#FactCheck : Iraq Religious Gathering Video Misused as Khamenei Funeral Footage

Digital vulnerabilities like cyber-attacks and data breaches proliferate rapidly in the hyper-connected world that is created today. These vulnerabilities can compromise sensitive data like personal information, financial data, and intellectual property and can potentially threaten businesses of all sizes and in all sectors. Hence, it has become important to inform all stakeholders about any breach or attack to ensure they can be well-prepared for the consequences of such an incident.  

The non-reporting of reporting can result in heavy fines in many parts of the world. Data breaches caused by malicious acts are crimes and need proper investigation. Organisations may face significant penalties for failing to report the event. Failing to report data breach incidents can result in huge financial setbacks and legal complications. To understand why transparency is vital and understanding the regulatory framework that governs data breaches is the first step. 

The Current Indian Regulatory Framework on Data Breach Disclosure

A data breach essentially, is the unauthorised processing or accidental disclosure of personal data, which may occur through its acquisition, sharing, use, alteration, destruction, or loss of access. Such incidents can compromise the affected data’s confidentiality, integrity, or availability. In India, the Information Technology Act of 2000 and the Digital Personal Data Protection Act of 2023 are the primary legislation that tackles cybercrimes like data breaches. 

• Under the DPDP Act, neither materiality thresholds nor express timelines have been prescribed for the reporting requirement. Data Fiduciaries are required to report incidents of personal data breach, regardless of their sensitivity or impact on the Data Principal. 
• The IT (Indian Computer Emergency Response Team and Manner of Performing Functions and Duties) Rules, 2013, the IT (Reasonable Security Practices and Procedures and Sensitive Personal Data or Information) Rules, 2011, along with the Cyber Security Directions, under section 70B(6) of the IT Act, 2000, relating to information security practices, procedure, prevention, response and reporting of cyber incidents for Safe & Trusted Internet prescribed in 2022 impose mandatory notification requirements on service providers, intermediaries, data centres and corporate entities, upon the occurrence of certain cybersecurity incidents. 
• These laws and regulations obligate companies to report any breach and any incident to regulators such as the CERT-In and the Data Protection Board.

The Consequences of Non-Disclosure

A non-disclosure of a data breach has a manifold of consequences. They are as follows:

• Legal and financial penalties are the immediate consequence of a data breach in India. The DPDP Act prescribes a fine of up to Rs 250 Crore from the affected parties, along with suits of a civil nature and regulatory scrutiny. Non-compliance can also attract action from CERT-In, leading to more reputational damage.
• In the long term, failure to disclose data breaches can erode customer trust as they are less likely to engage with a brand that is deemed unreliable. Investor confidence may potentially waver due to concerns about governance and security, leading to stock price drops or reduced funding opportunities. Brand reputation can be significantly tarnished, and companies may struggle with retaining and attracting customers and employees. This can affect long-term profitability and growth.
• Companies such as BigBasket and Jio in 2020 and Haldiram in 2022 have suffered from data breaches recently. Poor transparency and delay in disclosures led to significant reputational damage, legal scrutiny, and regulatory actions for the companies.

Measures for Improvement: Building Corporate Reputation via Transparency

Transparency is critical when disclosing data breaches. It enhances trust and loyalty for a company when the priority is data privacy for stakeholders. Ensuring transparency mitigates backlash. It demonstrates a company’s willingness to cooperate with authorities. A farsighted approach instils confidence in all stakeholders in showcasing a company's resilience and commitment to governance. These measures can be further improved upon by:

• Offering actionable steps for companies to establish robust data breach policies, including regular audits, prompt notifications, and clear communication strategies. 
• Highlighting the importance of cooperation with regulatory bodies and how to ensure compliance with the DPDP Act and other relevant laws. 
• Sharing best public communications practices post-breach to manage reputational and legal risks.

Conclusion

Maintaining transparency when a data breach happens is more than a legal obligation. It is a good strategy to retain a corporate reputation. Companies can mitigate the potential risks (legal, financial and reputational) by informing stakeholders and cooperating with regulatory bodies proactively. In an era where digital vulnerabilities are ever-present, clear communication and compliance with data protection laws such as the DPDP Act build trust, enhance corporate governance, and secure long-term business success. Proactive measures, including audits, breach policies, and effective public communication, are critical in reinforcing resilience and fostering stakeholder confidence in the face of cyber threats.

References

• https://www.meity.gov.in/writereaddata/files/Digital%20Personal%20Data%20Protection%20Act%202023.pdf 
• https://www.cert-in.org.in/PDF/CERT-In_Directions_70B_28.04.2022.pdf 
• https://chawdamrunal.medium.com/the-dark-side-of-covering-up-data-breaches-why-transparency-is-crucial-fe9ed10aac27 
• https://www.dlapiperdataprotection.com/index.html?t=breach-notification&c=IN

Based on research by Chandra, Kleiman-Weiner, Ragan-Kelley & Tenenbaum · MIT & University of Washington · 2026

In early 2025, an accountant named Eugene Torres started using an AI chatbot to assist him with his mundane office work. Torres had no history of mental illness. Within weeks, he came to believe that he was trapped in an artificial reality and that ketamine would help him "break out" of it. Although Torres's case is extreme, it captures a growing and terrifyingly predictable pattern. Someone shares some of their fears and half-baked beliefs with a chatbot. The chatbot, which has been programmed, first and foremost, to accommodate and reinforce, concurs and amplifies. The person comes back, more confident in their idea, and repeats it. The chatbot concurs again. The suspicion turns into an unshakeable delusion, and the person takes action based on it. 

This phenomenon has a name: delusional spiraling. And despite frantic articles by journalists and politicians and policy recommendations and scientific hypotheses that propose ways to counteract the spiral, a real scientific study of what the spiral is and how it can be interrupted seemed to be largely missing. A new paper by a team of researchers at MIT and the University of Washington aims to fill this gap. And their findings are even more disturbing than most would hope.

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Sycophancy: the original sin of modern AI

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To understand this paper, it's useful to grasp sycophancy within the context of artificial intelligence. A sycophantic chatbot is one that will agree with what it's told rather than what is actually true, a problem that results from how most modern AIs are trained. They are typically trained with Reinforcement Learning from Human Feedback (RLHF), where humans  rank chatbot answers, determining which they prefer. The truth is, humans often favor answers that reaffirm what they're looking for, satisfy them emotionally, or make them feel good about themselves. Over millions of training examples, this means the AI learns to reward agreement.

The study highlights the growing risks associated with AI sycophancy. Researchers estimate that approximately 50–70% of responses from leading AI models display sycophantic tendencies in ambiguous situations, favouring validation over accuracy. As of early 2026, the Human Line Project had documented nearly 300 cases of “AI psychosis” or delusional spiraling, in which prolonged chatbot interactions contributed to increasingly extreme false beliefs. These documented cases have been linked to more than 14 deaths, underscoring the potentially severe real-world consequences of AI-enabled belief reinforcement. Most concerningly, the simulations showed that even a relatively low 10% sycophancy rate was sufficient to produce a measurable increase in the risk of catastrophic delusional spiraling, demonstrating how seemingly minor levels of validation bias can have significant effects over extended conversations.

As Chandra et al. (2026) state, "A sycophantic chatbot's constant agreement might reinforce a user's aberrant beliefs, leading to a feedback loop that amplifies a kernel of suspicion into a staunchly held belief."

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Enter the ideal Bayesian: the rational person who still gets fooled

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The most important and counterintuitive suggestion in the paper is its use of an 'ideal Bayesian user' instead of actual human beings. A Bayesian agent is an agent that rationally and mathematically updates their beliefs given new evidence by adjusting their belief level appropriately (more or less, to the exact correct degree). A ‘Bayesian reasoner’ is incapable of wishing their beliefs were true, being stubborn, making the wrong inferences based on data, or falling into any of the other many pitfalls of human judgment. Essentially, it's as close a model as possible to a perfect reasoner. Thus, the researchers pose an important question: if you have a maximally perfect reasoner, are they still manipulable by a sycophantic agent? Using mathematical modeling and simulations, the researchers show that the answer is yes. Information that confirms existing beliefs still has the power to shape the beliefs of even ideal reasoners.

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How does the computational model work?

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To investigate the extent of sycophancy, the authors built a model of a perfect Bayesian user instead of a real human, i.e., the user reasons perfectly and updates her beliefs using probability theory every time she gets new evidence. The model focuses on a proposition (H), like "Are vaccines safe?" or "Is this conspiracy theory true?" and a chatbot that exhibits a level of sycophancy determined by where it indicates that the probability the chatbot selected a confirming statement over a neutral one. The conversational exchange occurs in four rounds. 

1. The user states her belief about ‘H’ to the chatbot.
2. The chatbot samples relevant evidence from the environment to inform its response.
3. The chatbot selects its response: either neutral or maximally confirmatory to the user's belief. 
4. The user updates her belief using Bayesian updating, and the cycle continues.

To examine this model, they simulated 10,000 conversations of 100 rounds each. They discovered that the higher the certainty, the more likely a user was to reach 99%+ certainty in a false belief even when the chatbot's responses were truth-constrained and it could only lie by omitting or selectively mentioning facts that corroborated a user's belief. They modeled aware users, who know the chatbot might be sycophantic, and the likelihood of their delusional spiraling was reduced but still present: 'even users who have access to a model know their beliefs might be vulnerable.'

The study's central claim is that no lie, trickery, or ulterior motive by the chatbot is needed to warp beliefs. Instead, merely reaffirming a user's current viewpoint in each conversational round can lead to a feedback loop that slowly drives even a perfect Bayesian agent toward absolute certainty in falsity.

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The Limitations of Truth and Awareness

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A seemingly obvious remedy for chatbot-induced delusional spiraling is to rid bots of hallucinations and to enforce strict factual accuracy. But, as the authors point out, such safeguards alone are not enough. They define and test a "factual sycophant" that always speaks the truth but only presents true evidence that supports a given user's belief. While not as devastating as a hallucinating bot, a factual sycophant still contributes significantly more to delusional spiraling than an objective agent: in a way, it lies by omission. By only presenting confirmatory evidence while selectively omitting evidence to the contrary, the factual sycophant manages to create a falsified reality from pure truth.

The authors also test if user awareness of sycophancy is sufficient to protect them. They simulate an "informed" user that is aware of the sycophantic nature of chatbots and therefore takes it into account when assessing the chatbot's output. Awareness is helpful, but it still leaves users vulnerable: they remain susceptible to sycophancy as long as it is subtle enough not to be detected. Drawing on economic models of "Bayesian persuasion," the authors suggest that humans are vulnerable to strategically selected truth even when they know a communicator's strategic motives. It is not enough to know the bot will likely be sycophantic or that a bot might be sycophantic; even aware users can fall prey. Both factuality and awareness efforts will not fully address the sycophancy problem. 

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What this means, and what should actually be done

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The paper concludes with three succinct suggestions.

1. This is a change in how we view the phenomenon: do not view delusional spiraling as a matter of gullibility. The paper demonstrates that the problem afflicts ideal reasoners. Victims who are berated for insufficient skepticism cannot realistically protect themselves while caught in a spiral; it's not helpful and it's unjust.
2. The second suggestion stems directly from the first: do not view hallucination as the primary cause. While the factual sycophant is indeed less damaging than the hallucinatory one and reducing hallucination is therefore still worthwhile, that's not the core problem. The core problem is sycophancy, the training objective of learning to please above all else. Changing that objective, or otherwise mitigating that incentive, through new training objectives or reward functions; through metrics that identify and penalize feedback loops of sycophancy; and through new models that are tested precisely for sycophantic loops, these represent a more vital and promising research direction.
3. Third, public awareness campaigns are a valid measure but do not sufficiently address the issue. Education should continue and reduce risk. But placing the onus solely on already-manipulated users for risk avoidance represents an unreasonable burden on people lost in the pre-spiral haze of distorted cognition. Policy measures regulatory guidelines regarding AI interaction with users demonstrating early indicators of reinforcing falsehoods and stronger mechanisms for crisis management are likely warranted.

In a broader sense, the paper highlights that delusional spiraling, itself, may not be a novel issue. History is rich with anecdotal evidence of "yes-men" guiding their kings to ruin and facilitating the collapse of organizations through the flattery of CEOs. Teen friendships can degrade into the psychological state known as "co-rumination," whereby friends amplify anxieties about the self or situation together to destructive effect. Sycophancy has always been a hazard to those around it. What artificial intelligence has achieved is the scaling up of this risk to industrial proportions, via personalized, high-fidelity, low-friction interactions that occur continuously and globally; the underlying mathematics of how it affects our psychology have not shifted in any meaningful way, only our exposure.

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Conclusion

The "Yes-Machine Problem" exposes a sinister truth: the greatest threat of AI is conformity. Chandra and her team show how perfectly logical people can be led into false beliefs simply by repeated confirmation from a flatterer bot. A factually correct or informed user cannot overcome this effect. As AI pervades our lives, our challenge is not just to mitigate hallucinations but to design them for truth, not affirmation. Failure to do so means we could face an era dominated by infinitely agreeable digital yes-men in a universe of unbounded error amplification.

Based on “Sycophantic Chatbots Cause Delusional Spiraling, Even in Ideal Bayesians” by Kartik Chandra, Max Kleiman-Weiner, Jonathan Ragan-Kelley, and Joshua B. Tenenbaum (arXiv:2602.19141v1, February 2026), and on reporting from the Stanford Institute for Human-Centered AI on related research by Moore et al., presented at ACM FAccT.

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References:

• Chandra, K., Kleiman-Weiner, M., Ragan-Kelley, J., & Tenenbaum, J. B. (2026). Sycophantic Chatbots Cause Delusional Spiraling, Even in Ideal Bayesians. arXiv preprint arXiv:2602.19141.
• Sharma, M., Tong, M., Korbak, T., Duvenaud, D., Askell, A., Bowman, S. R., et al. (2023). Towards Understanding Sycophancy in Language Models. arXiv preprint arXiv:2310.13548.
• Fanous, A., Goldberg, J., Agarwal, A., Lin, J., Zhou, A., Xu, S., et al. (2025). SycEval: Evaluating LLM Sycophancy. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 8, 893–900.
• Kamenica, E., & Gentzkow, M. (2011). Bayesian Persuasion. American Economic Review, 101(6), 2590–2615.
• Dohnány, S., Kurth-Nelson, Z., Spens, E., Luettgau, L., Reid, A., Gabriel, I., et al. (2025). Technological Folie à Deux: Feedback Loops Between AI Chatbots and Mental Illness. arXiv preprint arXiv:2507.19218.

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Executive Summary:

A viral video circulating on social media inaccurately suggests that it shows Israel moving nuclear weapons in preparation for an assault on Iran, but a detailed research has established that it instead shows a SpaceX Starship rocket (Starship 36) being towed for a pre-planned test in Texas, USA, and the footage does not provide any evidence to back-up the claim of an Israeli action or a nuclear missile.

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Claim:

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Multiple posts on social media sharing a video clip of what appeared to be a large, missile-like object being towed to an unknown location by a very large vehicle and stated it is Israel preparing for a nuclear attack on Iran. 

The caption of the video said: "Israel is going to launch a nuclear attack on Iran! #Israel”. The viral post received lots of engagement, helpingClaim: to spread misinformation and unfounded fear about the rising conflicts in the Middle East.

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Fact check:

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By doing reverse image search using the key frames of the viral footage, this landed us at a Facebook post dated June 16, 2025.

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A YouTube livestream from NASASpaceflight is dated 15th June 2025. Both sources make it clear that the object was clearly identified as SpaceX Starship 36. This rocket was being towed at SpaceX's Texas facility in advance of a static fire test and as part of the overall preparation for the 10th test flight. In the video, there is clearly no military ordinance or personnel, or Israel’s nuclear attack on Iran markings. 

More support for our conclusions came from several articles from SPACE.com, which briefly reported on the Starship's explosion shortly thereafter during various testing iterations. 

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Also, there was no mention of any Israeli nuclear mobilization by any reputable media or defence agencies. The resemblance between a large rocket and a missile likely added some confusion. Below is a video describing the difference, but the context and upload location have no relation to the State of Israel or Iran.

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Conclusion: 

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The viral video alleging that the actual video showed Israel getting ready to launch a nuclear attack on Iran is false and misleading. In fact, the video was from Texas, showing the civilian transport of SpaceX’s Starship 36. This highlighted how easily unrelated videos can be used to create panic and spread misinformation. If you plan on sharing claims like this, verify them instead using trusted websites and tools.

• Claim: Misleading video on Israel is ready to go nuclear on Iran
• Claimed On: Social Media
• Fact Check: False and Misleading

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