting. These ethical challenges are deeply concerning.
Balancing Ethical Considerations and Innovations
It is immaterial how advanced a computer becomes in simulating human emotions like compassion, empathy, altruism, or other emotions as the machine will only be imitating them, not experiencing them as a human would. A potential solution to this ethical predicament is using a 'human-in-the-loop' or 'human-on-the-loop' semi-autonomous system. This would act as a compromise between autonomy and accountability.
A “human-on-the-loop” system is designed to provide human operators with the ability to intervene and terminate engagements before unacceptable levels of damage occur. For example, defensive weapon systems could autonomously select and engage targets based on their programming, during which a human operator retains full supervision and can override the system within a limited period if necessary.
In contrast, a ‘human-in-the-loop” system is intended to engage individual targets or specific target groups pre-selected by a human operator. Examples would include homing munitions that, once launched to a particular target location, search for and attack preprogrammed categories of targets within the area.
International Debate and Regulatory Frameworks
The regulation of autonomous weapons that employ AI, in particular, is a pressing global issue due to the ethical, legal, and security concerns it contains. There are many ongoing efforts at the international level which are in discussion to regulate such weapons. One such example is the initiative under the United Nations Convention on CertainConventional Weapons (CCW), where member states, India being an active participant, debate the limits of AI in warfare. However, existing international laws, such as the Geneva Conventions, offer legal protection by prohibiting indiscriminate attacks and mandating the distinction between combatants and civilians. The key challenge lies in achieving global consensus, as different nations have varied interests and levels of technological advancement. Some countries advocate for a preemptive ban on fully autonomous weapons, while others prioritise military innovation. The complexity of defining human control and accountability further complicates efforts to establish binding regulations, making global cooperation both essential and challenging.
The Future of AI in Defence and the Need for Stronger Regulations
The evolution of autonomous weapons poses complex ethical and security challenges. As AI-driven systems become more advanced, a growing risk of its misuse in warfare is also advancing, where lethal decisions could be made without human oversight. Proactive regulation is crucial to prevent unethical use of AI, such as indiscriminate attacks or violations of international law. Setting clear boundaries on autonomous weapons now can help avoid future humanitarian crises. India’s defence policy already recognises the importance of regulating the use of AI and AWS, as evidenced by the formation of bodies like the Defence AI Project Agency (DAIPA) for enabling AI-based processes in defence Organisations. Global cooperation is essential for creating robust regulations that balance technological innovation with ethical considerations. Such collaboration would ensure that autonomous weapons are used responsibly, protecting civilians and combatants, while encouraging innovation within a framework prioritising human dignity and international security.
Conclusion
AWS and AI in warfare present significant ethical, legal, and security challenges. While these technologies promise enhanced military capabilities, they raise concerns about accountability, human oversight, and humanitarian risks. Balancing innovation with ethical responsibility is crucial, and semi-autonomous systems offer a potential compromise. India’s efforts to regulate AI in defence highlight the importance of proactive governance. Global cooperation is essential in establishing robust regulations that ensure AWS is used responsibly, prioritising human dignity and adherence to international law, while fostering technological advancement.
References
● https://indianexpress.com/article/explained/reaim-summit-ai-war-weapons-9556525/
Executive Summary
A CCTV video showing a man being shot is being widely circulated on social media with the claim that it depicts the killing of Lashkar-e-Taiba terrorist Amir Hamza in Pakistan. However, research by the CyberPeace Research Wing found that the claim is misleading. The viral video existed online even before the reported attack on Amir Hamza.
Claim
Social media users are sharing a CCTV clip claiming that Lashkar-e-Taiba terrorist Amir Hamza was shot dead in Pakistan.
Fact Check
To verify the claim, we first searched relevant keywords such as “Maulana Amir Hamza firing Lahore.” This led us to a report published on April 17, 2026, by The Hindu. Citing Pakistani channel 24 News HD TV, the report stated that unidentified attackers opened fire on the car of TV host Justice Nazir Ahmed Ghazi. Amir Hamza was injured in the incident, not killed.
We also reviewed the official social media accounts of 24 News HD TV. A post on its X handle (@24NewsHD) confirmed that Justice Ghazi was safe, while Amir Hamza sustained injuries in the firing incident in Lahore.
For further verification, we extracted keyframes from the viral video and performed a reverse image search. The same clip was found uploaded on March 28, 2026, on a Pakistani Facebook page. According to the post, the CCTV footage was linked to the killing of an individual named Saifullah Malakhel.
Although we could not independently verify the exact origin of the video, our findings clearly indicate that the footage predates the recent attack on Amir Hamza and is unrelated to the incident.
Conclusion
The viral claim is false. Amir Hamza was not killed but reportedly injured in the firing incident, as per credible media reports. The CCTV video being shared in this context is old and unrelated, and has been circulated with a misleading narrative.
