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Privacy
AI Gaming AI Model AI Systems AI technology Data Privacy data security Data Technology Microsoft Privacy

Microsoft MUSE AI: Revolutionizing Game Development with WHAM and Ethical Challenges

 

Microsoft has developed MUSE, a cutting-edge AI model that is set to redefine how video games are created and experienced. This advanced system leverages artificial intelligence to generate realistic gameplay elements, making it easier for developers to design and refine virtual environments. By learning from vast amounts of gameplay data, MUSE can predict player actions, create immersive worlds, and enhance game mechanics in ways that were previously impossible. While this breakthrough technology offers significant advantages for game development, it also raises critical discussions around data security and ethical AI usage. 

One of MUSE’s most notable features is its ability to automate and accelerate game design. Developers can use the AI model to quickly prototype levels, test different gameplay mechanics, and generate realistic player interactions. This reduces the time and effort required for manual design while allowing for greater experimentation and creativity. By streamlining the development process, MUSE provides game studios—both large and small—the opportunity to push the boundaries of innovation. 

The AI system is built on an advanced framework that enables it to interpret and respond to player behaviors. By analyzing game environments and user inputs, MUSE can dynamically adjust in-game elements to create more engaging experiences. This could lead to more adaptive and personalized gaming, where the AI tailors challenges and story progression based on individual player styles. Such advancements have the potential to revolutionize game storytelling and interactivity. 

Despite its promising capabilities, the introduction of AI-generated gameplay also brings important concerns. The use of player data to train these models raises questions about privacy and transparency. Developers must establish clear guidelines on how data is collected and ensure that players have control over their information. Additionally, the increasing role of AI in game creation sparks discussions about the balance between human creativity and machine-generated content. 

While AI can enhance development, it is essential to preserve the artistic vision and originality that define gaming as a creative medium. Beyond gaming, the technology behind MUSE could extend into other industries, including education and simulation-based training. AI-generated environments can be used for virtual learning, professional skill development, and interactive storytelling in ways that go beyond traditional gaming applications. 

As AI continues to evolve, its role in shaping digital experiences will expand, making it crucial to address ethical considerations and responsible implementation. The future of AI-driven game development is still unfolding, but MUSE represents a major step forward. 

By offering new possibilities for creativity and efficiency, it has the potential to change how games are built and played. However, the industry must carefully navigate the challenges that come with AI’s growing influence, ensuring that technological progress aligns with ethical and artistic integrity.
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GDPR
AI governance AI Security AI technology CCPA Compliance Cyber Security Data Privacy data security GDPR

The Need for Unified Data Security, Compliance, and AI Governance

 

Businesses are increasingly dependent on data, yet many continue to rely on outdated security infrastructures and fragmented management approaches. These inefficiencies leave organizations vulnerable to cyber threats, compliance violations, and operational disruptions. Protecting data is no longer just about preventing breaches; it requires a fundamental shift in how security, compliance, and AI governance are integrated into enterprise strategies. A proactive and unified approach is now essential to mitigate evolving risks effectively. 

The rapid advancement of artificial intelligence has introduced new security challenges. AI-powered tools are transforming industries, but they also create vulnerabilities if not properly managed. Many organizations implement AI-driven applications without fully understanding their security implications. AI models require vast amounts of data, including sensitive information, making governance a critical priority. Without robust oversight, these models can inadvertently expose private data, operate without transparency, and pose compliance challenges as new regulations emerge. 

Businesses must ensure that AI security measures evolve in tandem with technological advancements to minimize risks. Regulatory requirements are also becoming increasingly complex. Governments worldwide are enforcing stricter data privacy laws, such as GDPR and CCPA, while also introducing new regulations specific to AI governance. Non-compliance can result in heavy financial penalties, reputational damage, and operational setbacks. Businesses can no longer treat compliance as an afterthought; instead, it must be an integral part of their data security strategy. Organizations must shift from reactive compliance measures to proactive frameworks that align with evolving regulatory expectations. 

Another significant challenge is the growing issue of data sprawl. As businesses store and manage data across multiple cloud environments, SaaS applications, and third-party platforms, maintaining control becomes increasingly difficult. Security teams often lack visibility into where sensitive information resides, making it harder to enforce access controls and protect against cyber threats. Traditional security models that rely on layering additional tools onto existing infrastructures are no longer effective. A centralized, AI-driven approach to security and governance is necessary to address these risks holistically. 

Forward-thinking businesses recognize that managing security, compliance, and AI governance in isolation is inefficient. A unified approach consolidates risk management efforts into a cohesive, scalable framework. By breaking down operational silos, organizations can streamline workflows, improve efficiency through AI-driven automation, and proactively mitigate security threats. Integrating compliance and security within a single system ensures better regulatory adherence while reducing the complexity of data management. 

To stay ahead of emerging threats, organizations must modernize their approach to data security and governance. Investing in AI-driven security solutions enables businesses to automate data classification, detect vulnerabilities, and safeguard sensitive information at scale. Shifting from reactive compliance measures to proactive strategies ensures that regulatory requirements are met without last-minute adjustments. Moving away from fragmented security solutions and adopting a modular, scalable platform allows businesses to reduce risk and maintain resilience in an ever-evolving digital landscape. Those that embrace a forward-thinking, unified strategy will be best positioned for long-term success.
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South Korea
AI Apps AI technology Data Privacy data security DeepSeek Privacy privacy laws South Korea

South Korea Blocks DeepSeek AI App Downloads Amid Data Security Investigation

 

South Korea has taken a firm stance on data privacy by temporarily blocking downloads of the Chinese AI app DeepSeek. The decision, announced by the Personal Information Protection Commission (PIPC), follows concerns about how the company collects and handles user data. 

While the app remains accessible to existing users, authorities have strongly advised against entering personal information until a thorough review is complete. DeepSeek, developed by the Chinese AI Lab of the same name, launched in South Korea earlier this year. Shortly after, regulators began questioning its data collection practices. 

Upon investigation, the PIPC discovered that DeepSeek had transferred South Korean user data to ByteDance, the parent company of TikTok. This revelation raised red flags, given the ongoing global scrutiny of Chinese tech firms over potential security risks. South Korea’s response reflects its increasing emphasis on digital sovereignty. The PIPC has stated that DeepSeek will only be reinstated on app stores once it aligns with national privacy regulations. 

The AI company has since appointed a local representative and acknowledged that it was unfamiliar with South Korea’s legal framework when it launched the service. It has now committed to working with authorities to address compliance issues. DeepSeek’s privacy concerns extend beyond South Korea. Earlier this month, key government agencies—including the Ministry of Trade, Industry, and Energy, as well as Korea Hydro & Nuclear Power—temporarily blocked the app on official devices, citing security risks. 

Australia has already prohibited the use of DeepSeek on government devices, while Italy’s data protection agency has ordered the company to disable its chatbot within its borders. Taiwan has gone a step further by banning all government departments from using DeepSeek AI, further illustrating the growing hesitancy toward Chinese AI firms. 

DeepSeek, founded in 2023 by Liang Feng in Hangzhou, China, has positioned itself as a competitor to OpenAI’s ChatGPT, offering a free, open-source AI model. However, its rapid expansion has drawn scrutiny over potential data security vulnerabilities, especially in regions wary of foreign digital influence. South Korea’s decision underscores the broader challenge of regulating artificial intelligence in an era of increasing geopolitical and technological tensions. 

As AI-powered applications become more integrated into daily life, governments are taking a closer look at the entities behind them, particularly when sensitive user data is involved. For now, DeepSeek’s future in South Korea hinges on whether it can address regulators’ concerns and demonstrate full compliance with the country’s strict data privacy standards. Until then, authorities remain cautious about allowing the app’s unrestricted use.
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DeepSeek
AI Models AI technology AI Threat China Cyber Security Data Mining Data Privacy data security DeepSeek

DeepSeek AI Raises Data Security Concerns Amid Ties to China

 

The launch of DeepSeek AI has created waves in the tech world, offering powerful artificial intelligence models at a fraction of the cost compared to established players like OpenAI and Google. 

However, its rapid rise in popularity has also sparked serious concerns about data security, with critics drawing comparisons to TikTok and its ties to China. Government officials and cybersecurity experts warn that the open-source AI assistant could pose a significant risk to American users. 

On Thursday, two U.S. lawmakers announced plans to introduce legislation banning DeepSeek from all government devices, citing fears that the Chinese Communist Party (CCP) could access sensitive data collected by the app. This move follows similar actions in Australia and several U.S. states, with New York recently enacting a statewide ban on government systems. 

The growing concern stems from China’s data laws, which require companies to share user information with the government upon request. Like TikTok, DeepSeek’s data could be mined for intelligence purposes or even used to push disinformation campaigns. Although the AI app is the current focus of security conversations, experts say that the risks extend beyond any single model, and users should exercise caution with all AI systems. 

Unlike social media platforms that users can consciously avoid, AI models like DeepSeek are more difficult to track. Dimitri Sirota, CEO of BigID, a cybersecurity company specializing in AI security compliance, points out that many companies already use multiple AI models, often switching between them without users’ knowledge. This fluidity makes it challenging to control where sensitive data might end up. 

Kelcey Morgan, senior manager of product management at Rapid7, emphasizes that businesses and individuals should take a broad approach to AI security. Instead of focusing solely on DeepSeek, companies should develop comprehensive practices to protect their data, regardless of the latest AI trend. The potential for China to use DeepSeek’s data for intelligence is not far-fetched, according to cybersecurity experts. 

With significant computing power and data processing capabilities, the CCP could combine information from multiple sources to create detailed profiles of American users. Though this might not seem urgent now, experts warn that today’s young, casual users could grow into influential figures worth targeting in the future. 

To stay safe, experts advise treating AI interactions with the same caution as any online activity. Users should avoid sharing sensitive information, be skeptical of unusual questions, and thoroughly review an app’s terms and conditions. Ultimately, staying informed and vigilant about where and how data is shared will be critical as AI technologies continue to evolve and become more integrated into everyday life.
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Vulnerabilities and Exploits
Data Privacy Locked Device Security Patch Tech Giant Vulnerabilities and Exploits

Apple Patches Zero-Day Flaw allowing Third-Party Access to Locked Devices

 

Tech giant Apple fixed a vulnerability that "may have been leveraged in a highly sophisticated campaign against specific targeted individuals" in its iOS and iPadOS mobile operating system updates earlier this week.

According to the company's release notes for iOS 18.3.1 and iPadOS 18.3.1, the vulnerability made it possible to disable USB Restricted Mode "on a locked device." A security feature known as USB Restricted Mode was first introduced in 2018 and prevents an iPhone or iPad from sending data via a USB connection if the device hasn't been unlocked for seven days. 

In order to make it more challenging for law enforcement or criminals employing forensic tools to access data on those devices, Apple announced a new security feature last year which triggers devices to reboot if they are not unlocked for 72 hours. 

Based on the language used in its security update, Apple suggests that the attacks were most likely carried out with physical control of a person's device, implying that whoever exploited this vulnerability had to connect to the person's Apple devices using a forensics device such as Cellebrite or Graykey, two systems that allow law enforcement to unlock and access data stored on iPhones and other devices. Bill Marczak, a senior researcher at Citizen Lab, a University of Toronto group that studies cyberattacks on civil society, uncovered the flaw.

However, it remains unclear who was responsible for exploiting this vulnerability and against whom it was used. However, there have been reported instances in the past in which law enforcement agencies employed forensic tools, which often exploit zero-day flaws in devices such as the iPhone, to unlock them and access the data inside.

Amnesty International published a report in December 2024 detailing a string of assaults by Serbian authorities in which they utilised Cellebrite to unlock the phones of journalists and activists in the nation before infecting them with malware. According to security experts, the Cellebrite forensic tools were probably used "widely" on members of civil society, Amnesty stated.
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Data Theft
Amazon class action lawsuits Data Breach Data Harvesting SDK Data Privacy Data Safety User Data data security Data Theft

Amazon Faces Lawsuit Over Alleged Secret Collection and Sale of User Location Data

 

A new class action lawsuit accuses Amazon of secretly gathering and monetizing location data from millions of California residents without their consent. The legal complaint, filed in a U.S. District Court, alleges that Amazon used its Amazon Ads software development kit (SDK) to extract sensitive geolocation information from mobile apps. According to the lawsuit, plaintiff Felix Kolotinsky of San Mateo claims 

Amazon embedded its SDK into numerous mobile applications, allowing the company to collect precise, timestamped location details. Users were reportedly unaware that their movements were being tracked and stored. Kolotinsky states that his own data was accessed through the widely used “Speedtest by Ookla” app. The lawsuit contends that Amazon’s data collection practices could reveal personal details such as users’ home addresses, workplaces, shopping habits, and frequented locations. 

It also raises concerns that this data might expose sensitive aspects of users’ lives, including religious practices, medical visits, and sexual orientation. Furthermore, the complaint alleges that Amazon leveraged this information to build detailed consumer profiles for targeted advertising, violating California’s privacy and computer access laws. This case is part of a broader legal pushback against tech companies and data brokers accused of misusing location tracking technologies. 

In a similar instance, the state of Texas recently filed a lawsuit against Allstate, alleging the insurance company monitored drivers’ locations via mobile SDKs and sold the data to other insurers. Another legal challenge in 2024 targeted Twilio, claiming its SDK unlawfully harvested private user data. Amazon has faced multiple privacy-related controversies in recent years. In 2020, it terminated several employees for leaking customer data, including email addresses and phone numbers, to third parties. 

More recently, in June 2023, Amazon agreed to a $31 million settlement over privacy violations tied to its Alexa voice assistant and Ring doorbell products. That lawsuit accused the company of storing children’s voice recordings indefinitely and using them to refine its artificial intelligence, breaching federal child privacy laws. 

Amazon has not yet issued a response to the latest allegations. The lawsuit, Kolotinsky v. Amazon.com Inc., seeks compensation for affected California residents and calls for an end to the company’s alleged unauthorized data collection practices.
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University of Crete
Advanced Technology Data Privacy Hologram Optical Encryption University of Crete

Researchers at University of Crete Developes Uncrackable Optical Encryption

 

An optical encryption technique developed by researchers at the Foundation for Research and Technology Hellas (FORTH) and the University of Crete in Greece is claimed to provide an exceptionally high level of security. 

According to Optica, the system decodes the complex spatial information in the scrambled images by retrieving intricately jumbled information from a hologram using trained neural networks.

“From rapidly evolving digital currencies to governance, healthcare, communications and social networks, the demand for robust protection systems to combat digital fraud continues to grow," stated project leader Stelios Tzortzakis.

"Our new system achieves an exceptional level of encryption by utilizing a neural network to generate the decryption key, which can only be created by the owner of the encryption system.”

Optical encryption secures data at the network's optical transport level, avoiding slowing down the overall system with additional hardware at the non-optical levels. This strategy may make it easier to establish authentication procedures at both ends of the transfer to verify data integrity. 

The researchers investigated whether ultrashort laser filaments travelling in a highly nonlinear and turbulent medium might transfer optical information, such as a target's shape, that had been encoded in holograms of those shapes. The researchers claim that this renders the original data totally scrambled and unretrievable by any physical modelling or experimental method. 

Data scrambled by passage via ethanol liquid 

A femtosecond laser was used in the experimental setup to pass through a prepared hologram and into a cuvette that contained liquid ethanol. A CCD sensor recorded the optical data, which appeared as a highly scrambled and disorganised image due to laser filamentation and thermally generated turbulence in the liquid. 

"The challenge was figuring out how to decrypt the information," said Tzortzakis. “We came up with the idea of training neural networks to recognize the incredibly fine details of the scrambled light patterns. By creating billions of complex connections, or synapses, within the neural networks, we were able to reconstruct the original light beam shapes.”

In trials, the method was used to encrypt and decrypt thousands of handwritten digits and reference forms. After optimising the experimental approach and training the neural network, the encoded images were properly retrieved 90 to 95 percent of the time, with additional improvements potential with more thorough neural network training. 

The team is now working on ways to use a less expensive and bulkier laser system, as a necessary step towards commercialising the approach for a variety of potential industrial encryption uses. 

“Our study provides a strong foundation for many applications, especially cryptography and secure wireless optical communication, paving the way for next-generation telecommunication technologies," concluded Tzortzakis.
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privacy laws
Cyber Security Data Privacy data security Elon Musk Email OPM data breach privacy laws

Federal Employees Sue OPM Over Alleged Unauthorized Email Database

 

Two federal employees have filed a lawsuit against the Office of Personnel Management (OPM), alleging that a newly implemented email system is being used to compile a database of federal workers without proper authorization. The lawsuit raises concerns about potential misuse of employee information and suggests a possible connection to Elon Musk, though no concrete evidence has been provided. The controversy began when OPM sent emails to employees, claiming it was testing a new communication system. Recipients were asked to reply to confirm receipt, but the plaintiffs argue that this was more than a routine test—it was an attempt to secretly create a list of government workers for future personnel decisions, including potential job cuts.

Key Allegations and Concerns

The lawsuit names Amanda Scales, a former executive at Musk’s artificial intelligence company, xAI, who now serves as OPM’s chief of staff. The plaintiffs suspect that her appointment may be linked to the email system’s implementation, though they have not provided definitive proof. They claim that an unauthorized email server was set up within OPM’s offices, making it appear as though messages were coming from official government sources when they were actually routed through a separate system.

An anonymous OPM employee’s post, cited in the lawsuit, alleges that the agency’s Chief Information Officer, Melvin Brown, was sidelined after refusing to implement the email list. The post further claims that a physical server was installed at OPM headquarters, enabling external entities to send messages that appeared to originate from within the agency. These allegations have raised serious concerns about transparency and data security within the federal government.

The lawsuit also argues that the email system violates the E-Government Act of 2002, which requires federal agencies to conduct strict privacy assessments before creating databases containing personal information. The plaintiffs contend that OPM bypassed these requirements, putting employees at risk of having their information used without consent.

Broader Implications and Employee Anxiety

Beyond the legal issues, the case reflects growing anxiety among federal employees about potential restructuring under the new administration. Reports suggest that significant workforce reductions may be on the horizon, and the lawsuit implies that the email system could play a role in streamlining mass layoffs. If the allegations are proven true, it could have major implications for how employee information is collected and used in the future.

As of now, OPM has not officially responded to the allegations, and there is no definitive proof linking the email system to Musk or any specific policy agenda. However, the case has sparked widespread discussions about transparency, data security, and the ethical use of employee information within the federal government. The lawsuit highlights the need for stricter oversight and accountability to ensure that federal employees’ privacy rights are protected.

The lawsuit against OPM underscores the growing tension between federal employees and government agencies over data privacy and transparency. While the allegations remain unproven, they raise important questions about the ethical use of employee information and the potential for misuse in decision-making processes. As the case unfolds, it could set a precedent for how federal agencies handle employee data and implement new systems in the future. For now, the controversy serves as a reminder of the importance of safeguarding privacy and ensuring accountability in government operations.

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Technology
AI Learning Artificial Intelligence Data Privacy Personalised learning Technology

AI-Powered Personalized Learning: Revolutionizing Education

 

In an era where technology permeates every aspect of our lives, education is undergoing a transformative shift. Imagine a classroom where each student’s learning experience is tailored to their unique needs, interests, and pace. This is no longer a distant dream but a rapidly emerging reality, thanks to the revolutionary impact of artificial intelligence (AI). Personalized learning, once a buzzword, has become a game-changer, with AI at the forefront of this transformation. In this blog, we’ll explore how AI is driving the personalized learning revolution, its benefits and challenges, and what the future holds for this exciting frontier in education.

Personalized learning is an educational approach that tailors teaching and learning experiences to meet the unique needs, strengths, and interests of each student. Unlike traditional one-size-fits-all methods, personalized learning aims to provide a customized educational experience that accommodates diverse learning styles, paces, and preferences. The goal is to enhance student engagement and achievement by addressing individual characteristics such as academic abilities, prior knowledge, and personal interests.

The Role of AI in Personalized Learning

AI is playing a pivotal role in making personalized learning a reality. Here’s how:

  • Adaptive Learning Platforms: These platforms use AI to dynamically adjust educational content based on a student’s performance, learning style, and pace. By analyzing how students interact with the material, adaptive systems can modify task difficulty and provide tailored resources to meet individual needs. This ensures a personalized learning experience that evolves as students progress.
  • Analyzing Student Performance and Behavior: AI-driven analytics processes vast amounts of data on student behavior, performance, and engagement to identify patterns and trends. These insights help educators pinpoint areas where students excel or struggle, enabling timely interventions and support.

Benefits of AI-Driven Personalized Learning

The integration of AI into personalized learning offers numerous advantages:

  1. Enhanced Student Engagement: AI-powered personalized learning makes education more relevant and engaging by adapting content to individual interests and needs. This approach fosters a deeper connection to the subject matter and keeps students motivated.
  2. Improved Learning Outcomes: Studies have shown that personalized learning tools lead to higher test scores and better grades. By addressing individual academic gaps, AI ensures that students master concepts more effectively.
  3. Efficient Use of Resources: AI streamlines lesson planning and focuses on areas where students need the most support. By automating repetitive tasks and providing actionable insights, AI helps educators manage their time and resources more effectively.

Challenges and Considerations

While AI-driven personalized learning holds immense potential, it also presents several challenges:

  1. Data Privacy and Security: Protecting student data is a critical concern. Schools and technology providers must implement robust security measures and transparent data policies to safeguard sensitive information.
  2. Equity and Access: Ensuring equal access to AI-powered tools is essential to prevent widening educational disparities. Efforts must be made to provide all students with the necessary devices and internet connectivity.
  3. Teacher Training and Integration: Educators need comprehensive training to effectively use AI tools in the classroom. Ongoing support and resources are crucial to help teachers integrate these technologies into their lesson plans.

AI is revolutionizing education by enabling personalized learning experiences that cater to each student’s unique needs and pace. By enhancing engagement, improving outcomes, and optimizing resource use, AI is shaping the future of education. However, as we embrace these advancements, it is essential to address challenges such as data privacy, equitable access, and teacher training. With the right approach, AI-powered personalized learning has the potential to transform education and unlock new opportunities for students worldwide.

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Web browser
Cyber Security Data Privacy search engine Tor Browser Web browser

Best Tor Browser Substitute for Risk-Free Web Surfing

 


 Anonymous Browsing: Tools and Extensions for Enhanced Privacy

Anonymous browsing is designed to conceal your IP address and location, making it appear as though you are in a different region. This feature is particularly useful in safeguarding your private information and identity from third parties.

Many users assume that using Incognito (or Private) mode is the simplest way to achieve anonymity. However, this is not entirely accurate. Incognito mode’s primary purpose is to erase your browsing history, cookies, and temporary data once the session ends. While this feature is useful, it does not anonymize your activity or prevent your internet service provider (ISP) and websites from tracking your behavior.

Secure DNS, or DNS over HTTPS, offers another layer of security by encrypting your DNS queries. However, it only secures your searches and does not provide complete anonymity. For discreet browsing, certain browser add-ons can be helpful. While not flawless, these extensions can enhance your privacy. Alternatively, for maximum anonymity, experts recommend using the Tor Browser, which routes your internet traffic through multiple servers for enhanced protection.

Installing privacy-focused extensions on Chrome or Firefox is straightforward. Navigate to your browser's extension or add-on store, search for the desired extension, and click "Add to Chrome" or "Add to Firefox." Firefox will ask for confirmation before installation. Always ensure an extension’s safety by reviewing its ratings, user reviews, and developer credibility before adding it to your browser.

Top Privacy Tools for Anonymous Browsing

Cybersecurity experts recommend the following tools for enhanced privacy and discretion:

AnonymoX

AnonymoX is a browser add-on that enables anonymous and private internet browsing. It allows you to change your IP address and country, functioning like a lightweight VPN. With a single click, you can switch locations and conceal your identity. However, the free version includes ads, speed limitations, and restricted capabilities. While AnonymoX is a handy tool in certain situations, it is not recommended for constant use due to its impact on browser performance.

Browsec VPN

A VPN remains one of the most reliable methods to ensure online anonymity, and Browsec VPN is an excellent choice. This extension encrypts your traffic, offers multiple free virtual locations, and allows secure IP switching. Its user-friendly interface enables quick country changes and one-click activation or deactivation of features.

Browsec VPN also offers a Smart Settings feature, allowing you to configure the VPN for specific websites, bypass it for others, and set preset countries for selected sites. Upgrading to the premium version ($1.99 per month) unlocks additional features, such as faster speeds, access to over 40 countries, timezone matching, and custom servers for particular sites.

DuckDuckGo

DuckDuckGo is a trusted tool for safeguarding your privacy. This browser extension sets DuckDuckGo as your default search engine, blocks website trackers, enforces HTTPS encryption, prevents fingerprinting, and disables tracking cookies. While DuckDuckGo itself does not include a VPN, upgrading to the Pro subscription ($9.99 per month) provides access to the DuckDuckGo VPN, which encrypts your data and hides your IP address for enhanced anonymity.

Although Incognito mode and Secure DNS offer basic privacy features, they do not provide complete anonymity. To browse discreetly and protect your online activity, consider using browser extensions such as AnonymoX, Browsec VPN, or DuckDuckGo. For maximum security, the Tor Browser remains the gold standard for anonymous browsing.

Regardless of the tools you choose, always exercise caution when browsing the internet. Stay informed, regularly review your privacy settings, and ensure your tools are up-to-date to safeguard your digital footprint.

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Privacy Policy
CFPB Cyber Security Data Brokers Data Privacy data security online data risks Privacy Policy

Privacy Expert Urges Policy Overhaul to Combat Data Brokers’ Practices

Privacy expert Yael Grauer, known for creating the Big Ass Data Broker Opt-Out List (BADBOOL), has a message for those frustrated with the endless cycle of removing personal data from brokers’ databases: push lawmakers to implement meaningful policy reforms. Speaking at the ShmooCon security conference, Grauer likened the process of opting out to an unwinnable game of Whac-A-Mole, where users must repeatedly fend off new threats to their data privacy. 

Grauer’s BADBOOL guide has served as a resource since 2017, offering opt-out instructions for numerous data brokers. These entities sell personal information to advertisers, insurers, law enforcement, and even federal agencies. Despite such efforts, the sheer number of brokers and their data sources makes it nearly impossible to achieve a permanent opt-out. Commercial data-removal services like DeleteMe offer to simplify this task, but Grauer’s research for Consumer Reports found them less effective than advertised. 

The study, released in August, gave its highest ratings to Optery and EasyOptOuts, but even these platforms left gaps. “None of these services cover everything,” Grauer warned, emphasizing that even privacy experts struggle to protect their data. Grauer stressed the need for systemic solutions, pointing to state-led initiatives like California’s Delete Act. This legislation aims to create a universal opt-out system through a state-run data broker registry. While similar proposals have surfaced at the federal level, Congress has repeatedly failed to pass comprehensive privacy laws. 

Other states have implemented statutes like Maryland’s Online Data Privacy Act, which restricts the sale of sensitive data. However, these laws often allow brokers to deal in publicly available information, such as home addresses found on property-tax sites. Grauer criticized these carve-outs, noting that they undermine broader privacy protections. One promising development is the Consumer Financial Protection Bureau’s (CFPB) proposal to classify data brokers as consumer reporting agencies under the Fair Credit Reporting Act. 

This designation would impose stricter controls on their operations. Grauer urged attendees to voice their support for this initiative through the CFPB’s public-comments form, open until March 3. Despite these efforts, Grauer expressed skepticism about Congress’s ability to act. She warned of political opposition to the CFPB itself, citing calls from conservative groups and influential figures to dismantle the agency. 

Grauer encouraged attendees to engage with their representatives to protect this regulatory body and advocate for robust privacy legislation. Ultimately, Grauer argued, achieving meaningful privacy protections will require collective action, from influencing policymakers to supporting state and federal initiatives aimed at curbing data brokers’ pervasive reach.
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United States
Data Breach Data Privacy K-12 Schools PowerSchool United States

PowerSchool Breach Compromises Student and Teacher Data From K–12 Districts

 

PowerSchool, a widely used software serving thousands of K–12 schools in the United States, has suffered a major cybersecurity breach.

The Breach has left several schools worried about the potential exposure of critical student and faculty data. With over 45 million users relying on the platform, the breach raises serious concerns about data security in the United States' educational system. 

PowerSchool is a cloud-based software platform used by several schools to manage student information, grades, attendance, and contact with parents. The breach reportedly occurred through one of its customer support portals, when fraudsters gained unauthorised access using compromised credentials. 

Magnitude of the data breach

According to PowerSchool, the leaked data consists mainly of contact details such as names and addresses. However, certain school districts' databases might have included more sensitive data, such as Social Security numbers, medical information, and other personally identifiable information.

The company has informed users that the breach did not impact any other PowerSchool products, although the exact scope of the exposure is still being assessed. 

"We have taken all appropriate steps to prevent the data involved from further unauthorised access or misuse," PowerSchool said in response to the incident, as reported by Valley News Live. “We are equipped to conduct a thorough notification process to all impacted individuals.”

Additionally, the firm has promised to keep helping law enforcement in their efforts to determine how the breach occurred and who might be accountable.

Ongoing investigation and response 

Cybersecurity experts have already begun to investigate the hack, and both PowerSchool and local authorities are attempting to determine the exact scope of the incident. 

As the investigation continues, many people are pushing for stronger security measures to protect sensitive data in the educational sector, especially as more institutions rely on cloud-based systems for day-to-day activities. 

According to Valley News Live, PowerSchool has expressed their commitment to resolving the situation, saying, "We are deeply concerned by this incident and are doing everything we can to support the affected districts and families.”
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Social Media
Account security Cyber Security Cyber Security and Privacy Data Privacy Digital Footprint Online Privacy Social Media

Practical Tips to Avoid Oversharing and Protect Your Online Privacy

 

In today’s digital age, the line between public and private life often blurs. Social media enables us to share moments, connect, and express ourselves. However, oversharing online—whether through impulsive posts or lax privacy settings—can pose serious risks to your security, privacy, and relationships. 

Oversharing involves sharing excessive personal information, such as travel plans, daily routines, or even seemingly harmless details like pet names or childhood memories. Cybercriminals can exploit this information to answer security questions, track your movements, or even plan crimes like burglary. 

Additionally, posts assumed private can be screenshotted, shared, or retrieved long after deletion, making them a permanent part of your digital footprint. Beyond personal risks, oversharing also contributes to a growing culture of surveillance. Companies collect your data to build profiles for targeted ads, eroding your control over your personal information. 

The first step in safeguarding your online privacy is understanding your audience. Limit your posts to trusted friends or specific groups using privacy tools on social media platforms. Share updates after events rather than in real-time to protect your location. Regularly review and update your account privacy settings, as platforms often change their default configurations. 

Set your profiles to private, accept connection requests only from trusted individuals, and think twice before sharing. Ask yourself if the information is something you would be comfortable sharing with strangers, employers, or cybercriminals. Avoid linking unnecessary accounts, as this creates vulnerabilities if one is compromised. 

Carefully review the permissions you grant to apps or games, and disconnect those you no longer use. For extra security, enable two-factor authentication and use strong, unique passwords for each account. Oversharing isn’t limited to social media posts; apps and devices also collect data. Disable unnecessary location tracking, avoid geotagging posts, and scrub metadata from photos and videos before sharing. Be mindful of background details in images, such as visible addresses or documents. 

Set up alerts to monitor your name or personal details online, and periodically search for yourself to identify potential risks. Children and teens are especially vulnerable to the risks of oversharing. Teach them about privacy settings, the permanence of posts, and safe sharing habits. Simple exercises, like the “Granny Test,” can encourage thoughtful posting. 

Reducing online activity and spending more time offline can help minimize oversharing while fostering stronger in-person connections. By staying vigilant and following these tips, you can enjoy the benefits of social media while keeping your personal information safe.
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Modern Vehicles
Cyber Security Data Privacy data protection challenges Data Sharing Data Technology Electric Vehicles Modern Vehicles

Las Vegas Tesla Cybertruck Explosion: How Data Transformed the Investigation

 


After a rented Tesla Cybertruck caught fire outside the Trump International Hotel in Las Vegas, Tesla’s advanced data systems became a focal point in the investigation. The explosion, which resulted in a fatality, initially raised concerns about electric vehicle safety. However, Tesla’s telemetry data revealed the incident was caused by an external explosive device, not a malfunction in the vehicle.

Tesla’s telemetry systems played a key role in retracing the Cybertruck’s travel route from Colorado to Las Vegas. Las Vegas Sheriff Kevin McMahill confirmed that Tesla’s supercharger network provided critical data about the vehicle’s movements, helping investigators identify its journey.

Modern Tesla vehicles are equipped with sensors, cameras, and mobile transmitters that continuously send diagnostic and location data. While this information is typically encrypted and anonymized, Tesla’s privacy policy allows for specific data access during safety-related incidents, such as video footage and location history.

Tesla CEO Elon Musk confirmed that telemetry data indicated the vehicle’s systems, including the battery, were functioning normally at the time of the explosion. The findings also linked the incident to a possible terror attack in New Orleans earlier the same day, further emphasizing the value of Tesla’s data in broader investigations.

Tesla’s Role in Criminal Investigations

Tesla vehicles offer features like Sentry Mode, which acts as a security camera when parked. This feature has been instrumental in prior investigations. For example:

  • Footage from a Tesla Model X helped Oakland police charge suspects in a murder case. The video, stored on a USB drive within the vehicle, was accessed with a warrant.

Such data-sharing capabilities demonstrate the role of modern vehicles in aiding law enforcement.

Privacy Concerns Surrounding Tesla’s Data Practices

While Tesla’s data-sharing has been beneficial, it has also raised concerns among privacy advocates. In 2023, the Mozilla Foundation criticized the automotive industry for collecting excessive personal information, naming Tesla as one of the top offenders. Critics argue that this extensive data collection, while helpful in solving crimes, poses risks to individual privacy.

Data collected by Tesla vehicles includes:

  • Speed
  • Location
  • Video feeds from multiple cameras

This data is essential for developing autonomous driving software but can also be accessed during emergencies. For example, vehicles automatically transmit accident videos and provide location details during crises.

The Las Vegas explosion highlights the dual nature of connected vehicles: they provide invaluable tools for law enforcement while sparking debates about data privacy and security. As cars become increasingly data-driven, the challenge lies in balancing public safety with individual privacy rights.

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Online Privacy
2FA chat records Cyber Breaches Cyber Security data deletion Data Privacy data security Digital Footprint Online Privacy

How to Declutter and Safeguard Your Digital Privacy

 

As digital privacy concerns grow, taking steps to declutter your online footprint can help protect your sensitive information. Whether you’re worried about expanding government surveillance or simply want to clean up old data, there are practical ways to safeguard your digital presence. 

One effective starting point is reviewing and managing old chat histories. Platforms like Signal and WhatsApp, which use end-to-end encryption, store messages only on your device and those of your chat recipients. This encryption ensures governments or hackers need direct access to devices to view messages. However, even this security isn’t foolproof. 

Non-encrypted platforms like Slack, Facebook Messenger, and Google Chat store messages on cloud servers. While these may be encrypted to prevent theft, the platforms themselves hold the decryption keys. This means they can access your data and comply with government requests, no matter how old the messages. Long-forgotten chats can reveal significant details about your life, associations, and beliefs, making it crucial to delete unnecessary data. 

Kenn White, security principal at MongoDB, emphasizes the importance of regular digital cleaning. “Who you were five or ten years ago is likely different from who you are today,” he notes. “It’s worth asking if you need to carry old inside jokes or group chats forward to every new device.” 

Some platforms offer tools to help you manage old messages. For example, Apple’s Messages app allows users to enable auto-deletion. On iOS, navigate to Settings > Apps > Messages, then select “Keep Messages” and choose to retain messages for 30 days, one year, or forever. 

Similarly, Slack automatically deletes data older than a year for free-tier users, while paid plans retain data indefinitely unless administrators set up rolling deletions. However, on workplace platforms, users typically lack control over such policies, highlighting the importance of discretion in professional communications. 

While deleting old messages is a key step, consider extending your cleanup efforts to other areas. Review your social media accounts, clear old posts, and minimize the information shared publicly. Also, download essential data to offline storage if you need long-term access without risking exposure. 

Finally, maintain strong security practices like enabling two-factor authentication (2FA) and regularly updating passwords. These measures can help protect your accounts, even if some data remains online. 

Regularly decluttering your digital footprint not only safeguards your privacy but also reduces the risk of sensitive data being exposed in breaches or exploited by malicious actors. By proactively managing your online presence, you can ensure a more secure and streamlined digital life.
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Protecting online travel accounts
Biometric data Data Privacy data security database EU Personal Data Privacy Privacy Invasion Protecting online travel accounts

The Intersection of Travel and Data Privacy: A Growing Concern

 

The evolving relationship between travel and data privacy is sparking significant debate among travellers and experts. A recent Spanish regulation requiring hotels and Airbnb hosts to collect personal guest data has particularly drawn criticism, with some privacy-conscious tourists likening it to invasive surveillance. This backlash highlights broader concerns about the expanding use of personal data in travel.

Privacy Concerns Across Europe

This trend is not confined to Spain. Across the European Union, regulations now mandate biometric data collection, such as fingerprints, for non-citizens entering the Schengen zone. Airports and border control points increasingly rely on these measures to streamline security and enhance surveillance. Advocates argue that such systems improve safety and efficiency, with Chris Jones of Statewatch noting their roots in international efforts to combat terrorism, driven by UN resolutions and supported by major global powers like the US, China, and Russia.

Challenges with Biometric and Algorithmic Systems

Despite their intended benefits, systems leveraging Passenger Name Record (PNR) data and biometrics often fall short of expectations. Algorithmic misidentifications can lead to unjust travel delays or outright denials. Biometric systems also face significant logistical and security challenges. While they are designed to reduce processing times at borders, system failures frequently result in delays. Additionally, storing such sensitive data introduces serious risks. For instance, the 2019 Marriott data breach exposed unencrypted passport details of millions of guests, underscoring the vulnerabilities in large-scale data storage.

The EU’s Ambitious Biometric Database

The European Union’s effort to create the world’s largest biometric database has sparked concern among privacy advocates. Such a trove of data is an attractive target for both hackers and intelligence agencies. The increasing use of facial recognition technology at airports—from Abu Dhabi’s Zayed International to London Heathrow—further complicates the privacy landscape. While some travelers appreciate the convenience, others fear the long-term implications of this data being stored and potentially misused.

Global Perspectives on Facial Recognition

Prominent figures like Elon Musk openly support these technologies, envisioning their adoption in American airports. However, critics argue that such measures often prioritize efficiency over individual privacy. In the UK, stricter regulations have limited the use of facial recognition systems at airports. Yet, alternative tracking technologies are gaining momentum, with trials at train stations exploring non-facial data to monitor passengers. This reflects ongoing innovation by technology firms seeking to navigate legal restrictions.

Privacy vs. Security: A Complex Trade-Off

According to Gus Hosein of Privacy International, borders serve as fertile ground for experiments in data-driven travel technologies, often at the expense of individual rights. These developments point to the inevitability of data-centric travel but also emphasize the need for transparent policies and safeguards. Balancing security demands with privacy concerns remains a critical challenge as these technologies evolve.

The Choice for Travelers

For travelers, the trade-off between convenience and the protection of personal information grows increasingly complex with every technological advance. As governments and companies push forward with data-driven solutions, the debate over privacy and transparency will only intensify, shaping the future of travel for years to come.

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User Security
Data Privacy Mobile Security Threat Landscape User Security

Turn Your Phone Off Daily for Five Minutes to Prevent Hacking

 

There are numerous ways in which critical data on your phone can be compromised. These range from subscription-based apps that covertly transmit private user data to social media platforms like Facebook, to fraudulent accounts that trick your friends into investing in fake cryptocurrency schemes. This issue goes beyond being a mere nuisance; it represents a significant threat to individual privacy, democratic processes, and global human rights.

Experts and advocates have called for stricter regulations and safeguards to address the growing risks posed by spyware and data exploitation. However, the implementation of such measures often lags behind the rapid pace of technological advancements. This delay leaves a critical gap in protections, exacerbating the risks for individuals and organizations alike.

Ronan Farrow, a Pulitzer Prize-winning investigative journalist, offers a surprisingly simple yet effective tip for reducing the chances of phone hacking: turn your phone off more frequently. During an appearance on The Daily Show to discuss his new documentary, Surveilled, Farrow highlighted the pressing need for more robust government regulations to curb spyware technology. He warned that unchecked use of such technology could push societies toward an "Orwellian surveillance state," affecting everyone who uses digital devices, not just political activists or dissidents.

Farrow explained that rebooting your phone daily can disrupt many forms of modern spyware, as these tools often lose their hold during a restart. This simple act not only safeguards privacy but also prevents apps from tracking user activity or gathering sensitive data. Even for individuals who are not high-profile targets, such as journalists or political figures, this practice adds a layer of protection against cyber threats. It also makes it more challenging for hackers to infiltrate devices and steal information.

Beyond cybersecurity, rebooting your phone regularly has additional benefits. It can help optimize device performance by clearing temporary files and resolving minor glitches. This maintenance step ensures smoother operation and prolongs the lifespan of your device. Essentially, the tried-and-true advice to "turn it off and on again" remains a relevant and practical solution for both privacy protection and device health.

Spyware and other forms of cyber threats pose a growing challenge in today’s interconnected world. From Pegasus-like software that targets high-profile individuals to less sophisticated malware that exploits everyday users, the spectrum of risks is wide and pervasive. Governments and technology companies are increasingly being pressured to develop and enforce regulations that prioritize user security. However, until such measures are in place, individuals can take proactive steps like regular phone reboots, minimizing app permissions, and avoiding suspicious downloads to reduce their vulnerability.

Ultimately, as technology continues to evolve, so too must our awareness and protective measures. While systemic changes are necessary to address the larger issues, small habits like rebooting your phone can offer immediate, tangible benefits. In the face of sophisticated cyber threats, a simple daily restart serves as a reminder that sometimes the most basic solutions are the most effective.

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Technology
AI Ecosystem AI Models AI technology AI Tool Computing Data Privacy Data Sets DeFi privacy protection secure computing Technology

The Role of Confidential Computing in AI and Web3

 

 
The rise of artificial intelligence (AI) has amplified the demand for privacy-focused computing technologies, ushering in a transformative era for confidential computing. At the forefront of this movement is the integration of these technologies within the AI and Web3 ecosystems, where maintaining privacy while enabling innovation has become a pressing challenge. A major event in this sphere, the DeCC x Shielding Summit in Bangkok, brought together more than 60 experts to discuss the future of confidential computing.

Pioneering Confidential Computing in Web3

Lisa Loud, Executive Director of the Secret Network Foundation, emphasized in her keynote that Secret Network has been pioneering confidential computing in Web3 since its launch in 2020. According to Loud, the focus now is to mainstream this technology alongside blockchain and decentralized AI, addressing concerns with centralized AI systems and ensuring data privacy.

Yannik Schrade, CEO of Arcium, highlighted the growing necessity for decentralized confidential computing, calling it the “missing link” for distributed systems. He stressed that as AI models play an increasingly central role in decision-making, conducting computations in encrypted environments is no longer optional but essential.

Schrade also noted the potential of confidential computing in improving applications like decentralized finance (DeFi) by integrating robust privacy measures while maintaining accessibility for end users. However, achieving a balance between privacy and scalability remains a significant hurdle. Schrade pointed out that privacy safeguards often compromise user experience, which can hinder broader adoption. He emphasized that for confidential computing to succeed, it must be seamlessly integrated so users remain unaware they are engaging with such technologies.

Shahaf Bar-Geffen, CEO of COTI, underscored the role of federated learning in training AI models on decentralized datasets without exposing raw data. This approach is particularly valuable in sensitive sectors like healthcare and finance, where confidentiality and compliance are critical.

Innovations in Privacy and Scalability

Henry de Valence, founder of Penumbra Labs, discussed the importance of aligning cryptographic systems with user expectations. Drawing parallels with secure messaging apps like Signal, he emphasized that cryptography should function invisibly, enabling users to interact with systems without technical expertise. De Valence stressed that privacy-first infrastructure is vital as AI’s capabilities to analyze and exploit data grow more advanced.

Other leaders in the field, such as Martin Leclerc of iEXEC, highlighted the complexity of achieving privacy, usability, and regulatory compliance. Innovative approaches like zero-knowledge proof technology, as demonstrated by Lasha Antadze of Rarimo, offer promising solutions. Antadze explained how this technology enables users to prove eligibility for actions like voting or purchasing age-restricted goods without exposing personal data, making blockchain interactions more accessible.

Dominik Schmidt, co-founder of Polygon Miden, reflected on lessons from legacy systems like Ethereum to address challenges in privacy and scalability. By leveraging zero-knowledge proofs and collaborating with decentralized storage providers, his team aims to enhance both developer and user experiences.

As confidential computing evolves, it is clear that privacy and usability must go hand in hand to address the needs of an increasingly data-driven world. Through innovation and collaboration, these technologies are set to redefine how privacy is maintained in AI and Web3 applications.

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Technology
AI Model Artificial Intelligence Data Privacy Facial Recognition Technology

Meet Chameleon: An AI-Powered Privacy Solution for Face Recognition

 


An artificial intelligence (AI) system developed by a team of researchers can safeguard users from malicious actors' unauthorized facial scanning. The AI model, dubbed Chameleon, employs a unique masking approach to create a mask that conceals faces in images while maintaining the visual quality of the protected image.

Furthermore, the researchers state that the model is resource-optimized, meaning it can be used even with low computing power. While the Chameleon AI model has not been made public yet, the team has claimed they intend to release it very soon.

Researchers at Georgia Tech University described the AI model in a report published in the online pre-print journal arXiv. The tool can add an invisible mask to faces in an image, making them unrecognizable to facial recognition algorithms. This allows users to secure their identities from criminal actors and AI data-scraping bots attempting to scan their faces.

“Privacy-preserving data sharing and analytics like Chameleon will help to advance governance and responsible adoption of AI technology and stimulate responsible science and innovation,” stated Ling Liu, professor of data and intelligence-powered computing at Georgia Tech's School of Computer Science and the lead author of the research paper.

Chameleon employs a unique masking approach known as Customized Privacy Protection (P-3) Mask. Once the mask is applied, the photos cannot be recognized by facial recognition software since the scans depict them "as being someone else."

While face-masking technologies have been available previously, the Chameleon AI model innovates in two key areas:

  1. Resource Optimization:
    Instead of creating individual masks for each photo, the tool develops one mask per user based on a few user-submitted facial images. This approach significantly reduces the computing power required to generate the undetectable mask.
  2. Image Quality Preservation:
    Preserving the image quality of protected photos proved challenging. To address this, the researchers employed Chameleon's Perceptibility Optimization technique. This technique allows the mask to be rendered automatically, without requiring any manual input or parameter adjustments, ensuring the image quality remains intact.

The researchers announced their plans to make Chameleon's code publicly available on GitHub soon, calling it a significant breakthrough in privacy protection. Once released, developers will be able to integrate the open-source AI model into various applications.

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User Security
Data Breach Data Leak Data Privacy Data Theft National Public Data User Security

Over 600,000 People Impacted In a Major Data Leak

 

Over 600,000 persons were impacted by a data leak that took place at another background check company. Compared to the 2.9 billion persons impacted by the National Public Data theft, this is a minor breach, but it's still concerning. SL Data Services, the company in question, was discovered online. It was neither encrypted or password-protected and was available to the public.

Jeremiah Fowler, a cybersecurity researcher, uncovered the breach (or lack of protection on the files). Full names, residences, email addresses, employment data, social media accounts, phone numbers, court records, property ownership data, car records, and criminal records were all leaked.

Everything was stored in PDF files, the majority of which were labelled "background check." The database had a total of 713.1GB of files. Fortunately, the content is no longer publicly available, however it took some time to be properly secured. After receiving the responsible disclosure warning, SL Data Services took a week to make it unavailable. 

A week is a long time to have 600,000 people's information stored in publicly accessible files. Unfortunately, those with data in the breach might not even know their information was included. Since background checks are typically handled by someone else, and the person being checked rarely knows whose background check company was utilised, this might become even more complicated. 

While social security numbers and financial details are not included in the incident, because so much information about the people affected is publicly available, scammers can use it to deceive unsuspecting victims using social engineering.

Thankfully, there is no evidence that malicious actors accessed the open database or obtained sensitive information, but there is no certainty that they did not. Only time will tell—if we observe an increase in abrupt social engineering attacks, we know something has happened.
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