#FactCheck: False Social Media Claim on six Army Personnel were killed in retaliatory attack by ULFA in Myanmar
Executive Summary:
A widely circulated claim on social media indicates that six soldiers of the Assam Rifles were killed during a retaliatory attack carried out by a Myanmar-based breakaway faction of the United Liberation Front of Asom (Independent), or ULFA (I). The post included a photograph of coffins covered in Indian flags with reference to soldiers who were part of the incident where ULFA (I) killed six soldiers. The post was widely shared, however, the fact-check confirms that the photograph is old, not related, and there are no trustworthy reports to indicate that any such incident took place. This claim is therefore false and misleading.
Claim:
Social media users claimed that the banned militant outfit ULFA (I) killed six Assam Rifles personnel in retaliation for an alleged drone and missile strike by Indian forces on their camp in Myanmar with captions on it “Six Indian Army Assam Rifles soldiers have reportedly been killed in a retaliatory attack by the Myanmar-based ULFA group.”. The claim was accompanied by a viral post showing coffins of Indian soldiers, which added emotional weight and perceived authenticity to the narrative.
Fact Check:
We began our research with a reverse image search of the image of coffins in Indian flags, which we saw was shared with the viral claim. We found the image can be traced to August 2013. We found the traces in The Washington Post, which confirms the fact that the viral snap is from the Past incident where five Indian Army soldiers were killed by Pakistani intruders in Poonch, Jammu, and Kashmir, on August 6, 2013.
Also, The Hindu and India Today offered no confirmation of the death of six Assam Rifles personnel. However, ULFA (I) did issue a statement dated July 13, 2025, claiming that three of its leaders had been killed in a drone strike by Indian forces.
However, by using Shutterstock, it depicts that the coffin's image is old and not representative of any current actions by the United Liberation Front of Asom (ULFA).
The Indian Army denied it, with Defence PRO Lt Col Mahendra Rawat telling reporters there were "no inputs" of such an operation. Assam Chief Minister Himanta Biswa Sarma also rejected that there was cross-border military action whatsoever. Therefore, the viral claim is false and misleading.
Conclusion:
The assertion that ULFA (I) killed six soldiers from the 6th Assam Rifles in a retaliation strike is incorrect. The viral image used in these posts is from 2013 in Jammu & Kashmir and has no relevance to the present. There have been no verified reports of any such killings, and both the Indian Army and the Assam government have categorically denied having conducted or knowing of any cross-border operation. This faulty narrative is circulating, and it looks like it is only inciting fear and misinformation therefore, please ignore it.
- Claim: Report confirms the death of six Assam Rifles personnel in an ULFA-led attack.
- Claimed On: Social Media
- Fact Check: False and Misleading
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Introduction
Cybercrime in India is developing at a rapid rate in terms of depth and volume, with culprits leveraging technology, anonymity, and social engineering to exploit unsuspecting victims. In a high-profile instance of coordinated police action, the Delhi Police Crime Branch recently cracked a large-scale pan-India cybercrime syndicate with its arms stretching across Delhi, Rajasthan, and Uttar Pradesh. The syndicate used to be involved in a range of cybercrimes, from sextortion and online fraud to fake call centres and cloning of bank accounts. With over ₹5 crore of illicit financial transactions revealed, the operation highlights the critical role of proactive cyber policing, data security and public awareness in India's war against digital crime.
A Multi-State Operation: Crime Network across States
On May 24, 2025, on receiving a tip-off, the Delhi Police conducted a specific raid in New Ashok Nagar to catch a suspect consignment said to be used for cybercrime. This resulted in a multi-layered investigation that revealed a large crime syndicate. Police recovered 28 mobile phones, 30 SIM cards, 15 debit cards, 8 cheque books, and two laptops, equipment said to have been used in crimes ranging from sextortion to fake loan scams.
Three of the initial arrests revealed the use of fake kits like pre-activated SIMs and counterfeit documents to create phoney digital identities and bank accounts. They were being used to bypass KYC norms and make untraceable transactions, illustrating how cyber thieves exploit digital identity as well as financial authentication loopholes in the system.
Fake Call Centre Falsely Claiming to be a Lender
Tracing the leads, the investigation then led the police to Mundka, a semi-residential and industrial area in Delhi, where a fake call centre in the name of a loan assistance service was operating. Suspects were allegedly operating the business. With deceptive scripts, their telemarketing staff lured victims with the offer of instant personal loans. When a prospective victim replied favorably and was willing to go further, he was asked to send identification documents and was then forced to pay a "processing fee." Once the payment was made, the accused would cut off contact immediately, leaving the victims shortchanged.
During the raid, seven individuals were apprehended, six of whom were trained tele-callers with a reasonable level of technical skill. In spite of possessing educational certificates and receiving a meagre pay of between ₹8,000 and ₹9,000 a month, these individuals had been enticed into the cybercrime network, demonstrating how educated youth are now more commonly being exploited or recruited by such scam networks in return for quick money.
Uncovering the Sextortion Racket
The most shocking disclosure was that of a sextortion racket being run from New Ashok Nagar, a residential area located in West Delhi, New Delhi. Suspects tricked victims with fraudulent Facebook profiles, contacted them on Messenger, and then changed to WhatsApp video calls. Pornographic videos were played on such calls while the reactions of the victim were secretly recorded. These were later utilised for extortion by threatening to share them with the whole world. The ability of such a group to blackmail and psychologically manipulate the victims indicates the psychological nature of cybercrime and the need for online safety education.
Impact and Significance: A Wake-Up Call for Law Enforcement and Public Awareness
This crackdown is uncovering some ominous trends that reflect the changing face of cybercrime in India. The syndicate's framework highlights the organised and multi-state nature of cybercrime, mostly operating through systemic loopholes. Misuse of social media sites and fintech apps is also rampant, and these are being leveraged for scams, sextortion, and monetary fraud. One of the most concerning trends is young people becoming more engaged in cybercrime, either out of economic necessity or enticed by easy cash. Most of these scams increasingly involve psychological manipulation, particularly in sextortion, where shame and fear are employed as tools. Digital identity fraud has also been facilitated through false documents and lenient Know Your Customer (KYC) checks, with fraudsters being able to evade verification processes.
These observations underscore the necessity of strong reporting channels. There also needs to be an urgent implementation of stringent verification standards in the telecom and banking industries, along with extensive community-level digital literacy initiatives to sensitise citizens to online threats and preventive measures.
CyberPeace Vision: Building a Safe Digital India
India needs a multi-level cyber security approach, comprising people awareness, AI-driven detection systems, and coordination of inter-state policing. Precedence needs to be given to:
- Capacity building of cyber police units.
- Real-time exchange of scam intelligence among law enforcement.
- Schools, colleges, and workplaces should be aware of digital hygiene.
- Rehabilitation of cyber-offenders, especially youth.
- Countering online misinformation and disinformation through fact-checking and public education campaigns
- Ensuring inclusivity in cyber safety policies so vulnerable populations, including rural users, senior citizens, and linguistic minorities, are not left behind
The breakdown of the syndicate is a major victory, but the absence of difficulty with which these networks function highlights the need for cybercrime prevention initiatives, not after the fact.
Conclusion
The Delhi Police bust of a pan-India cybercrime gang is evidence of the increasing reach and audacity of cyber crooks from one corner of India to another. From sextortion and social engineering to financial fraud and identity theft on the web, the bust demonstrates how deep and pervasive cybercrime gangs have become. It is also a reminder that anyone can get entangled and that education, awareness, and early reporting are our best defence. With India's online presence expanding day by day, our collective cyber awareness must keep pace. The fight against cybercrime will not be won only by arrests, but through a national effort to secure our digital spaces.
References
- https://indianexpress.com/article/cities/delhi/delhi-police-cyber-crime-syndicate-10047218/
- https://www.thehindu.com/news/cities/Delhi/delhi-police-bust-pan-india-cybercrime-syndicate/article69652694.ece#:~:text=The%20Delhi%20police%20have%20dismantled,and%20an%20orchestrated%20sextortion%20racket.
- https://cybercrime.gov.in/
- https://www.ncrb.gov.in/
- https://economictimes.indiatimes.com/wealth/save/online-scams-are-on-the-rise-learn-about-the-latest-tricks-fraudsters-are-using-to-identify-frauds-and-protect-yourself/articleshow/114162295.cms?from=mdr
Executive Summary
A volcano erupted at Indonesia’s Anak Krakatau on the night of September 4, 2026. A video is being shared on social media in connection with the eruption. The video shows lava rising high into the air following a volcanic eruption, with people seen fleeing the area. Some social media users are sharing the video claiming that it shows the eruption of Indonesia’s Anak Krakatau volcano. Research by CyberPeace found that the viral video is AI-generated. The video was created with the help of AI tools. However, four volcanoes, including Anak Krakatau, have erupted in Indonesia.
Claim
An Instagram user shared the viral video with the caption: “Indonesia’s Anak Krakatau volcano erupted Friday night. According to MAGMA Indonesia, lava fountains were seen rising from the volcano’s crater, while ash plumes reached a height of up to 400 metres. The volcano remains at Level III, with authorities enforcing a 3-kilometre exclusion zone around the crater.”
https://www.instagram.com/reels/DdBfQprThPA/
Fact Check
To investigate the viral video, we examined it closely and noticed several inconsistencies. At the beginning of the video, people can be seen standing calmly as the volcanic eruption takes place. Shortly afterward, the vehicles parked there suddenly begin moving. In one of the cars, no driver is visible. Meanwhile, the legs of a person running on the road disappear, and the person appears to merge into the background. These visual inconsistencies raised suspicions that the viral video had been created using AI tools.
We checked the video using the AI detection tool Hive Moderation, which indicated that there was a more than 94 percent likelihood that the video was AI-generated.
We checked the keyframes of the video using the AI detection tool Was It AI, which identified the video as 97 percent likely to be AI-generated.
Conclusion
The Anak Krakatau volcano in Indonesia erupted on the night of September 4, 2026. However, our research found that the video being shared in connection with the eruption was created using AI tools. Visual inconsistencies in the footage, along with the results of AI detection tools, indicate that the video is AI-generated and does not show genuine footage of the Anak Krakatau eruption. Therefore, the claim that the viral video shows the September 4 eruption of Indonesia’s Anak Krakatau volcano is false.
Introduction
You ask an app for directions to a street you've driven down a hundred times. You let autocomplete finish your sentence before you've decided what you meant to say. You take a photo of a document instead of reading it, trusting the summary a model hands back. None of these moments feel like a loss. Each one is, on its own, a reasonable trade of effort for convenience. But add them up across a year, a career, an industry, and you start to wonder what exactly we've been trading away. Every technology wave produces its own founding myth. For AI, the myth is that intelligence can be manufactured at scale, bottled into a model, and dispensed on demand - cheaper, faster, and eventually better than the human original. It's a seductive story, and one we've been telling ourselves so uncritically that we've stopped noticing what it costs.
The casualties of this bet are rarely dramatic. Nobody announces that a skill has quietly atrophied, or that a habit of independent judgement has gone unused long enough to weaken. These losses don't show up as headlines; they show up later, as gaps, when the system that was supposed to think for us turns out not to have been thinking at all. Ford Motor Company's recent decision to rehire around 350 veteran engineers, after leaning heavily on AI-driven quality systems, is a small but telling data point.¹ The lesson isn't that automation failed outright — it's that a process can be automated without the judgement that made the process work ever being captured in the first place. That distinction between automating a task and actually preserving the human expertise behind it is the real subject of this AI moment.
How Organisations Are Using AI in Decision-Making
More organisations are now leaning on AI not just to execute tasks, but to help shape decisions. Deloitte's 2026 Global Human Capital Trends survey found that 60% of executives now regularly use AI to support their decisions, and the same report cites Gartner's projection that by 2027, half of all business decisions will be augmented or automated by AI agents. Companies like Netflix and Amazon are often pointed to as examples of this working well using AI to enhance recommendations and logistics while keeping people involved in the interpretation, generating significant value in the process. Elsewhere, results have been more mixed: MIT's "State of AI in Business 2025" study found that 95% of generative AI pilots showed no measurable P&L impact within six months, often because this initiative failed to integrate feedback or adapt to context rather than because the underlying model was flawed. Critics have noted the study used a narrow definition of success (six-month, bottom-line ROI), so the figure may understate the value AI creates in ways that aren't captured on the P&L. Notably, this is not an argument against using AI. It is an argument about how we use it and why the human-in-the-loop principle, keeping people actively involved in judgement rather than passively rubber-stamping outputs, is not a compliance checkbox but the thing that determines whether automation actually works. That distinction, between automating a task and preserving the human expertise behind it, is the point of contention.
Finding the Balance
The lesson isn't to use AI less, it's to be deliberate about where it sits in the process. The strongest results come from pairing AI's speed with human judgement, not swapping one for the other. That means keeping a clear owner for important decisions, checking that the model is optimising for the right goal, and treating its output as a strong first draft rather than a final answer. Used this way, AI doesn't replace thinking, it gives good judgement more room to work.
Two Framings We Should Retire
Conversations about AI adoption keep falling into two lazy framings. The first is AI versus humans, as if technology and workforce are locked in a zero-sum contest for relevance. The second is AI versus jobs, reducing every discussion to headcount and displacement. Both are legitimate concerns, but they crowd out a more urgent question: as AI gets embedded deeper into how decisions are made, what happens to the quality of the decisions themselves? This is not a question about whether AI is useful and it plainly is. It is a question about what gets quietly outsourced along with the task, and whether anyone notices before it matters.
Why “Wisdom of Crowds” Does Not Automatically Apply to AI
A comforting analogy often gets reached for: surely, with millions of people using the same models, errors will average out, the way independent forecasters tend to converge on accurate estimates.² That analogy breaks down where it matters most. The wisdom-of-crowds effect depends on independent thinking, genuinely diverse information, and an aggregation mechanism that does not distort the signal. When millions of people query the same underlying model, those conditions collapse. Everyone draws from the same statistical engine, trained on overlapping data, tuned toward similar “safe” answers. The apparent agreement is not corroboration, it is an echo. This creates a genuinely new risk: AI can be confidently, fluently, and uniformly wrong across an entire organisation at once, without the friction that would normally surface an error in a single person's judgement.
The Casualties, Named Plainly
Several things erode quietly when organisations are not deliberate about integrating AI into decisions. Independent judgement is the first casualty of the willingness to form a view before checking what the model says. Verification effort follows: generative AI collapses retrieval and generation into one fluent output, and people invest less effort checking something that already sounds complete and well-reasoned. Diversity of thought narrows as more decision-makers lean on the same handful of models for research and drafting, quietly reducing the range of framings available when it matters most. Accountability becomes harder to trace when a recommendation generated by a model and passed along with minimal scrutiny creates a strange vacuum where a decision was made but nobody quite owns it. And informational anchoring sets in, where a signal becomes a coordination point simply because everyone is looking at it, regardless of its accuracy.
Why Human-in-the-Loop Is a Design Requirement
“Human in the loop” often becomes a rubber-stamp step rather than genuine scrutiny. That is a mistake, because the functions humans provide are structural, not decorative. Context that a model cannot infer history, relationships, unstated constraints shapes whether a reasonable-sounding answer is right in a specific situation. Domain expertise built over years lets someone recognise when a fluent answer is subtly wrong. Ethical judgement decides trade-offs a model has no standing to make on an organisation's behalf. Accountability means someone can be asked why a decision was made and answer from reasoning, not from “the system recommended it.” And the rarest function of all is the willingness to challenge a convincing answer and resisting the very fluency that makes AI output persuasive.
What This Looks Like in Practice
For organisations, the goal is not slowing AI adoption but being deliberate about where human judgement stays load-bearing. AI output should default to draft status until a qualified person has actively tested its logic against context the model lacks. Teams using the same AI tools for analysis should build in a step that actively seeks disagreement, rather than assuming convergence means correctness. Ford's decision to bring engineers back to lead design reviews is instructive: expertise, once encoded into a system, is not safe to let atrophy in the people who built it.³ Verification should be visible and required for decisions with real financial, legal, safety, or reputational consequences. And organisations should track which decisions were AI-assisted and who owned the final call, so accountability stays traceable rather than quietly disappearing.
Conclusion
Decades ago, management thinkers warned that automating a broken process only helps an organisation fail faster. The AI era raises the stakes on that warning: judgement itself, the hard-won capacity to reason well under uncertainty, can be automated away without anyone deciding to give it up. Machines already process information faster than any team of people. What they cannot yet do is originate the wisdom that comes from human experience, accountability, and the willingness to be told one is wrong. That capacity erodes not because AI is powerful, but because organisations stop deliberately exercising it. The real task ahead is not resisting AI, but ensuring that as it takes on more of the work of deciding, humans deliberately keep hold of the responsibility of deciding.
References
- https://www.assemblymag.com/articles/100186-ford-rehires-veteran-engineers-to-improve-ai-vehicle-quality
- https://finance.yahoo.com/technology/ai/articles/ford-rehires-veteran-engineers-ai-144332497.html
- https://finance.yahoo.com/technology/ai/articles/ford-rehires-more-300-engineers-162210705.html
- https://www.msn.com/en-us/money/other/ford-rehires-hundreds-of-engineers-after-ai-struggles-to-improve-quality/ar-AA26P4QB?ocid=BingNewsSerp
- https://www.foxbusiness.com/technology/ford-rehires-experienced-engineers-after-ai-misses-mark
- https://www.livemint.com/opinion/online-views/artificial-wisdom-of-crowds-jobs-crisis-ai-technology-automation-openai-model-11785009289768.html
- https://www.deloitte.com/us/en/insights/topics/talent/human-capital-trends/2026/decision-making-with-ai.html
- https://www.hpcwire.com/aiwire/2026/03/04/deloittes-state-of-ai-2026-why-enterprise-execution-is-falling-behind-adoption/ and Legal.io summary: https://www.legal.io/blog/5719519/MIT-Report-Finds-95-of-AI-Pilots-Fail-to-Deliver-ROI-Exposing-GenAI-Divide
- https://www.marketingaiinstitute.com/blog/mit-study-ai-pilots
