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WhatsApp messages masquerading as an offer from Maruti Suzuki with links luring unsuspecting users with the promise of Maruti Suzuki 40th Anniversary Celebration presents, have been making the rounds on the app. If you receive such messages try to stay away from it, as it can be a scam.

The Research Wing of CyberPeace Foundation along with Autobot Infosec Private Limited have conducted a study based on a WhatsApp message that contained a link pretending to be a free gift offer from Maruti Suzuki which asks users to participate in a survey in order to get a chance to win a Maruti Baleno Sigma MT car.

Warning SignsThe campaign pretends to be an offer from Maruti Suzuki but is hosted on a third party domain instead of the official Maruti Suzuki website which makes it more suspicious.

The domain names associated with the campaign have been registered in very recent times.

Multiple redirections have been noticed between the links.

No reputed site would ask its users to share the campaign on WhatsApp.

The prize is kept really attractive to lure the laymen.

Grammatical mistakes have been noticed.

A congratulations message appears on the landing page with an attractive photo of Maruti Suzuki cars that asks users to participate in a quick survey in order to get a “Maruti Suzuki BALENO Sigma MT”. Also, the bottom of the page seems to appear like a comment section with public comments establishing the truthfulness of the offer.

The survey starts with some basic questions like Do you know Maruti Suzuki?, How old are you?, How do you think of Maruti Suzuki?, Are you male or female? Etc. Once the user answers the questions a “congratulatory message” is displayed.

On clicking the OK button users are given three attempts to win the prize. After completing all the attempts a message pops up that the user has won “Maruti Suzuki BALENO Sigma MT”. It then prompts the user to share the message on WhatsApp.

Strangely enough the user has to keep clicking the WhatsApp button until the progress bar completes. After clicking on the green ‘WhatsApp’ button multiple times it shows a section where an instruction has been given to complete registration in order to get the prize.

After clicking on the green ‘Complete registration’ button, it redirects the user to multiple advertisements web pages varying each time the user clicks on the button.

During the analysis the research team found a javascript code called hm.js was being executed in the background from the host hm[.]baidu[.]com which is a subdomain of Baidu and is used for Baidu Analytics, also known as Baidu Tongji. The important part is that Baidu is a Chinese multinational technology company specializing in Internet-related services, products and artificial intelligence, headquartered in Beijing’s Haidian district, China.To read the full report, please click (https://www.cyberpeace.org/CyberPeace/Repository/20210828Research-report-on-Maruti-Suzuki-40th-Anniversary-Celebration-free-gift-scam.pdf) here:

Conclusive Summary

1. The whole research activity was performed in a secured sandbox environment where the WhatsApp application was not installed. If any user opens the link from a device like smartphones where the WhatsApp application is installed, the sharing features on the site will open the Whatsapp application on the device to share the link.

2. The campaign collects browser and system information from the users.

3. Most of the domain names associated with the campaign have the registrant country as China.

4. Cybercriminals used Cloudflare technologies to mask the real IP addresses of the front-end domain names used in this Maruti Suzuki 40th Anniversary Celebration free gift campaign. But during the phases of investigation, the research team has identified a domain name that was requested in the background and has been traced as belonging to China.

CyberPeace Advisory

1. CyberPeace Foundation and Autobot Infosec recommend that people should avoid opening such messages sent via social platforms.

2. If at all, the user gets into this trap, it could lead to whole system compromise such as access to the microphone, Camera, Text Messages, Contacts, Pictures, Videos, Banking Applications, etc as well as financial losses.

3. Do not share confidential details like login credentials, banking information with such a type of scam.

4. Do not share or forward fake messages containing links without proper verification.

5. There is a need for International Cyber Cooperation between countries to bust the cybercriminal gangs running the fraud campaigns affecting individuals and organizations, to make Cyberspace resilient and peaceful.

Source: https://www.business-standard.com//content/press-releases-ani/cyber-criminals-target-internet-users-with-maruti-suzuki-40th-anniversary-celebration-free-gift-scam-121083101204_1.html

Executive Summary:

Apple has quickly responded to two severe zero-day threats, CVE-2024-44308 and CVE-2024-44309 in iOS, macOS, visionOS, and Safari. These defects, actively used in more focused attacks presumably by state actors, allow for code execution and cross-site scripting (XSS). In a report shared by Google’s Threat Analysis Group, the existing gaps prove that modern attacks are highly developed. Apple’s mitigation comprises memory management, especially state management to strengthen device security. Users are encouraged to update their devices as soon as possible, turn on automatic updates and be careful in the internet space to avoid these new threats.

Introduction

Apple has proved its devotion to the security issue releasing the updates fixing two zero-day bugs actively exploited by hackers. The bugs, with the IDs CVE-2024-44308 and CVE-2024-44309, are dangerous and can lead to code execution and cross-site scripting attacks. The vulnerabilities have been employed in attack and the significance of quick patch release for the safety of the users.

Vulnerabilities in Detail

The discovery of vulnerabilities (CVE-2024-44308, CVE-2024-44309) is credited to Clément Lecigne and Benoît Sevens of Google's Threat Analysis Group (TAG). These vulnerabilities were found in JavaScriptCore and WebKit, integral components of Apple’s web rendering framework. The details of these vulnerabilities are mentioned below:

CVE-2024-44308

• Severity: High (CVSS score: 8.8)
• Description: A flaw in the JavaScriptCore component of WebKit. Malicious web content could cause code to be executed on the target system and make the system vulnerable to the full control of the attacker.
• Technical Finding: This vulnerability involves bad handling of memory in the course of executing JavaScript, allowing the use of injected payloads remotely by the attackers.

CVE-2024-44309

• Severity: Moderate (CVSS score: 6.1)
• Description: A cookie management flaw in WebKit which might result in cross site scripting (XSS). This vulnerability enables the attackers to embed unauthorized scripts into genuine websites and endanger the privacy of users as well as their identities.
• Technical Finding: This issue arises because of wrong handling of cookies at the state level while processing the maliciously crafted web content and provides an unauthorized route to session data.

Affected Systems

These vulnerabilities impact a wide range of Apple devices and software versions:

• iOS 18.1.1 and iPadOS 18.1.1: For devices including iPhone XS and later, iPad Pro (13-inch), and iPad mini 5th generation onwards.
• iOS 17.7.2 and iPadOS 17.7.2: Supports earlier models such as iPad Pro (10.5-inch) and iPad Air 3rd generation.
• macOS Sequoia 15.1.1: Specifically targets systems running macOS Sequoia.
• visionOS 2.1.1: Exclusively for Apple Vision Pro.
• Safari 18.1.1: For Macs running macOS Ventura and Sonoma.

Apple's Mitigation Approach

Apple has implemented the following fixes:

• CVE-2024-44308: Enhanced input validation and robust memory checks to prevent arbitrary code execution.
• CVE-2024-44309: Improved state management to eliminate cookie mismanagement vulnerabilities.

These measures ensure stronger protection against exploitation and bolster the underlying security architecture of affected components.

Broader Implications

The exploitation of these zero-days highlights the evolving nature of threat landscapes:

• Increasing Sophistication: Attackers are refining techniques to target niche vulnerabilities, bypassing traditional defenses.
• Spyware Concerns: These flaws align with the modus operandi of spyware tools, potentially impacting privacy and national security.
• Call for Timely Updates: Users delaying updates inadvertently increase their risk exposure

Technical Recommendations for Users

To mitigate potential risks:

1. Update Devices Promptly: Install the latest patches for iOS, macOS, visionOS, and Safari.
2. Enable Automatic Updates: Ensures timely application of future patches.
3. Restrict WebKit Access: Avoid visiting untrusted websites until updates are installed.
4. Monitor System Behavior: Look for anomalies that could indicate exploitation.

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Conclusion

The exploitation of CVE-2024-44308 and CVE-2024-44309 targeting Apple devices highlight the importance of timely software updates to protect users from potential exploitation. The swift action of Apple by providing immediate improved checks, state management and security patches. Users are therefore encouraged to install updates as soon as possible to guard against these zero day flaws.

References:

• https://support.apple.com/en-us/121752
• https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2024-44308
• https://securityonline.info/cve-2024-44308-and-cve-2024-44309-apple-addresses-zero-day-vulnerabilities/ 

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Introduction

Search engines have become indispensable in our daily lives, allowing us to find information instantly by entering keywords or phrases. Using the prompt "search Google or type a URL" reflects just how seamless this journey to knowledge has become. With millions of searches conducted every second, and Google handling over 6.3 million searches per minute as of 2023 (Statista), one critical question arises: do search engines prioritise results based on user preferences and past behaviours, or are they truly unbiased?

Understanding AI Bias in Search Algorithms

AI bias is also known as machine learning bias or algorithm bias. It refers to the occurrence of biased results due to human biases that deviate from the original training data or AI algorithm which leads to distortion of outputs and creation of potentially harmful outcomes. The sources of this bias are algorithmic bias, data bias and interpretation bias which emerge from user history, geographical data, and even broader societal biases in training data. 

Common biases include excluding certain groups of people from opportunities because of AI bias. In healthcare, underrepresenting data of women or minority groups can skew predictive AI algorithms. While AI helps streamline the automation of resume scanning during a search to help identify ideal candidates, the information requested and answers screened out can result in biased outcomes due to a biased dataset or any other bias in the input data.

Case in Point: Google’s "Helpful" Results and Its Impact 

Google optimises results by analysing user interactions to determine satisfaction with specific types of content. This data-driven approach forms ‘filter bubbles’ by repeatedly displaying content that aligns with a user’s preferences, regardless of factual accuracy. While this can create a more personalised experience, it risks confining users to a limited view, excluding diverse perspectives or alternative viewpoints.

The personal and societal impacts of such biases are significant. At an individual level, filter bubbles can influence decision-making, perceptions, and even mental health. On a societal level, these biases can reinforce stereotypes, polarise opinions, and shape collective narratives. There is also a growing concern that these biases may promote misinformation or limit users’ exposure to diverse perspectives, all stemming from the inherent bias in search algorithms.

Policy Challenges and Regulatory Measures

Regulating emerging technologies like AI, especially in search engine algorithms, presents significant challenges due to their intricate, proprietary nature. Traditional regulatory frameworks struggle to keep up with them as existing laws were not designed to address the nuances of algorithm-driven platforms. Regulatory bodies are pushing for transparency and accountability in AI-powered search algorithms to counter biases and ensure fairness globally. For example, the EU’s Artificial Intelligence Act aims to establish a regulatory framework that will categorise AI systems based on risk and enforces strict standards for transparency, accountability, and fairness, especially for high-risk AI applications, which may include search engines. India has proposed the Digital India Act in 2023 which will define and regulate High-risk AI. 

Efforts include ethical guidelines emphasising fairness, accountability, and transparency in information prioritisation. However, a complex regulatory landscape could hinder market entrants, highlighting the need for adaptable, balanced frameworks that protect user interests without stifling innovation.

CyberPeace Insights

In a world where search engines are gateways to knowledge, ensuring unbiased, accurate, and diverse information access is crucial. True objectivity remains elusive as AI-driven algorithms tend to personalise results based on user preferences and past behaviour, often creating a biased view of the web. Filter bubbles, which reinforce individual perspectives, can obscure factual accuracy and limit exposure to diverse viewpoints. Addressing this bias requires efforts from both users and companies. Users should diversify sources and verify information, while companies should enhance transparency and regularly audit algorithms for biases. Together, these actions can promote a more equitable, accurate, and unbiased search experience for all users. 

References 

• https://www.bbc.com/future/article/20241101-how-online-photos-and-videos-alter-the-way-you-think 
• https://www.bbc.com/future/article/20241031-how-google-tells-you-what-you-want-to-hear
• https://www.ibm.com/topics/ai-bias#:~:text=In%20healthcare%2C%20underrepresenting%20data%20of,can%20skew%20predictive%20AI%20algorithms

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