#FactCheck: A digitally altered video of actor Sebastian Stan shows him changing a ‘Tell Modi’ poster to one that reads ‘I Told Modi’ on a display panel.

Introduction

Search Engine Optimisation (SEO) is a process through which one can improve website visibility on search engine platforms like Google, Microsoft Bing, etc. There is an implicit understanding that SEO suggestions or the links that are generated on top are the more popular information sources and, hence, are deemed to be more trustworthy. This trust, however, is being misused by threat actors through a process called SEO poisoning.

SEO poisoning is a method used by threat actors to attack and obtain information about the user by using manipulative methods that position their desired link, web page, etc to appear at the top of the search engine algorithm. The end goal is to lure the user into clicking and downloading their malware, presented in the garb of legitimate marketing or even as a valid result for Google search.

An active example of attempts at SEO poisoning has been discussed in a report by the Hindustan Times on 11th November, 2024. It highlights that using certain keywords could make a user more susceptible to hacking. Hackers are now targeting people who enter specific words or specific combinations in search engines. According to the report, users who looked up and clicked on links at the top related to the search query “Are Bengal cats legal in Australia?” had details regarding their personal information posted online soon after.

SEO Poisoning - Modus Operandi Of Attack

There are certain tactics that are used by the attackers on SEO poisoning, these are:

• Keyword stuffing- This method involves overloading a webpage with irrelevant words, which helps the false website appear higher in ranking.
• Typosquatting- This method involves creating domain names or links similar to the more popular and trusted websites. A lack of scrutiny before clicking would lead the user to download malware, from what they thought was a legitimate site.
• Cloaking- This method operates by showing different content to both the search engines and the user. While the search engine sees what it assumes to be a legitimate website, the user is exposed to harmful content.
• Private Link Networks- Threat actors create a group of unrelated websites in order to increase the number of referral links, which enables them to rank higher on search engine platforms.
• Article Spinning- This method involves imitating content from other pre-existing, legitimate websites, while making a few minor changes, giving the impression to search engine crawlers of it being original content.
• Sneaky Redirect- This method redirects the users to malicious websites (without their knowledge) instead of the ones the user had intended to click.

CyberPeace Recommendations

• Employee Security Awareness Training: Security awareness training can help employees familiarise themselves with tactics of SEO poisoning, encouraging them to either spot such inconsistencies early on or even alert the security team at the earliest. 
• Tool usage: Companies can use Digital Risk Monitoring tools to catch instances of typosquatting. Endpoint Detection and Response (EDR) tools also help keep an eye on client history and assess user activities during security breaches to figure out the source of the affected file.
• Internal Security Measures: To refer to lists of Indicators of Compromise (IOC). IOC has URL lists that show evidence of the strange behaviour of websites, and this can be used to practice caution. Deploying Web Application Firewalls (WAFs) to mitigate and detect malicious traffic is helpful.

Conclusion

The nature of SEO poisoning is such that it inherently promotes the spread of misinformation, and facilitates cyberattacks. Misinformation regarding the legitimacy of the links and the content they display, in order to lure users into clicking on them, puts personal information under threat. As people trust their favoured search engines, and there is a lack of awareness of such tactics in use, one must exercise caution while clicking on links that seem to be popular, despite them being hosted by trusted search engines.

References

• https://www.checkpoint.com/cyber-hub/cyber-security/what-is-cyber-attack/what-is-seo-poisoning/
• https://www.vectra.ai/topics/seo-poisoning
• https://www.techtarget.com/whatis/definition/search-poisoning
• https://www.blackberry.com/us/en/solutions/endpoint-security/ransomware-protection/seo-poisoning
• https://www.coalitioninc.com/blog/seo-poisoning-attacks
• https://www.sciencedirect.com/science/article/abs/pii/S0160791X24000186
• https://www.repindia.com/blog/secure-your-organisation-from-seo-poisoning-and-malvertising-threats/ 
• https://www.hindustantimes.com/technology/typing-these-6-words-on-google-could-make-you-a-target-for-hackers-101731286153415.html

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Introduction

The fast-paced development of technology and the wider use of social media platforms have led to the rapid dissemination of misinformation with characteristics such as diffusion, fast propagation speed, wide influence, and deep impact through these platforms. Social Media Algorithms and their decisions are often perceived as a black box introduction that makes it impossible for users to understand and recognise how the decision-making process works. 

Social media algorithms may unintentionally promote false narratives that garner more interactions, further reinforcing the misinformation cycle and making it harder to control its spread within vast, interconnected networks. Algorithms judge the content based on the metrics, which is user engagement. It is the prerequisite for algorithms to serve you the best. Hence, algorithms or search engines enlist relevant items you are more likely to enjoy. This process, initially, was created to cut the clutter and provide you with the best information. However, sometimes it results in unknowingly widespread misinformation due to the viral nature of information and user interactions. 

Analysing the Algorithmic Architecture of Misinformation

Social media algorithms, designed to maximize user engagement, can inadvertently promote misinformation due to their tendency to trigger strong emotions, creating echo chambers and filter bubbles. These algorithms prioritize content based on user behaviour, leading to the promotion of emotionally charged misinformation. Additionally, the algorithms prioritize content that has the potential to go viral, which can lead to the spread of false or misleading content faster than corrections or factual content.

Additionally, popular content is amplified by platforms, which spreads it faster by presenting it to more users. Limited fact-checking efforts are particularly difficult since, by the time they are reported or corrected, erroneous claims may have gained widespread acceptance due to delayed responses. Social media algorithms find it difficult to distinguish between real people and organized networks of troll farms or bots that propagate false information. This creates a vicious loop where users are constantly exposed to inaccurate or misleading material, which strengthens their convictions and disseminates erroneous information through networks.

Though algorithms, primarily, aim to enhance user engagement by curating content that aligns with the user's previous behaviour and preferences. Sometimes this process leads to "echo chambers," where individuals are exposed mainly to information that reaffirms their beliefs which existed prior, effectively silencing dissenting voices and opposing viewpoints. This curated experience reduces exposure to diverse opinions and amplifies biased and polarising content, making it arduous for users to discern credible information from misinformation. Algorithms feed into a feedback loop that continuously gathers data from users' activities across digital platforms, including websites, social media, and apps. This data is analysed to optimise user experiences, making platforms more attractive. While this process drives innovation and improves user satisfaction from a business standpoint, it also poses a danger in the context of misinformation. The repetitive reinforcement of user preferences leads to the entrenchment of false beliefs, as users are less likely to encounter fact-checks or corrective information.

Moreover, social networks and their sheer size and complexity today exacerbate the issue. With billions of users participating in online spaces, misinformation spreads rapidly, and attempting to contain it—such as by inspecting messages or URLs for false information—can be computationally challenging and inefficient. The extensive amount of content that is shared daily means that misinformation can be propagated far quicker than it can get fact-checked or debunked.

Understanding how algorithms influence user behaviour is important to tackling misinformation. The personalisation of content, feedback loops, the complexity of network structures, and the role of superspreaders all work together to create a challenging environment where misinformation thrives. Hence, highlighting the importance of countering misinformation through robust measures. 

The Role of Regulations in Curbing Algorithmic Misinformation

The EU's Digital Services Act (DSA) applicable in the EU is one of the regulations that aims to increase the responsibilities of tech companies and ensure that their algorithms do not promote harmful content. These regulatory frameworks play an important role they can be used to establish mechanisms for users to appeal against the algorithmic decisions and ensure that these systems do not disproportionately suppress legitimate voices. Independent oversight and periodic audits can ensure that algorithms are not biased or used maliciously. Self-regulation and Platform regulation are the first steps that can be taken to regulate misinformation. By fostering a more transparent and accountable ecosystem, regulations help mitigate the negative effects of algorithmic misinformation, thereby protecting the integrity of information that is shared online. In the Indian context, the Intermediary Guidelines, 2023, Rule 3(1)(b)(v) explicitly prohibits the dissemination of misinformation on digital platforms. The ‘Intermediaries’ are obliged to ensure reasonable efforts to prevent users from hosting, displaying, uploading, modifying, publishing, transmitting, storing, updating, or sharing any information related to the 11 listed user harms or prohibited content. This rule aims to ensure platforms identify and swiftly remove misinformation, and false or misleading content.

Cyberpeace Outlook

Understanding how algorithms prioritise content will enable users to critically evaluate the information they encounter and recognise potential biases. Such cognitive defenses can empower individuals to question the sources of the information and report misleading content effectively. In the future of algorithms in information moderation, platforms should evolve toward more transparent, user-driven systems where algorithms are optimised not just for engagement but for accuracy and fairness. Incorporating advanced AI moderation tools, coupled with human oversight can improve the detection and reduction of harmful and misleading content. Collaboration between regulatory bodies, tech companies, and users will help shape the algorithms landscape to promote a healthier, more informed digital environment.

References:

• https://www.advancedsciencenews.com/misformation-spreads-like-a-nuclear-reaction-on-the-internet/
• https://www.niemanlab.org/2024/09/want-to-fight-misinformation-teach-people-how-algorithms-work/ 
• Press Release: Press Information Bureau (pib.gov.in) 

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Executive Summary:

A viral online video claims Billionaire and Founder of Tesla & SpaceX Elon Musk of promoting Cryptocurrency. The CyberPeace Research Team has confirmed that the video is a deepfake, created using AI technology to manipulate Elon’s facial expressions and voice through the use of relevant, reputed and well verified AI tools and applications to arrive at the above conclusion for the same. The original footage had no connections to any cryptocurrency, BTC or ETH apportion to the ardent followers of crypto-trading. The claim that Mr. Musk endorses the same and is therefore concluded to be false and misleading.

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Claims:

A viral video falsely claims that Billionaire and founder of Tesla Elon Musk is endorsing a Crypto giveaway project for the crypto enthusiasts which are also his followers  by consigning a portion of his valuable Bitcoin and Ethereum stock.

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Fact Check:

Upon receiving the viral posts, we conducted a Google Lens search on the keyframes of the video. The search led us to various legitimate sources featuring Mr. Elon Musk but none of them included any promotion of any cryptocurrency giveaway. The viral video exhibited signs of digital manipulation, prompting a deeper investigation.

We used AI detection tools, such as TrueMedia.org, to analyze the video. The analysis confirmed with 99.0% confidence that the video was a deepfake. The tools identified "substantial evidence of manipulation," particularly in the facial movements and voice, which were found to be artificially generated.

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Analysis link

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Additionally, an extensive review of official statements and interviews with Mr. Musk revealed no mention of any such giveaway. No credible reports were found linking Elon Musk to this promotion, further confirming the video’s inauthenticity.

Conclusion:

The viral video claiming that Elon Musk promotes a crypto giveaway is a deep fake. The research using various tools such as Google Lens, AI detection tool confirms that the video is manipulated using AI technology. Additionally, there is no information in any official sources. Thus, the CyberPeace Research Team confirms that the video was manipulated using AI technology, making the claim false and misleading.

• Claim: Elon Musk conducting giving away Cryptocurrency viral on social media.
• Claimed on: X(Formerly Twitter)
• Fact Check: False & Misleading

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