#FactCheck -Old Chhattisgarh ACB Bribery Case Misrepresented as ‘Cockroach Janta Party’ Action in Viral Video

Introduction

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Cyberwarfare has evolved into one of the most decisive instruments of statecraft and conflict. The increasing digitisation of critical infrastructure like power grids, water systems, transportation systems, healthcare networks, and energy sources has made these systems new targets in the war of algorithms. Military logic is evolving to paralyse the nation’s critical infrastructure to keep its resources engaged in repairing them and thereby break the nation’s ability to deter and counter attacks, all without firing a single bullet. 

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From Ransomware to an Invisible Sabotage: The changing nature of warfare

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The operational technology (OT) landscape has become the epicentre of cyber operations, all around the world. Once, which was insulated, related to industrial systems that controlled turbines, pipelines, or dams, they now stand connected to the Internet through supervisory control and data acquisition (SCADA) and the Internet of Things. These connections have also become gateways for attackers, besides enhancing the efficiency of the infrastructural lifelines of the nation.   

Groups like Volt Typhoon, Sandworm, Laurionite, and Cyberavengers have transformed the art of digital infiltration into a strategic shift. Volt Typhoon, which is linked to China, has used “living-off-the-land” techniques to exploit the legitimate administrative tools to remain invisible while scanning the critical infrastructures in the US. Sandworm, which is aligned with Russia’s GRU (Glavnoye Razvedyvatelnoye Upravlenie) or Main Intelligence Directorate (in English), has demonstrated the power of cyber sabotage in real time, as its attacks on Ukraine’s power grids in 2015 and 2021 had left millions in darkness, coinciding with kinetic missile strikes. Meanwhile, the Iranian-affiliated Cyberavengers group, which has weaponised the AI-assisted malware, such as IOCONTROL, that are capable of hijacking water and energy control systems. Each of these systems used in these operations reflects a shift from direct espionage activities to a state of strategic paralysis. 

In comparison to the traditional cybercrime activities that are aimed at stealing data and extortion of money, these campaigns repeatedly target the physical systems, which consist of the machinery that sustains civilian life and military preparedness.  

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The Military Logic behind Cyber Targeting: A Web of Vulnerabilities 

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A critical infrastructure is a complex ecosystem that covers power generation, transportation, communication, and manufacturing are all interconnected, which means a single compromised node can cascade into a national paralysis. For instance, a breach in the systems of the dam can flood an entire city, a grid shutdown can halt water supply to hospitals, and even affect air traffic. The 2015 Black Energy Malware attack in Ukraine has proved this possibility when three utilities were hacked, plunging thousands of homes into darkness. The Iranian hackers once again gained access to the Bowman Avenue Dam of New York and controlled its floodgates, which gave a chilling demonstration of the destructive reality of digital manipulation. 

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The systems remain vulnerable mainly for 3 reasons such as- 

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• Legacy Architectures: Many of these industrial systems were designed decades ago with no built-in cybersecurity mechanisms. 
• Slow Patching and Segmentation Gaps: All updates and segmentation between IT and TO networks often lag, providing open entry points for attackers. 
• Converging with IoT: The integration of smart sensors and cloud-based management tools has expanded the attack surface exponentially. 

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This interconnected fragility has turned our critical infrastructures into both a weapon and a target or a tool for coercion in modern hybrid warfare. Between 2023 and 2024, over 420 cyberattacks were witnessed in several critical global infrastructures, which averaged to 13 attacks per second, according to a news report. These were not just random acts of digital vandalism; they were deliberate and coordinated operational attempts by state-led actors from China, Russia, and Iran. 

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Developing a new Resilience as the new tool of Deterrence 

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Cyber deterrence no longer rests on the fear of retaliation, it relies on the need for resilience. Nations that can absorb attacks, maintain continuity, and recover rapidly would be the true superpowers of this digital age. Segmentation, real-time threat detection, and AI-assisted recovery models are vital pillars of this model of resilience. The logic of modern cyberwarfare is clear, which means that the more a nation digitizes, the more it will need to defend itself. 

However, as the line between war and peace blurs, safeguarding critical infrastructure is no longer just an IT priority; rather, it is a national security doctrine. In this silent theatre of cyberwarfare, survival will depend not only on firepower, but on firewalls. 

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References

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• https://rmcglobal.com/critical-infrastructure-under-siege-the-top-ot-threats-of-2025/
• https://ccdcoe.org/uploads/2018/10/Geers2009_The-Cyber-Threat-to-National-Critical-Infrastructures.pdf
• https://www.researchgate.net/publication/335752979_Cybersecurity_of_Critical_Infrastructure 
• https://arxiv.org/html/2510.04118v1 ‍
• https://www.anapaya.net/blog/top-5-critical-infrastructure-cyberattacks

Introduction

Artificial intelligence is often hailed as a democratiser of knowledge, opportunity and skill. It is set to improve diagnostics, personalised learning, and productivity to boost the economy, which can assist millions of people to leave poverty. However, this may be an incomplete picture. A report of the United Nations Development Programme in 2025 tells a more complex tale. The Next Great Divergence: Why AI May Widen Inequality Between Countries cautions that, unless acts are taken to intervene, AI will not alleviate inequality between countries but will instead concentrate benefits in already advantaged economies and increase risks in more vulnerable ones.

Two Gaps, One Crisis

AI is not going to create a level playing field: it has been injected into a world where there is unprecedented inequality. The report outlines two structural asymmetries that will influence the ways in which its effects manifest: a capability gap and a vulnerability gap. 

Those countries that have high connectivity, skills, compute and regulation will be in a position to reap a greater portion of the AI dividend. Others will be exposed to greater risks of job losses, information exclusion, misinformation, and the indirect consequences of increased energy and water demands. 

The centre of this transition is the Asia-Pacific region, that harbors a population of more than 55 per cent of the world. More than half of the global AI users are now located in the region, but the initial positions are quite different. Nations such as Singapore and South Korea are already spending a lot of money on AI infrastructure, with others still striving to offer basic broadband services. Two out of three individuals already use AI tools in certain high-income economies. In most countries with low incomes, the utilisation is lower. Such figures are important as they depict not only a gap in technology but also a structural difference in terms of who controls AI and who is controlled by the latter.

When Inequality Becomes a Trust Problem

Any trusted technological system is based on three tenets: transparency, fairness and accountability. AI inequality negatively impacts all three.

If governments implement imported AI systems in areas with limited technical capability, with limited transparency on their operation, their construction, and their biases. Citizens do not really trust when decision-making systems are black boxes and domestic institutions lack the know-how to question them.

Data exclusion also interferes with fairness. The AI systems trained with the datasets not sufficiently representative of the rural population, linguistic minorities, and women will generate poorer results in those groups systematically. Since South Asian women are much less likely to own a smartphone,  this impacts their representation in digital data, and consequently in any AI system trained on such data. 

Safety Risks Are Not Evenly Distributed

The lack of trust has a direct safety aspect. For example, those countries that have less robust information ecosystems have a greater exposure to AI-generated misinformation that can bias the discourse of the populace, alter elections, and cause violence. They also have the weakest capability of screening, tagging, or combating such content.

The same can be said about labour markets. The very same technologies that can speed up marginalisation and destabilise governance increase human insecurity, especially among employees in the informal economy with weak social security. The UNDP report points out that the exposure of female employment to disruption by AI is disproportionate to that of male employment, which further presents a gendered dimension in an already unequal situation.

Risks of infrastructure are skewed as well. Large AI systems may create disproportionately high energy and water demands on countries that host the data infrastructure without there being an equivalent economic payback. The environmental cost is local while profits are outsourced. Dangers of AI spread downwards, and the advantages go upwards.

The Governance Gap and Regulatory Arbitrage

Governance is perhaps the most important aspect. There are only a few states that presently have extensive AI regulation systems. This gives rise to a patchy landscape, in which safety standards differ dramatically and where companies have an incentive to install systems in jurisdictions that have weaker regulation.

The main reason is the lack of capability, as expressed by Philip Schellekens, chief economist of the UNDP in Asia and the Pacific, who says that those countries that invest in skills, computing power and well-run governance structures will gain. The rest will be left far behind. 

This departure has its ramifications outside the nations. When users in other areas are subjected to widely different rates of safety and equity by the same international platforms, the concept of uniform digital norms would no longer be sustainable. Confidence in AI systems is lost not only locally but also on a global scale.

Way Forward

The UNDP report makes it clear that there is no inevitability of divergence. To avert it, however, it is necessary to consider AI governance as a development, rather than a technology problem.

The capacity to govern should be constructed and not presumed. This implies assisting countries in establishing regulatory systems, institutional capacity, and facilitating cross-border collaboration on standards. It can also imply considering some AI features as a public good, with common models and open standards that do not allow a few firms or states to become too powerful.

The UNDP articulates the problem in a simple manner: in the end, the world's people and not machines must decide on what technologies should be given priority and how to utilise them optimally.

Conclusion

AI inequality is often framed as an economic divergence story. But its implications run deeper. It reshapes who is protected, who is visible in data, and who has the power to challenge harmful outcomes. The risk is not just that some countries fall behind economically. It is that the global digital ecosystem fragments into zones of high trust and low trust, high protection and low protection. The choices made now will determine which path prevails. AI can reinforce existing divides or help bridge them. 

But that outcome will not be decided by the technology itself. It will be decided by how societies choose to distribute access, power, and responsibility in the systems they build.

References

1. https://www.undp.org/sites/g/files/zskgke326/files/2025-12/undp-rbap-the-next-great-divergence_1.pdf
2. https://www.undp.org/asia-pacific/press-releases/ai-risks-sparking-new-era-divergence-development-gaps-between-countries-widen-undp-report-finds
3. https://www.undp.org/asia-pacific/blog/next-great-divergence-how-ai-could-split-world-again-if-we-dont-intervene
4. https://www.aljazeera.com/news/2025/12/2/ai-threatens-to-widen-inequality-among-states-un
5. https://www.undp.org/asia-pacific/next-great-divergence
6. https://www.eco-business.com/press-releases/ai-risks-spark-new-era-of-divergence-as-development-gaps-widen-undp-report/

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Introduction

Recently in July 2026, India's Cyber Crime Coordination Centre (I4C) under the Ministry of Home Affairs quietly tried to do something almost no government has managed before: switch off an app that doesn't need the internet to work.  On July 23, 2026, I4C sent takedown notices to Google, Apple and GitHub, ordering them to pull three offline messaging apps – like BitChat, Briar and Bridgefy – from the Play Store, App Store and GitHub's code repository, respectively, giving a three-hour deadline. The notices followed a period of student-led demonstrations at Jantar Mantar, New Delhi, associated with a group "Cockroach Janata Party," a period that also saw a mobile internet shutdown in parts of central Delhi. When Twitter co-founder Jack Dorsey, who built and open-sourced BitChat, publicised the GitHub notice on X, the episode made international news. Google and Apple got near-identical orders the same night, and telecom operators were reportedly told, and then just as quickly untold, to block the apps at the network level. By July 29, all three apps were still live on both app stores, and BitChat's code was still on GitHub. This incident is worth unpacking carefully, because it sits at the intersection of three things most people care about but rarely see explained together: how this technology actually works, what the law actually allows, and why an app can be "banned" on paper while still working perfectly on your phone.

What makes these apps different

Ordinary apps like WhatsApp or Telegram are centralised: your message travels from your phone to a company's server, and then to the recipient's phone. Block or seize the server, and communication stops. BitChat, Briar and Bridgefy are built differently. They use Bluetooth mesh networking, a system where nearby phones talk directly to each other, and each device also relays messages onwards to phones further away, like a bucket brigade. No message ever touches a central server. Briar adds a further layer by routing traffic over Tor, an anonymity network, when internet access is available, and falls back to Bluetooth or Wi-Fi Direct when it isn't. Bridgefy is tuned for larger crowds, useful during concerts, natural disasters, or protests where thousands of phones are packed into a small area and cellular networks buckle under the load. This design, often called decentralised or peer-to-peer communication, is precisely why these apps are useful during disasters and precisely why they worry law enforcement: they keep working when the internet doesn't, whether that's because a cyclone knocked out cell towers or because the government itself ordered a shutdown.

The legal machinery behind a takedown notice

India's power to block online content mainly comes from Section 69A of the Information Technology Act, 2000, which lets the central government order blocking on grounds like sovereignty, public order or preventing incitement to an offence  but only through a defined process set out in the IT (Blocking) Rules, 2009: a designated officer, a review committee, and recorded written reasons. The Supreme Court examined this exact provision in its landmark 2015 ruling, Shreya Singhal v. Union of India. While the judgement is best remembered for striking down the vague "offensive speech" law under Section 66A, it separately upheld Section 69A specifically because it came with procedural guardrails, a reasoned order, an opportunity to be heard, and the possibility of judicial review that stopped it from becoming an unchecked censorship tool. The July 23 notices, however, reportedly leaned on a different lever: Section 79(3)(b) of the IT Act, read with Rule 3(1)(d) of the IT Intermediary Guidelines and Digital Media Ethics Code Rules, 2021. That provision governs when an intermediary loses its legal immunity ("safe harbour") for user content if it fails to act on a government or court order,  a mechanism built for content takedowns, not necessarily for pulling an entire app off a store shelf within three hours. Legal commentators have flagged this as significant, since Shreya Singhal itself read down Section 79(3)(b) to require action only pursuant to a court order or a properly authorised government direction, not an informal notice. This isn't the first time a mesh-messaging app has run into this machinery. In 2023, following an I4C request, the government blocked Briar and thirteen other apps in Jammu and Kashmir under Section 69A, citing use, the first known instance of Section 69A being used for a regional block. Briar's developers challenged this in the Delhi High Court; in 2024, the court dismissed the challenge, holding that principles of natural justice can give way in matters of national security.

Why you can't easily switch off a mesh network

Here's the technical wrinkle that made the July order largely symbolic: removing an app from the Play Store stops new downloads, but it does nothing to phones that already have it installed, and it does nothing at all to the Bluetooth radios exchanging messages between those phones. Unlike an internet shutdown, which works by controlling the pipes that all traffic must pass through, a mesh network has no chokepoint, no server to seize, no IP address to blacklist, and no single company to compel.

GitHub, for its part, said it followed its standard process of notifying the account holder and offering an appeal before taking any action, which is one reason BitChat's source code stayed publicly accessible throughout. Within a day, officials reportedly told the companies orally that enforcement wasn't necessary after all, though no public clarification or official document has been released explaining why the notices were issued or withdrawn.

Two legitimate, competing interests

None of this means the government's underlying worry is baseless. Law enforcement agencies genuinely lose visibility when communication moves off networks they can lawfully intercept, and coordination of unlawful assembly or violence is a real concern during volatile protests. 

The transparency gap

The single biggest problem with how this played out isn't the underlying concern  it's the absence of a public, reasoned order. Under the blocking rules, disclosure is restricted, and courts, including the Supreme Court in Anuradha Bhasin v. Union of India, have said that when access is restricted, reasons must be recorded and, where possible, made available. A three-hour notice, issued and then informally withdrawn without explanation, sits uneasily with that standard. A more durable approach,  one that CyberPeace and other digital-rights researchers have called for, would combine clearly identified statutory authority; published (even if redacted) reasoning; proportionality review; and investment in lawful digital forensics, rather than blanket app-store takedowns that decentralised technology is, by design, built to survive.

CyberPeace's policy recommendations

Alongside the legal analysis above, CyberPeace puts forward a ten-point framework for how India should approach decentralised communication technologies going forward, instead of defaulting to blanket takedowns:

• Strengthen transparency in blocking decisions
• Ensure statutory clarity
• Apply legality, necessity and proportionality
• Differentiate technology from misuse
• Invest in advanced investigative capabilities
• Establish a multi-stakeholder advisory mechanism
• Develop a framework for emerging decentralised technologies
• Promote responsible innovation
• Enhance public awareness
• Foster international cooperation

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Conclusion

The referred incident illustrates that regulating decentralised technologies requires more than swift takedown notices. As communication networks become increasingly resilient and distributed, effective governance must combine legal certainty, technical realism, transparency, and proportionate enforcement. India's challenge is not simply to regulate emerging technologies but to develop a kind of regulatory framework that safeguards national security and the constitutional values of privacy, free expression, and due process.

Sources

• MediaNama — Bitchat was not the only mesh-messaging app targeted by a government takedown notice
• Outlook Business — Beyond GitHub, Govt Also Directed Google To Take Down Bitchat, Briar And Bridgefy
• The Wire — Government Asks GitHub to Remove Bluetooth Messaging App Bitchat Over Concerns of 'Misuse'
• The Tech Trace (Substack) — The Indian govt's crackdown on Bluetooth-enabled messaging apps that wasn't?
• Bar and Bench — Section 69A IT Act and the expanding architecture of digital censorship in India
• Supreme Court Observer — X relies on 'Shreya Singhal' in arbitrary content-blocking case in Karnataka HC
• LiveLaw — Internet Freedom, Shreya Singhal v Union of India, IT Act, Blocking Rules 2009
• Manupatra — Full text, Shreya Singhal v. Union of India (2015) 5 SCC 1
• Open Magazine — CJP Protests at Jantar Mantar: How Offline Mesh Messaging Apps Powered a Network of Resistance