#FactCheck - AI-Generated Video Falsely Claims Death of Iran’s Supreme Leader

Introduction

In the hyper-connected era, something as mundane as charging your phone can become a gateway to cyberattacks. A recent experience of Assam Chief Minister Himanta Biswa Sarma has reignited fears of an emerging digital menace called juice jacking. Sarma, who was taking an Emirates flight from Delhi to Dubai, used an international charger and cable provided by another passenger on board. As he afterwards reported on X (formerly Twitter), the passenger got off while he slept and so could not return the borrowed items. Though most people admired the CM's humility and openness, cybersecurity experts and citizens were quick to point out a possible red flag, that it could be a juice-jacking attempt. Whether by design or not, the scene calls out to the concealed risks of using unfamiliar charging equipment, particularly for those who hold sensitive roles.

What Is Juice Jacking?

Juice jacking takes advantage of the multi-purpose nature of USB connectors, which can carry both electrical energy and information. Attackers hack USB ports or cables to either:

• Insert harmful payloads (malware, spyware, ransomware) during power transfer, or
• Create unauthorised data pathways for silent information exfiltration.

Types of Juice Jacking Attacks

1. Data Theft (Exfiltration Attack): The USB cable or port is rigged to silently extract files, media, contacts, keystrokes, or login information from the attached phone.
2. Malware Injection (Payload Attack): The USB device is set to impersonate a Human Interface Device (HID), such as a keyboard. It sends pre-defined commands (shell scripts, command-line inputs) to the host, loading backdoors or spying tools.
3. Firmware Tampering: In more sophisticated cases, attackers implement persistent malware at the bootloader or firmware level, bypassing antivirus protection and living through factory resets.
4. Remote Command-and-Control Installation: Certain strains of malware initiate backdoors to enable remote access to the device over the internet upon reconnection to a live network.

Why the Assam CM’s Incident Raised Flags 

Whereas CM Sarma's experience was one of thanks, the digital repercussions of this scenario are immense:

• High-value targets like government officials, diplomats, and corporate executives tend to have sensitive information.
• A hacked cable can be used as a spy tool, sending information or providing remote access.
• With the USB On-The-Go (OTG) feature in contemporary Android and iOS devices, an attacker can run autorun scripts and deploy payloads at device connect/disconnect.
• If device encryption is poor or security settings are incorrectly configured, attackers may gain access to location, communication history, and app credentials.

Technical Juice Jacking Indicators

The following are indications that a device could have been attacked:

• Unsolicited request for USB file access or data syncing on attaching.
• Faster battery consumption (from background activities).
• The device is acting strangely, launching apps or entering commands without user control.
• Installation of new apps without authorisation.
• Data consumption increases even if no browsing is ongoing.

‍

CyberPeace Tech-Policy Advisory: Preventing Juice Jacking

‍

1. Hardware-Level Mitigation
   
   1. Utilise USB Data Blockers: Commonly referred to as "USB condoms," such devices plug the data pins (D+ and D-), letting only power (Vcc and GND) pass through. This blocks all data communication over USB.
   2. Charge-Only Cables: Make use of cables that physically do not have data lines. These are specifically meant to provide power only.
   3. Carry a Power Bank: Use your own power source, if possible, for charging, particularly in airports, conferences, or flights.

2. Operating System(OS) Level Protections

1. iOS Devices:

‍

Enable USB Restricted Mode:

Keep USB accessories from being able to connect when your iPhone is locked.

Settings → Face ID & Passcode → USB Accessories → Off

‍

2. Android Devices:

Disable USB Debugging:

Debugging makes device access available for development, but it can be taken advantage of. If USB Debugging is turned on, and someone connects your phone to a computer, they might be able to access your data, install apps, or even control your phone, especially if your phone is unlocked. Hence, it should be kept off. 

Settings → Developer Options → USB Debugging → Off

‍

3. Set USB Default to 'Charge Only'

Settings → Connected Devices → USB Preferences → Default USB Configuration → Charge Only

‍

3) Behavioural Recommendations

• Never take chargers or USB cables from strangers.
• Don't use public USB charging points, particularly at airports or coffee shops.
• Turn full-disk encryption on on your device. It is supported by most Android and all iOS devices.
• Deploy endpoint security software that can identify rogue USB commands and report suspicious behaviour.
• Check cables or ports physically, many attack cables are indistinguishable from legitimate ones (e.g., O.MG cables).

Conclusion

"Juice jacking is no longer just a theoretical or obscure threat. In the age of highly mobile, USB-charged devices, physical-layer attacks are becoming increasingly common, and their targets are growing more strategic. The recent case involving the Assam Chief Minister was perhaps harmless, but it did serve to underscore a fundamental vulnerability in daily digital life. As mobile security becomes more relevant to individuals and organisations worldwide, knowing about hardware-based attacks like juice jacking is essential. Security never needs to be sacrificed for convenience, particularly when an entire digital identity might be at risk with just a single USB cable.

References

• https://www.indiatoday.in/trending-news/story/assam-chief-minister-himanta-biswa-sarma-x-post-on-emirates-passenger-sparks-juice-jacking-concerns-2706349-2025-04-09
• https://www.cert-in.org.in/s2cMainServlet?pageid=PUBVLNOTES02&VLCODE=CIAD-2016-0085
• https://www.fcc.gov/juice-jacking-tips-to-avoid-it
• https://www.cyberpeace.org/resources/blogs/juice-jacking
• https://support.apple.com/en-in/HT208857
• https://developer.android.com/studio/debug/dev-options

‍

CAPTCHA, or the Completely Automated Public Turing Test to Tell Computers and Humans Apart function, is an image or distorted text that users have to identify or interpret to prove they are human. 2007 marked the inception of CAPTCHA, and Google developed its free service called reCAPTCHA, one of the most commonly used technologies to tell computers apart from humans. CAPTCHA protects websites from spam and abuse by using tests considered easy for humans but were supposed to be difficult for bots to solve. 

But, now this has changed. With AI becoming more and more sophisticated, it is now capable of solving CAPTCHA tests at a rate that is more accurate than humans, rendering them increasingly ineffective. This raises the question of whether CAPTCHA is still effective as a detection tool with the advancements of AI.

CAPTCHA Evolution: From 2007 Till Now

CAPTCHA has evolved through various versions to keep bots at bay. reCAPTCHA v1 relied on distorted text recognition, v2 introduced image-based tasks and behavioural analysis, and v3 operated invisibly, assigning risk scores based on user interactions. While these advancements improved user experience and security, AI now solves CAPTCHA with 96% accuracy, surpassing humans (50-86%). Bots can mimic human behaviour, undermining CAPTCHA’s effectiveness and raising the question: is it still a reliable tool for distinguishing real people from bots?

Smarter Bots and Their Rise

AI advancements like machine learning, deep learning and neural networks have developed at a very fast pace in the past decade, making it easier for bots to bypass CAPTCHA. They allow the bots to process and interpret the CAPTCHA types like text and images with almost human-like behaviour. Some examples of AI developments against bots are OCR or Optical Character Recognition. The earlier versions of CAPTCHA relied on distorted text: AI because of this tech is able to recognise and decipher the distorted text, making CAPTCHA useless. AI is trained on huge datasets which allows Image Recognition by identifying the objects that are specific to the question asked. These bots can mimic human habits and patterns by Behavioural Analysis and therefore fool the CAPTCHA. 

To defeat CAPTCHA, attackers have been known to use Adversarial Machine Learning, which refers to AI models trained specifically to defeat CAPTCHA. They collect CAPTCHA datasets and answers and create an AI that can predict correct answers. The implications that CAPTCHA failures have on platforms can range from fraud to spam to even cybersecurity breaches or cyberattacks. 

CAPTCHA vs Privacy: GDPR and DPDP

GDPR and the DPDP Act emphasise protecting personal data, including online identifiers like IP addresses and cookies. Both frameworks mandate transparency when data is transferred internationally, raising compliance concerns for reCAPTCHA, which processes data on Google’s US servers. Additionally, reCAPTCHA's use of cookies and tracking technologies for risk scoring may conflict with the DPDP Act's broad definition of data. The lack of standardisation in CAPTCHA systems highlights the urgent need for policymakers to reevaluate regulatory approaches.

CyberPeace Analysis: The Future of Human Verification

CAPTCHA, once a cornerstone of online security, is losing ground as AI outperforms humans in solving these challenges with near-perfect accuracy. Innovations like invisible CAPTCHA and behavioural analysis provided temporary relief, but bots have adapted, exploiting vulnerabilities and undermining their effectiveness. This decline demands a shift in focus. 

Emerging alternatives like AI-based anomaly detection, biometric authentication, and blockchain verification hold promise but raise ethical concerns like privacy, inclusivity, and surveillance. The battle against bots isn’t just about tools but it’s about reimagining trust and security in a rapidly evolving digital world.

AI is clearly winning the CAPTCHA war, but the real victory will be designing solutions that balance security, user experience and ethical responsibility. It’s time to embrace smarter, collaborative innovations to secure a human-centric internet.

References

• https://www.business-standard.com/technology/tech-news/bot-detection-no-longer-working-just-wait-until-ai-agents-come-along-124122300456_1.html 
• https://www.milesrote.com/blog/ai-defeating-recaptcha-the-evolving-battle-between-bots-and-web-security 
• https://www.technologyreview.com/2023/10/24/1081139/captchas-ai-websites-computing/‍
• https://datadome.co/guides/captcha/recaptcha-gdpr/

Introduction

The term ‘super spreader’ is used to refer to social media and digital platform accounts that are able to quickly transmit information to a significantly large audience base in a short duration. The analogy references the medical term, where a small group of individuals is able to rapidly amplify the spread of an infection across a huge population. The fact that a few handful accounts are able to impact and influence many is attributed to a number of factors like large follower bases, high engagement rates, content attractiveness or virality and perceived credibility.

Super spreader accounts have become a considerable threat on social media because they are responsible for generating a large amount of low-credibility material online. These individuals or groups may create or disseminate low-credibility content for a number of reasons, running from social media fame to garnering political influence, from intentionally spreading propaganda to seeking financial gains. Given the exponential reach of these accounts, identifying, tracing and categorising such accounts as the sources of misinformation can be tricky. It can be equally difficult to actually recognise the content they spread for the misinformation that it actually is. 

How Do A Few Accounts Spark Widespread Misinformation? 

Recent research suggests that misinformation superspreaders, who consistently distribute low-credibility content, may be the primary cause of the issue of widespread misinformation about different topics. A study[1] by a team of social media analysts at Indiana University has found that a significant portion of tweets spreading misinformation are sent by a small percentage of a given user base. The researchers conducted a review of 2,397,388 tweets posted on Twitter (now X) that were flagged as having low credibility and details on who was sending them. The study found that it does not take a lot of influencers to sway the beliefs and opinions of large numbers. This is attributed to the impact of what they describe as superspreaders. The researchers collected 10 months of data, which added up to 2,397,388 tweets sent by 448,103 users, and then reviewed it, looking for tweets that were flagged as containing low-credibility information. They found that approximately a third of the low-credibility tweets had been posted by people using just 10 accounts, and that just 1,000 accounts were responsible for posting approximately 70% of such tweets.[2]

Case Study

1. How Misinformation ‘Superspreaders’ Seed False Election Theories

During the 2020 U.S. presidential election, a small group of "repeat spreaders" aggressively pushed false election claims across various social media platforms for political gain, and this even led to rallies and radicalisation in the U.S.[3] Superspreaders accounts were responsible for disseminating a disproportionately large amount of misinformation related to the election, influencing public opinion and potentially undermining the electoral process.

In the domestic context, India was ranked highest for the risk of misinformation and disinformation according to experts surveyed for the World Economic Forum’s 2024 Global Risk Report. In today's digital age, misinformation, deep fakes, and AI-generated fakes pose a significant threat to the integrity of elections and democratic processes worldwide. With 64 countries conducting elections in 2024, the dissemination of false information carries grave implications that could influence outcomes and shape long-term socio-political landscapes. During the 2024 Indian elections, we witnessed a notable surge in deepfake videos of political personalities, raising concerns about the influence of misinformation on election outcomes.

2. Role of Superspreaders During Covid-19

Clarity in public health communication is important when any grey areas or gaps in information can be manipulated so quickly. During the COVID-19 pandemic, misinformation related to the virus, vaccines, and public health measures spread rapidly on social media platforms, including Twitter (Now X). Some prominent accounts or popular pages on platforms like Facebook and Twitter(now X) were identified as superspreaders of COVID-19 misinformation, contributing to public confusion and potentially hindering efforts to combat the pandemic.

As per the Center for Countering Digital Hate Inc (US), The "disinformation dozen," a group of 12 prominent anti-vaccine accounts[4], were found to be responsible for a large amount of anti-vaccine content circulating on social media platforms, highlighting the significant role of superspreaders in influencing public perceptions and behaviours during a health crisis.

There are also incidents where users are unknowingly engaged in spreading misinformation by forwarding information or content which are not always shared by the original source but often just propagated by amplifiers, using other sources, websites, or YouTube videos that help in dissemination. The intermediary sharers amplify these messages on their pages, which is where it takes off. Hence such users do not always have to be the ones creating or deliberately popularising the misinformation, but they are the ones who expose more people to it because of their broad reach. This was observed during the pandemic when a handful of people were able to create a heavy digital impact sharing vaccine/virus-related misinformation. 

3. Role of Superspreaders in Influencing Investments and Finance

Misinformation and rumours in finance may have a considerable influence on stock markets, investor behaviour, and national financial stability. Individuals or accounts with huge followings or influence in the financial niche can operate as superspreaders of erroneous information, potentially leading to market manipulation, panic selling, or incorrect impressions about individual firms or investments.

Superspreaders in the finance domain can cause volatility in markets, affect investor confidence, and even trigger regulatory responses to address the spread of false information that may harm market integrity. In fact, there has been a rise in deepfake videos, and fake endorsements, with multiple social media profiles providing unsanctioned investing advice and directing followers to particular channels. This leads investors into dangerous financial decisions. The issue intensifies when scammers employ deepfake videos of notable personalities to boost their reputation and can actually shape people’s financial decisions. 

Bots and Misinformation Spread on Social Media

Bots are automated accounts that are designed to execute certain activities, such as liking, sharing, or retweeting material, and they can broaden the reach of misinformation by swiftly spreading false narratives and adding to the virality of a certain piece of content. They can also artificially boost the popularity of disinformation by posting phony likes, shares, and comments, making it look more genuine and trustworthy to unsuspecting users. Bots can exploit social network algorithms by establishing false identities that interact with one another and with real users, increasing the spread of disinformation and pushing it to the top of users' feeds and search results.

Bots can use current topics or hashtags to introduce misinformation into popular conversations, allowing misleading information to acquire traction and reach a broader audience. They can lead to the construction of echo chambers, in which users are exposed to a narrow variety of perspectives and information, exacerbating the spread of disinformation inside restricted online groups. There are incidents reported where bot's were found as the sharers of content from low-credibility sources.

Bots are frequently employed as part of planned misinformation campaigns designed to propagate false information for political, ideological, or commercial gain. Bots, by automating the distribution of misleading information, can make it impossible to trace the misinformation back to its source. Understanding how bots work and their influence on information ecosystems is critical for combatting disinformation and increasing digital literacy among social media users.

CyberPeace Policy Recommendations

1. Recommendations/Advisory for Netizens:

1. Educating oneself: Netizens need to stay informed about current events, reliable fact-checking sources, misinformation counter-strategies, and common misinformation tactics, so that they can verify potentially problematic content before sharing.
2. Recognising the threats and vulnerabilities: It is important for netizens to understand the consequences of spreading or consuming inaccurate information, fake news, or misinformation. Netizens must be cautious of sensationalised content spreading on social media as it might attempt to provoke strong reactions or to mold public opinions. Netizens must consider questioning the credibility of information, verifying its sources, and developing cognitive skills to identify low-credibility content and counter misinformation.
3. Practice caution and skepticism: Netizens are advised to develop a healthy skepticism towards online information, and critically analyse the veracity of all information sources. Before spreading any strong opinions or claims, one must seek supporting evidence,  factual data, and expert opinions, and verify and validate claims with reliable sources or fact-checking entities.
4. Good netiquette on the Internet, thinking before forwarding any information: It is important for netizens to practice good netiquette in the online information landscape. One must exercise caution while sharing any information, especially if the information seems incorrect, unverified or controversial. It's important to critically examine facts and recognise and understand the implications of sharing false, manipulative, misleading or fake information/content. Netizens must also promote critical thinking and encourage their loved ones to think critically, verify information, seek reliable sources and counter misinformation.
5. Adopting and promoting Prebunking and Debunking strategies: Prebunking and debunking are two effective strategies to counter misinformation. Netizens are advised to engage in sharing only accurate information and do fact-checking to debunk any misinformation. They can rely on reputable fact-checking experts/entities who are regularly engaged in producing prebunking and debunking reports and material. Netizens are further advised to familiarise themselves with fact-checking websites, and resources and verify the information.

2. Recommendations for tech/social media platforms 

1. Detect, report and block malicious accounts: Tech/social media platforms must implement strict user authentication mechanisms to verify account holders' identities to minimise the formation of fraudulent or malicious accounts. This is imperative to weed out suspicious social media accounts, misinformation superspreader accounts and bots accounts. Platforms must be capable of analysing public content, especially viral or suspicious content to ascertain whether it is misleading, AI-generated, fake or deliberately misleading. Upon detection, platform operators must block malicious/ superspreader accounts. The same approach must apply to other community guidelines’ violations as well. 
2. Algorithm Improvements: Tech/social media platform operators must develop and deploy advanced algorithm mechanisms to detect suspicious accounts and recognise repetitive posting of misinformation. They can utilise advanced algorithms to identify such patterns and flag any misleading, inaccurate, or fake information.
3. Dedicated Reporting Tools: It is important for the tech/social media platforms to adopt robust policies to take action against social media accounts engaged in malicious activities such as spreading misinformation, disinformation, and propaganda. They must empower users on the platforms to flag/report suspicious accounts, and misleading content or misinformation through user-friendly reporting tools.
4. Holistic Approach: The battle against online mis/disinformation necessitates a thorough examination of the processes through which it spreads. This involves investing in information literacy education, modifying algorithms to provide exposure to varied viewpoints, and working on detecting malevolent bots that spread misleading information. Social media sites can employ similar algorithms internally to eliminate accounts that appear to be bots. All stakeholders must encourage digital literacy efforts that enable consumers to critically analyse information, verify sources, and report suspect content. Implementing prebunking and debunking strategies. These efforts can be further supported by collaboration with relevant entities such as cybersecurity experts, fact-checking entities, researchers, policy analysts and the government to combat the misinformation warfare on the Internet.  

References:

1. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0302201 {1}
2. https://phys.org/news/2024-05-superspreaders-responsible-large-portion-misinformation.html#google_vignette {2}
3. https://phys.org/news/2024-05-superspreaders-responsible-large-portion-misinformation.html#google_vignette {3}
4. https://counterhate.com/research/the-disinformation-dozen/ {4}
5. https://phys.org/news/2024-05-superspreaders-responsible-large-portion-misinformation.html#google_vignette
6. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0302201
7. https://www.nytimes.com/2020/11/23/technology/election-misinformation-facebook-twitter.html
8. https://www.wbur.org/onpoint/2021/08/06/vaccine-misinformation-and-a-look-inside-the-disinformation-dozen
9. https://healthfeedback.org/misinformation-superspreaders-thriving-on-musk-owned-twitter/
10. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8139392/
11. https://www.jmir.org/2021/5/e26933/
12. https://www.yahoo.com/news/7-ways-avoid-becoming-misinformation-121939834.html

‍