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Introduction

In the labyrinthine world of cybersecurity, a new spectre has emerged from the digital ether, casting a long shadow over the seemingly impregnable orchards of Apple's macOS. This phantom, known as SpectralBlur, is a backdoor so cunningly crafted that it remained shrouded in the obscurity of cyberspace, undetected by the vigilant eyes of antivirus software until its recent unmasking. The discovery of SpectralBlur is not just a tale of technological intrigue but a narrative that weaves together the threads of geopolitical manoeuvring, the relentless pursuit of digital supremacy, and the ever-evolving landscape of cyber warfare.

SpectralBlur, a term that conjures images of ghostly interference and elusive threats, is indeed a fitting moniker for this new macOS backdoor threat. Cybersecurity researchers have peeled back the layers of the digital onion to reveal a moderately capable backdoor that can upload and download files, execute shell commands, update its configuration, delete files, and enter states of hibernation or sleep, all at the behest of a remote command-and-control server. Greg Lesnewich, a security researcher whose name has become synonymous with the relentless pursuit of digital malefactors, has shed light on this new threat that overlaps with a known malware family attributed to the enigmatic North Korean threat actors.

SpectralBlur similar to Lazarus Group’s KANDYKORN

The malware shares its DNA with KANDYKORN, also known as SockRacket, an advanced implant that functions as a remote access trojan capable of taking control of a compromised host. It is a digital puppeteer, pulling the strings of infected systems with a malevolent grace. The KANDYKORN activity also intersects with another campaign orchestrated by the Lazarus sub-group known as BlueNoroff, or TA444, which culminates in the deployment of a backdoor referred to as RustBucket and a late-stage payload dubbed ObjCShellz.

Recently, the threat actor has been observed combining disparate pieces of these two infection chains, leveraging RustBucket droppers to deliver KANDYKORN. This latest finding is another sign that North Korean threat actors are increasingly setting their sights on macOS to infiltrate high-value targets, particularly those within the cryptocurrency and blockchain industries. 'TA444 keeps running fast and furious with these new macOS malware families,' Lesnewich remarked, painting a picture of a relentless adversary in the digital realm.

Patrick Wardle, a security researcher whose insights into the inner workings of SpectralBlur have further illuminated the threat landscape, noted that the Mach-O binary was uploaded to the VirusTotal malware scanning service in August 2023 from Colombia. The functional similarities between KANDYKORN and SpectralBlur have raised the possibility that they may have been built by different developers with the same requirements. What makes the malware stand out are its attempts to hinder analysis and evade detection while using grant to set up a pseudo-terminal and execute shell commands received from the C2 server.

The disclosure comes as 21 new malware families designed to target macOS systems, including ransomware, information stealers, remote access trojans, and nation-state-backed malware, were discovered in 2023, up from 13 identified in 2022. 'With the continued growth and popularity of macOS (especially in the enterprise!), 2024 will surely bring a bevvy of new macOS malware,' Wardle noted, his words a harbinger of the digital storms on the horizon.

Hackers are beefing up their efforts to go after the best MacBooks as security researchers have discovered a brand new macOS backdoor which appears to have ties to another recently identified Mac malware strain. As reported by Security Week, this new Mac malware has been dubbed SpectralBlur and although it was uploaded to VirusTotal back in August of last year, it remained undetected by the best antivirus software until it recently caught the attention of Proofpoint’s Greg Lesnewich.

Lesnewich explained that SpectralBlur has similar capabilities to other backdoors as it can upload and download files, delete files and hibernate or sleep when given commands from a hacker-controlled command-and-control (C2) server. What is surprising about this new Mac malware strain though is that it shares similarities to the KandyKorn macOS backdoor which was created by the infamous North Korean hacking group Lazarus.

Just like SpectralBlur, KandyKorn is designed to evade detection while providing the hackers behind it with the ability to monitor and control infected Macs. Although different, these two Mac malware strains appear to be built based on the same requirements. Once installed on a vulnerable Mac, SpectralBlur executes a function that allows it to decrypt and encrypt network traffic to help it avoid being detected. However, it can also erase files after opening them and then overwrite the data they contain with zeros..

How to keep your Apple computers safe from hackers

As with the best iPhones, keeping your Mac up to date is the easiest and most important way to keep it safe from hackers. Hackers often prey on users who haven’t updated their devices to the latest software as they can exploit unpatched vulnerabilities and security flaws.

Checking to see if you're running the latest macOS version is quite easy. Just click on the Apple Logo in the top right corner of your computer, head to System Preferences and then click on Software Update. If you need a bit more help, check out our guide on how to update a Mac for more detailed instructions with pictures.

Even though your Mac has its own built-in malware scanner from Apple called xProtect, you should consider using one of the best Mac antivirus software solutions for additional protection. Paid antivirus software is often updated more frequently and you often also get access to other extras to help keep you safe online like a password manager or a VPN.

Besides updating your Mac frequently and using antivirus software, you must be careful online. This means sticking to trusted online retailers, carefully checking the URLs of the websites you visit and avoiding opening links and attachments sent to you via email or social media from people you don’t know. Likewise, you should also learn how to spot a phishing scam to know which emails you want to delete right away.

Conclusion 

The thing about hackers and other cybercriminals is that they are constantly evolving their tactics and attack methods. This helps them avoid detection and allows them to devise brand-new ways to trick ordinary people. With the surge we saw in Mac malware last year, though, Apple will likely be working on beefing up xProtect and macOS to better defend against these new threats.

References 

• https://www.scmagazine.com/news/new-macos-malware-spectralblur-idd-as-north-korean-backdoor
• https://www.tomsguide.com/news/this-new-macos-backdoor-lets-hackers-take-over-your-mac-remotely-how-to-stay-safe
• https://thehackernews.com/2024/01/spectralblur-new-macos-backdoor-threat.html

Introduction

Assisted Reproductive Technology (“ART”) refers to a diverse set of medical procedures designed to aid individuals or couples in achieving pregnancy when conventional methods are unsuccessful. This umbrella term encompasses various fertility treatments, including in vitro fertilization (IVF), intrauterine insemination (IUI), and gamete and embryo manipulation. ART procedures involve the manipulation of both male and female reproductive components to facilitate conception.

The dynamic landscape of data flows within the healthcare sector, notably in the realm of ART, demands a nuanced understanding of the complex interplay between privacy regulations and medical practices. In this context, the Information Technology (Reasonable Security Practices And Procedures And Sensitive Personal Data Or Information) Rules, 2011, play a pivotal role, designating health information as "sensitive personal data or information" and underscoring the importance of safeguarding individuals' privacy. This sensitivity is particularly pronounced in the ART sector, where an array of personal data, ranging from medical records to genetic information, is collected and processed. The recent Assisted Reproductive Technology (Regulation) Act, 2021, in conjunction with the Digital Personal Data Protection Act, 2023, establishes a framework for the regulation of ART clinics and banks, presenting a layered approach to data protection.

A note on data generated by ART

Data flows in any sector are scarcely uniform and often not easily classified under straight-jacket categories. Consequently, mapping and identifying data and its types become pivotal. It is believed that most data flows in the healthcare sector are highly sensitive and personal in nature, which may severely compromise the privacy and safety of an individual if breached. The Information Technology (Reasonable Security Practices And Procedures And Sensitive Personal Data Or Information) Rules, 2011 (“SPDI Rules”) categorizes any information pertaining to physical, physiological, mental conditions or medical records and history as “sensitive personal data or information”; this definition is broad enough to encompass any data collected by any ART facility or equipment. These include any information collected during the screening of patients, pertaining to ovulation and menstrual cycles, follicle and sperm count, ultrasound results, blood work etc. It also includes pre-implantation genetic testing on embryos to detect any genetic abnormality. 

But data flows extend beyond mere medical procedures and technology. Health data also involves any medical procedures undertaken, the amount of medicine and drugs administered during any procedure, its resultant side effects, recovery etc. Any processing of the above-mentioned information, in turn, may generate more personal data points relating to an individual’s political affiliations, race, ethnicity, genetic data such as biometrics and DNA etc.; It is seen that different ethnicities and races react differently to the same/similar medication and have different propensities to genetic diseases. Further, it is to be noted that data is not only collected by professionals but also by intelligent equipment like AI which may be employed by any facility to render their service. Additionally, dissemination of information under exceptional circumstances (e.g. medical emergency) also affects how data may be classified. Considerations are further nuanced when the fundamental right to identity of a child conceived and born via ART may be in conflict with the fundamental right to privacy of a donor to remain anonymous. 

Intersection of Privacy laws and ART laws: 

In India, ART technology is regulated by the Assisted Reproductive Technology (Regulation) Act, 2021 (“ART Act”). With this, the Union aims to regulate and supervise assisted reproductive technology clinics and ART banks, prevent misuse and ensure safe and ethical practice of assisted reproductive technology services. When read with the Digital Personal Data Protection Act, 2023 (“DPDP Act”) and other ancillary guidelines, the two legislations provide some framework regulations for the digital privacy of health-based apps.

The ART Act establishes a National Assisted Reproductive Technology and Surrogacy Registry (“National Registry”) which acts as a central database for all clinics and banks and their nature of services. The Act also establishes a National Assisted Reproductive Technology and Surrogacy Board (“National Board”)  under the Surrogacy Act to monitor the implementation of the act and advise the central government on policy matters. It also supervises the functioning of the National Registry, liaises with State Boards and curates a code of conduct for professionals working in ART clinics and banks. Under the DPDP Act, these bodies (i.e. National Board, State Board, ART clinics and banks) are most likely classified as data fiduciaries (primarily clinics and banks), data processors (these may include National Board and State boards) or an amalgamation of both (these include any appropriate authority established under the ART Act for investigation of complaints, suspend or cancellation of registration of clinics etc.) depending on the nature of work undertaken by them. If so classified, then the duties and liabilities of data fiduciaries and processors would necessarily apply to these bodies. As a result, all bodies would necessarily have to adopt Privacy Enhancing Technologies (PETs) and other organizational measures to ensure compliance with privacy laws in place. This may be considered one of the most critical considerations of any ART facility since any data collected by them would be sensitive personal data pertaining to health, regulated by the Information Technology (Reasonable Security Practices And Procedures And Sensitive Personal Data Or Information) Rules, 2011 (“SPDI Rules 2011”). These rules provide for how sensitive personal data or information are to be collected, handled and processed by anyone.

The ART Act independently also provides for the duties of ART clinics and banks in the country. ART clinics and banks are required to inform the commissioning couple/woman of all procedures undertaken and all costs, risks, advantages, and side effects of their selected procedure. It mandatorily ensures that all information collected by such clinics and banks to not informed to anyone except the database established by the National Registry or in cases of medical emergency or on order of court. Data collected by clinics and banks (these include details on donor oocytes, sperm or embryos used or unused) are required to be detailed and must be submitted to the National Registry online. ART banks are also required to collect personal information of donors including name, Aadhar number, address and any other details. By mandating online submission, the ART Act is harmonized with the DPDP Act, which regulates all digital personal data and emphasises free, informed consent.

Conclusion

With the increase in active opt-ins for ART, data privacy becomes a vital consideration for all healthcare facilities and professionals. Safeguard measures are not only required on a corporate level but also on a governmental level. It is to be noted that in the 262 Session of the Rajya Sabha, the Ministry of Electronics and Information Technology reported 165 data breach incidents involving citizen data from January 2018 to October 2023 from the Central Identities Data Repository despite publicly denying. This discovery puts into question the safety and integrity of data that may be submitted to the National Registry database, especially given the type of data (both personal and sensitive information) it aims to collate. At present the ART Act is well supported by the DPDP Act. However, further judicial and legislative deliberations are required to effectively regulate and balance the interests of all stakeholders.

References

• The Information Technology (Reasonable Security Practices And Procedures And Sensitive Personal Data Or Information) Rules, 2011
• Caring for Intimate Data in Fertility Technologies https://dl.acm.org/doi/pdf/10.1145/3411764.3445132 
• Digital Personal Data Protection Act, 2023
• https://www.wolterskluwer.com/en/expert-insights/pharmacogenomics-and-race-can-heritage-affect-drug-disposition  

Introduction

According to Statista, the global artificial intelligence software market is forecast to grow by around 126 billion US dollars by 2025. This will include a 270% increase in enterprise adoption over the past four years. The top three verticals in the Al market are BFSI (Banking, Financial Services, and Insurance), Healthcare & Life Sciences, and Retail & e-commerce. These sectors benefit from vast data generation and the critical need for advanced analytics. Al is used for fraud detection, customer service, and risk management in BFSI; diagnostics and personalised treatment plans in healthcare; and retail marketing and inventory management.

The Chairperson of the Competition Commission of India’s Chief, Smt. Ravneet Kaur raised a concern that Artificial Intelligence has the potential to aid cartelisation by automating collusive behaviour through predictive algorithms. She explained that the mere use of algorithms cannot be anti-competitive but in case the algorithms are manipulated, then that is a valid concern about competition in markets.

This blog focuses on how policymakers can balance fostering innovation and ensuring fair competition in an AI-driven economy. 

What is the Risk Created by AI-driven Collusion?

AI uses predictive algorithms, and therefore, they could lead to aiding cartelisation by automating collusive behaviour. AI-driven collusion could be through:

• The use of predictive analytics to coordinate pricing strategies among competitors.
• The lack of human oversight in algorithm-induced decision-making leads to tacit collusion (competitors coordinate their actions without explicitly communicating or agreeing to do so).

AI has been raising antitrust concerns and the most recent example is the partnership between Microsoft and OpenAI, which has raised concerns among other national competition authorities regarding potential competition law issues. While it is expected that the partnership will potentially accelerate innovation, it also raises concerns about potential anticompetitive effects such as market foreclosure or the creation of barriers to entry for competitors and, therefore, has been under consideration in the German and UK courts. The problem here is in detecting and proving whether collusion is taking place. 

The Role of Policy and Regulation

The uncertainties induced by AI regarding its effects on competition create the need for algorithmic transparency and accountability in mitigating the risks of AI-driven collusion. It leads to the need to build and create regulatory frameworks that mandate the disclosure of algorithmic methodologies and establish a set of clear guidelines for the development of AI and its deployment. These frameworks or guidelines should encourage an environment of collaboration between competition watchdogs and AI experts. 

The global best practices and emerging trends in AI regulation already include respect for human rights, sustainability, transparency and strong risk management. The EU AI Act could serve as a model for other jurisdictions, as it outlines measures to ensure accountability and mitigate risks. The key goal is to tailor AI regulations to address perceived risks while incorporating core values such as privacy, non-discrimination, transparency, and security.

Promoting Innovation Without Stifling Competition

Policymakers need to ensure that they balance regulatory measures with innovation scope and that the two priorities do not hinder each other. 

1. Create adaptive and forward-thinking regulatory approaches to keep pace with technological advancements that take place at the pace of development and allow for quick adjustments in response to new AI capabilities and market behaviours.n
2. Competition watchdogs need to recruit domain experts to assess competition amid rapid changes in the technology landscape. Create a multi-stakeholder approach that involves regulators, industry leaders, technologists and academia who can create inclusive and ethical AI policies. 
3. Businesses can be provided incentives such as recognition through certifications, grants or benefits in acknowledgement of adopting ethical AI practices. 
4. Launch studies such as the CCI’s market study to study the impact of AI on competition. This can lead to the creation of a driving force for sustainable growth with technological advancements. 

Conclusion: AI and the Future of Competition

We must promote a multi-stakeholder approach that enhances regulatory oversight, and incentivising ethical AI practices. This is needed to strike a delicate balance that safeguards competition and drives sustainable growth. As AI continues to redefine industries, embracing collaborative, inclusive, and forward-thinking policies will be critical to building an equitable and innovative digital future. 

The lawmakers and policymakers engaged in the drafting of the frameworks need to ensure that they are adaptive to change and foster innovation. It is necessary to note that fair competition and innovation are not mutually exclusive goals, they are complementary to each other. Therefore, a regulatory framework that promotes transparency, accountability, and fairness in AI deployment must be established.

References

• https://www.thehindu.com/sci-tech/technology/ai-has-potential-to-aid-cartelisation-fair-competition-integral-for-sustainable-growth-cci-chief/article69041922.ece 
• https://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-market-74851580.html 
• https://www.ey.com/en_in/insights/ai/how-to-navigate-global-trends-in-artificial-intelligence-regulation#:~:text=Six%20regulatory%20trends%20in%20Artificial%20Intelligence&text=These%20include%20respect%20for%20human,based%20approach%20to%20AI%20regulation. ‍
• https://www.business-standard.com/industry/news/ai-has-potential-to-aid-fair-competition-for-sustainable-growth-cci-chief-124122900221_1.html