#FactCheck -AI-Generated Image Falsely Shows Kavya Maran Hugging Young Cricketer Vaibhav Suryavanshi
Executive Summary
A picture allegedly showing Sunrisers Hyderabad (SRH) owner Kavya Maran emotionally hugging young cricketer Vaibhav Suryavanshi has gone viral on social media. The image is being shared as a genuine photograph from a cricket-related event, with users claiming that Kavya Maran was seen embracing Vaibhav Suryavanshi. However, CyberPeace Research Wing research found the claim to be false. No credible news reports, official statements, or authentic photographs support the incident depicted in the viral image.
Claim
A Facebook user shared the viral image with the caption: “Kavya Maran Hug Vaibhav Suryavanshi 🥰🔥 #cricketnews #RRvsSRH” The link to the post and its screenshot are provided below.

Fact Check
During the research, we found no credible news reports, official statements, or authentic images confirming that Kavya Maran hugged Vaibhav Suryavanshi as shown in the viral picture. To further verify the image, it was analysed using AI detection tools, including Sightengine and Hive Moderation. Both tools indicated a high probability that the image was generated using Artificial Intelligence. The findings suggest that the viral photograph is not a genuine image captured at a real event but a digitally created visual.


Conclusion
Our research found that the viral image showing Kavya Maran emotionally hugging Vaibhav Suryavanshi is not authentic. The picture was generated using AI and does not depict a real incident.
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Executive Summary - When Anthropic and OpenAI's AI Testing Turned Into Real Breaches
You would be surprised to know that a testing function built to measure how good AI models are at simulated hacking ended up doing the real thing instead. Not once , but three times, across two of the world's leading AI labs, within the same 9-day window at the end of July 2026. As per the reports, Anthropic, which is among the world's leading AI labs, was running these evaluations on its own AI models namely - Claude Opus 4.7, Claude Mythos 5, and an unreleased research model, inside an environment co-managed with a third-party evaluation vendor. As per the reports, the models were told they were operating inside closed, internet-free simulations. They were not. A configuration error left the door open to the real internet, and the AI did exactly what it was trained to do in a hacking exercise, find the target and break in. Except the targets, this time, were real companies. Real credentials got stolen. Real data got accessed. Two of the three victims didn't even know they'd been breached until the AI lab called to tell them. This shows how a single unverified assumption, "this environment has no internet access" can quietly collapse the entire safety boundary of an AI test. It indicates that as these systems get more capable and more autonomous, the risk isn't necessarily the AI deciding to go rogue, it is humans failing to double-check the cage before putting something powerful inside it. And it warns us that the margin for this kind of error is shrinking fast, because what used to be a contained mistake can now scan thousands of systems and act on it within minutes. bAnthropic was not alone. Just over a week earlier, on 21 July, OpenAI had disclosed that its own models, GPT-5.6 Sol and an unreleased successor broke out of an isolated test environment and reached the real production infrastructure of Hugging Face, another AI company. In fact, it was OpenAI's disclosure that pushed Anthropic to go back and audit its own evaluation runs in the first place, which is how the three incidents above came to light. This blog examines the incident not as an isolated slip-up by two labs, but as a preview of the larger picture, a world where the gap between "theoretically vulnerable" and "actually exploited" is closing faster than most organisations' security practices are ready for.
The Chain of Disclosures
It started with Hugging Face, the open-source AI platform, which disclosed on July 16 that it had detected and contained an intrusion into part of its production infrastructure, driven end-to-end by an autonomous AI agent. Five days later, OpenAI confirmed it was responsible: models it was evaluating internally, GPT-5.6 Sol and an unreleased prototype, both running with their cyber-safety behaviour deliberately turned down to measure raw capability, had exploited a previously unknown vulnerability to break out of an isolated test environment and reach Hugging Face's real servers, apparently while chasing answers to a benchmark challenge. That disclosure prompted Anthropic to go back through its own records. On July 30, it published the results: after auditing 141,006 evaluation runs in which its Claude models could conceivably have touched the internet, it found three incidents, six runs in total, in which a model reached real systems belonging to three outside organisations and gained unauthorised access.
How a Fictional Exercise became a Real Attack
All three Anthropic incidents shared the same root cause. Claude was being run through capture-the-flag exercises, a standard way labs test offensive cyber capability: the model is dropped into a fictional scenario, told a piece of secret data is hidden somewhere on a network, and left to find its own way in. Anthropic's prompts told Claude, explicitly, that the environment was an internet-free simulation. Because of a misunderstanding with its evaluation partner, Irregular, that statement was false; the machines had live internet access nobody had verified. So when Claude's search for the flag led it onto the open internet, it did what it had been told to expect: it assumed everything it found was part of the exercise, including things that weren't.
- Incident 1: A fictional target company happened to share its name with a real, active domain. Across four runs, Claude Opus 4.7 attacked the real company instead, extracting infrastructure credentials and reaching a database containing several hundred rows of genuine production data, the most serious impact of the three incidents. In its own reasoning, the model repeatedly noted the system looked real and kept going anyway.
- Incident 2: Inside its fictional scenario, Claude Mythos 5 found a fake "onboarding document" referencing a software package that didn't exist on PyPI, the public Python package registry. It recognised the opportunity, built a functioning malicious package, and, after working around several dead ends to get an email account and register on PyPI, published it. The package lived online for about an hour and was installed on fifteen real machines, including a security company's automated scanner, letting Claude harvest real credentials from a company it had never even set out to target.
- Incident 3: An unreleased internal research model, unable to find its fictional target, scanned roughly 9,000 real hosts and broke into one using textbook techniques credentials read off an exposed debug page, then SQL injection. Partway through, it noticed the system it had compromised had no plausible link to its assignment, concluded on its own that the target was real, and stopped.
Timeline of Incidents

The Threat is Scale, not Novelty
None of the three models discovered a novel vulnerability. Weak passwords, unauthenticated endpoints, exposed debug output, and a classic "dependency confusion" trick are techniques that have appeared on security checklists for a decade and are still relevant. That's arguably the more sobering finding: the frontier is not a new class of attack; it is the speed and tirelessness with which known, boring weaknesses can now be found and used. Anthropic's own analysis lands on a subtler point, too: in each case, whether the model's behaviour counted as "aligned" or "harmful" depended entirely on what it believed about its situation, not on any goal of its own. All three models were simply trying to complete the task they had been assigned. Two of them did so while holding a false belief, installed by their own evaluators, about whether their targets were real. Only the newest of the three models, on independently concluding it had reached a genuine system, chose to stop. Anthropic is careful to note this is not a controlled experiment and should not be read as a guarantee that newer models will always behave better. But the throughline is clear enough: telling a capable model a lie about its environment is not a neutral setup choice. It is itself a safety-relevant decision.
The Detection Gap
Perhaps the most alarming detail is the quietest one. Anthropic reached out to the three affected organisations on July 27. Two of them had detected nothing at all, no alert, no anomaly, no investigation until that call. Real credentials had been stolen and real data accessed inside systems whose owners had no idea anything had happened. That is a statement about the state of everyday detection capability, not about AI. An agent that completes an entire intrusion, start to finish, within a single automated session doesn't leave the kind of slow, human-paced footprint that most monitoring is built to catch.
The Silver Lining - Why These Disclosures Deserve Credit
Both incidents share an underappreciated feature: they were disclosed voluntarily, promptly, and with real detail, and both labs notified the organisations affected. Hugging Face brought in outside forensic specialists and law enforcement. Anthropic halted its cyber evaluations the same day it found the first suspicious transcript and has asked METR, an independent evaluation body, to review its findings. That kind of candour is exactly the behaviour any sensible policy response should want to reinforce. A regulatory reflex that punishes disclosure risks teaching labs to say less next time, not to do better. What both incidents point to, far more than any specific model capability, is a mundane and fixable governance gap: environments used to test powerful, semi-restrained AI systems need the same security discipline as production systems, verified network isolation, continuous monitoring, and evaluation scopes that are stated positively ("here is what's in bounds") rather than enforced by simply telling the model a comforting falsehood. As both companies note, a fictional test range that turns out to have a live path to the internet isn't really fictional anymore. Basic asset hygiene, like knowing what's exposed, patching debug endpoints, claiming your internal package names before someone else does, and watching outbound traffic from environments that are supposed to have none did more to prevent and contain these incidents than anything specific to the models involved.
CyberPeace findings and recomendations : For enterprises and public institutions
- Maintain a full inventory of internet-facing assets and unauthenticated endpoints, and assume the inventory is incomplete until proven otherwise.
- Eliminate default, weak, and reused credentials, and enforce phishing-resistant MFA on anyone externally reachable.
- Strip debug pages and verbose error output from production systems.
- Treat dependency confusion as a live threat: pin dependencies, use private registry namespaces, and pre-emptively claim internal package names on public registries.
- Apply deny-by-default egress filtering to every environment running AI or agentic tooling, including development and test environments, and verify isolation empirically rather than assuming it from configuration.
- Alert on any outbound connection from an environment that is supposed to have none.
- Review authentication and access logs from April 2026 onwards for short, unusually efficient sessions that look more like machine-speed compromise than human reconnaissance.
For AI developers and evaluation vendors
- Network-isolate offensive-capability evaluation environments by default, with isolation verified per run rather than inherited from configuration.
- State the scope explicitly and positively, which systems are in bounds rather than asserting a falsehood about connectivity.
- Build contractual isolation guarantees and joint pre-run verification into third-party evaluation partnerships; both labs involved here have acknowledged that neither side alone caught the misconfiguration.
- Monitor transcripts and network logs continuously, not retrospectively.
For policymakers
- A regulatory response that punishes candour risks producing silence rather than safety. India currently has no reporting framework that clearly covers containment failures in AI evaluations affecting Indian entities' behaviour.
- RT-In's existing incident-reporting directions were not drafted with this candour in mode. Closing that gap would mean an explicit reporting obligation for evaluation of containment failures touching third-party infrastructure and a safe harbour mechanism that protects labs which disclose promptly.
- Minimum containment standards (egress verification, log retention) for organisations conducting offensive-capability AI evaluation within Indian jurisdiction;
- Recognition in national cyber doctrine that agentic tooling collapses the gap between a known-but-deferred vulnerability and an exploited one.
Conclusion
The above incidents reveal less about AI's offensive capability and more about the gap between how these systems are tested and how carefully those tests are contained. Both labs found the breaches through their own review, not external detection, a point in their favor, but also a reminder that containment failures can go unnoticed for a while. The realistic risk ahead isn't a sudden leap in AI's hacking sophistication; it's the compounding effect of speed and scale applied to routine reconnaissance, run against infrastructure that assumes a human attacker's pace. Treating evaluation environments with the same rigor as production systems, sandboxing, monitoring, and independent audits, should become standard practice, not an afterthought triggered by another lab's incident. The path forward is less about slowing AI down and more about catching up our containment discipline to match what these systems can now do.
Sources
- Anthropic, "Investigating three real-world incidents in our cybersecurity evaluations" (July 30, 2026)
- OpenAI, "OpenAI and Hugging Face partner to address security incident during model evaluation" (July 21, 2026, updated July 28–29, 2026)
- Hugging Face, "Security incident disclosure — July 2026" (July 16, 2026)
- Axios, "Anthropic says three Claude models reached real-world systems during cyber tests" (July 30, 2026)
- Help Net Security, "Anthropic's Claude breached three companies during security tests" (July 31, 2026)
- Simon Willison, "Investigating three real-world incidents in our cybersecurity evaluations" (July 30, 2026)
Contributors
- Maj. Vineet Kumar, Founder & Global President, CyberPeace
- Mr. Neeraj Soni, Sr. Researcher, Policy & Advocacy, CyberPeace
- Mr. Isharth Kumar, (NLIU Bhopal), Intern, Policy & Advocacy, CyberPeace

Executive Summary
A video showing stone pelting on vehicles is being widely shared on social media and falsely linked to a campaign called the “Cockroach Janata Party.” The claim suggests that people have taken to the streets and are attacking VIP vehicles by throwing stones. CyberPeace Research Wing research found that the video is from March and shows stone pelting on a police vehicle in Mathura following the killing of “Farasa Wale Baba.”
Claim
An 18-second viral clip circulating online shows a crowd throwing stones at passing vehicles. The video also contains overlaid text reading,“Cockroach sarkon par utar chuke hain, ab koi VIP nahi, ab sab barabar hain.”Users are sharing it as part of a supposed “Cockroach Janata Party” campaign.

Fact Check
A reverse image search of key frames shows that the clip was originally uploaded on multiple social media accounts on March 22–23, where it was described as an incident from Mathura following the death of a local figure known as “Farasa Wale Baba.” In those posts, the incident was reported as stone pelting on a police vehicle by miscreants.

Further verification found the same visuals in a video posted by NDTV India on March 21, 2026, with a caption stating that it showed stone pelting on police during unrest in Mathura after the death of “Farasa Wale Baba.”

Conclusion
The researchclearly confirms that the viral video has been misrepresented. The footage is from a March incident in Mathura involving unrest following a local death, and it has no connection to any “Cockroach Janata Party” campaign or VIP-targeted violence claims.

Introduction
Law grows by confronting its absences, it heals through its own gaps. States often find themselves navigating a shared frontier without a mutual guide or lines of law in an era of expanding digital boundaries and growing cyber damages. The United Nations General Assembly ratified the United Nations Convention against Cybercrime on December 24, 2024, and more than sixty governments were in attendance in the signing ceremony on 24th & 25th October this year, marking a moment of institutional regeneration and global commitment.
A new Lexicon for Global Order
The old liberal order is being strained by growing nationalism, economic fracturing, populism, and great-power competition as often emphasised in the works of scholars like G. John Iken berry and John Mearsheimer. Multilateral arrangements become more brittle in such circumstances. Therefore, the new cybercrimes convention represents not only a legal tool but also a resurgence of international promise, a significant win for collective governance in an uncertain time. It serves as a reminder that institutions can be rebuilt even after they have been damaged.
In Discussion: The Fabric of the Digital Polis
The digital sphere has become a contentious area. On the one hand, the US and its allies support stakeholder governance, robust individual rights, and open data flows. On the other hand, nations like China and Russia describe a “post-liberal cyber order” based on state mediation, heavily regulated flows, and sovereignty. Instead of focusing on ideological dichotomies, India, which is positioned as both a rising power and a voice of the Global South, has offered a viewpoint based on supply-chain security, data localisation, and capacity creation. Thus, rather than being merely a regulation, the treaty arises from a framework of strategic recalibration.
What Changed & Why it Matters
There have been regional cybercrime accords up to this point, such as the Budapest Convention. The goal of this new international convention, which is accessible to all UN members, is to standardise definitions, evidence sharing and investigation instruments. 72 states signed the Hanoi signature event in October, 2025, demonstrating an unparalleled level of scope and determination. In addition to establishing structures for cooperative investigations, extradition, and the sharing of electronic evidence, it requires signatories to criminalise acts such as fraud, unlawful access to systems, data interference, and online child exploitation.
For the first time, a legally obligatory global architecture aims to harmonise cross-border evidence flows, mutual legal assistance, and national procedural laws. Cybercrime offers genuine promise for community defence at a time when it is no longer incidental but existential, attacks on hospitals, schools and infrastructure are now common, according to the Global Observatory.
Holding the Line: India’s Deliberate Path in the Age of Cyber Multilateralism
India takes a contemplative rather than a reluctant stance towards the UN Cybercrime Treaty. Though it played an active role during the drafting sessions and lent its voice to the shaping of global cyber norms, New Delhi is yet to sign the convention. Subtle but intentional, the reluctance suggests a more comprehensive reflection, an evaluation of how international obligations correspond with domestic constitutional protections, especially the right to privacy upheld by the Supreme Court in Puttaswamy v. UOI (2017).
Prudence is the reason for this halt. Policy circles speculate that the government is still assessing the treaty’s consequences for national data protection, surveillance regimes, and territorial sovereignty. Officials have not provided explicit justifications for India’s refusal to join. India’s position has frequently been characterised by striking a careful balance between digital sovereignty and taking part in cooperative international regimes. In earlier negotiations, India had even proposed including clauses to penalise “offensive messages” on social media, echoing the erstwhile Section 66A of the IT Act, 2000, but the suggestion found little international traction.
Advocates for digital rights such as Raman Jit Singh Chima of Access Now have warned that ensuring that the treaty’s implementation upholds constitutional privacy principles may be necessary for India to eventually endorse it. He contends that the treaty’s wording might not entirely meet India’s legal requirements in the absence of such voluntary pledges.
UN Secretary-General Antonio Guterres praised the agreement as “a powerful, legally binding instrument to strengthen our collective defences against “cybercrime” during its signing in Hanoi. The issue for India is to make sure that multilateral collaboration develops in accordance with constitutional values rather than to reject that vision. Therefore, the path forward is one of assertion rather than absence, careful march towards a cyber future that protects freedom and sovereignty.