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Transforming Data Security with Large Language Models (LLMs): Sentra’s Innovative Approach

September 12, 2023
5
 Min Read
AI and ML

In today's data-driven world, the success of any data security program hinges on the accuracy, speed, and scalability of its data classification efforts. Why? Because not all data is created equal, and precise data classification lays the essential groundwork for security professionals to understand the context of data-related risks and vulnerabilities. Armed with this knowledge, security operations (SecOps) teams can remediate in a targeted, effective, and prioritized manner, with the ultimate aim of proactively reducing an organization's data attack surface and risk profile over time.

Sentra is excited to introduce Large Language Models (LLMs) into its classification engine. This development empowers enterprises to proactively reduce the data attack surface while accurately identifying and understanding sensitive unstructured data such as employee contracts, source code, and user-generated content at scale.

Many enterprises today grapple with a multitude of data regulations and privacy frameworks while navigating the intricate world of cloud data. Sentra's announcement of adding LLMs to its classification engine is redefining how enterprise security teams understand, manage, and secure their sensitive and proprietary data on a massive scale. Moreover, as enterprises eagerly embrace AI's potential, they must also address unauthorized access or manipulation of Language Model Models (LLMs) and remain vigilant in detecting and responding to security risks associated with AI model training. Sentra is well-equipped to guide enterprises through this multifaceted journey.

A New Era of Data Classification 

Identifying and managing unstructured data has always been a headache for organizations,  whether it's legal documents buried in email attachments, confidential source code scattered across various folders, or user-generated content strewn across collaboration platforms. Imagine a scenario where an enterprise needs to identify all instances of employee contracts within its vast data repositories. Previously, this would have involved painstaking manual searches, leading to inefficiency, potential oversight, and increased security risks.

Sentra’s LMM-powered classification engine can now comprehend the context, sentiment, and nuances of unstructured data, enabling it to classify such data with a level of accuracy and granularity that was previously unimaginable. The model can analyze the content of documents, emails, and other unstructured data sources, not only identifying employee contracts but also providing valuable insights into their context. It can understand contract clauses, expiration dates, and even flag potential compliance issues.

Similarly, for source code scattered across diverse folders, Sentra can recognize programming languages, identify proprietary code, and ensure that sensitive code is adequately protected.

When it comes to user-generated content on collaboration platforms, Sentra can analyze and categorize this data, making it easier for organizations to monitor and manage user interactions, ensuring compliance with their policies and regulations.

This new classification approach not only aids in understanding the business context of unstructured customer data but also aligns seamlessly with compliance standards such as GDPR, CCPA, and HIPAA. Ensuring the highest level of security, Sentra exclusively scans data with LLM-based classifiers within the enterprise's cloud premises. The assurance that the data never leaves the organization’s environment reduces an additional layer of risk.

Quantifying Risk: Prioritized Data Risk Scores 

Automated data classification capabilities provide a solid foundation for data security management practices. What’s more, data classification speed and accuracy are paramount when striving for an in-depth comprehension of sensitive data and quantifying risk. 

Sentra offers data risk scoring that considers multiple layers of data, including sensitivity scores, access permissions, user activity, data movement, and misconfigurations. This unique technology automatically scores the most critical data risks, providing security teams and executives with a clear, prioritized view of all their sensitive data at-risk, with the option to drill down deeply into the root cause of the vulnerability (often at a code level). 

Having a clear, prioritized view of high-risk data at your fingertips empowers security teams to truly understand, quantify, and prioritize data risks while directing targeted remediation efforts.

The Power of Accuracy and Efficiency

One of the most significant advantages of Sentra's LLM-powered data classification is the unprecedented accuracy it brings to the table. Inaccurate or incomplete data classification can lead to costly consequences, including data breaches, regulatory fines, and reputational damage. With LLMs, Sentra ensures that your data is classified with  precision, reducing the risk of errors and omissions.

Moreover, this enhanced accuracy translates into increased efficiency. Sentra's LLM engine can process vast volumes of data in a fraction of the time it would take a human workforce. This not only saves valuable resources but also enables organizations to proactively address security and compliance challenges.

Key developments of Sentra's classification engine encompass:

  • Automatic classification of proprietary customer data with additional context to comply with regulations and privacy frameworks.
  • LLM-powered scanning of data asset content and analysis of metadata, including file names, schemas, and tags.
  • The capability for enterprises to train their LLMs and seamlessly integrate them into Sentra's classification engine for improved proprietary data classification.

We are excited about the possibilities that this advancement will unlock for our customers as we continue to innovate and redefine cloud data security.

Ron has more than 20 years of tech hands-on and leadership experience, focusing on cybersecurity, cloud, big data, and machine learning. Following his military experience, Ron built a company that was sold to Oracle. He became a serial entrepreneur and a seed investor in several cybersecurity startups, including Axonius, Firefly, Guardio, Talon Cyber Security, and Lightricks.

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Karin Zano
Karin Zano
October 1, 2024
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Data Security

5 Cybersecurity Tips for Cybersecurity Awareness Month

5 Cybersecurity Tips for Cybersecurity Awareness Month

Secure our World: Cybersecurity Awareness Month 2024

As we kick off October's Cybersecurity Awareness Month and think about this year’s theme, “Secure Our World,” it’s important to remember that safeguarding our digital lives doesn't have to be complex. Simple, proactive steps can make a world of difference in protecting yourself and your business from online threats. In many cases, these simple steps relate to data — the sensitive information about users’ personal and professional lives. As a business, you are largely responsible for keeping your customers' and employees’ data safe. Starting with cybersecurity is the best way to ensure that this valuable information stays secure, no matter where it’s stored or how you use it.

Keeping Personal Identifiable Information (PII) Safe

Data security threats are more pervasive than ever today, with cybercriminals constantly evolving their tactics to exploit vulnerabilities. From phishing attacks to ransomware, the risks are not just technical but also deeply personal — especially when it comes to protecting Personal Identifiable Information (PII).

Cybersecurity Awareness Month is a perfect time to reflect on the importance of strong data security. Businesses, in particular, can contribute to a safer digital environment through Data Security Posture Management (DSPM). DSPM helps businesses - big and small alike -  monitor, assess, and improve their security posture, ensuring that sensitive data, such as PII, remains protected against breaches. By implementing DSPM, businesses can identify weak spots in their data security and take action before an incident occurs, reinforcing the idea that securing our world starts with securing our data.

Let's take this month as an opportunity to Secure Our World by embracing these simple but powerful DSPM measures to protect what matters most: data.

5 Cybersecurity Tips for Businesses

  1. Discover and Classify Your Data: Understand where all of your data resides, how it’s used, and its levels of sensitivity and protection. By leveraging discovery and classification, you can maintain complete visibility and control over your business’s data, reducing the risks associated with shadow data (unmanaged or abandoned data).
  2. Ensure data always has a good risk posture: Maintain a strong security stance by ensuring your data always has a good posture through Data Security Posture Management (DSPM). DSPM continuously monitors and strengthens your data’s security posture (readiness to tackle potential cybersecurity threats), helping to prevent breaches and protect sensitive information from evolving threats.
  3. Protect Private and Sensitive Data: Keep your private and sensitive data secure, even from internal users. By implementing Data Access Governance (DAG) and utilizing techniques like data de-identification and masking, you can protect critical information and minimize the risk of unauthorized access.
  4. Embrace Least-Privilege Control: Control data access through the principle of least privilege — only granting access to the users and systems who need it to perform their jobs. By implementing Data Access Governance (DAG), you can limit access to only what is necessary, reducing the potential for misuse and enhancing overall data security.
  5. Continual Threat Monitoring for Data Protection: To protect your data in real-time, implement continual monitoring of new threats. With Data Detection and Response (DDR), you can stay ahead of emerging risks, quickly identifying and neutralizing potential vulnerabilities to safeguard your sensitive information.

How Sentra Helps Secure Your Business’s World

Today, a business's “world” is extremely complex and ever-changing. Users can easily move, change, or copy data and connect new applications/environments to your ecosystem. These factors make it challenging to pinpoint where your data resides and who has access to it at any given moment. 

Sentra helps by giving businesses a vantage point of their entire data estate, including multi-cloud and on-premises environments. We combine all of the above practices—granular discovery and classification, end-to-end data security posture management, data access governance, and continuous data detection and response into a single platform. To celebrate Cybersecurity Awareness Day, check out how our data security platform can help improve your security posture.

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David Stuart
David Stuart
September 25, 2024
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Top Advantages and Benefits of DSPM

Top Advantages and Benefits of DSPM

Addressing data protection in today’s data estates requires innovative solutions. Data in modern environments moves quickly, as countless employees in a given organization can copy, move, or modify sensitive data within seconds. In addition, many organizations operate across a variety of on premises environments, along with multiple cloud service providers and technologies like PaaS and IaaS. Data quickly sprawls across this multifaceted estate as team members perform daily tasks. 

Data Security Posture Management (DSPM) is a key technology that meets these challenges by discovering and classifying sensitive data and then protecting it wherever it goes. DSPM helps organizations mitigate risks and maintain compliance across a complex data landscape by focusing on the continuous discovery and monitoring of sensitive information. 

If you're not familiar with DSPM, you can check out our comprehensive DSPM guide to get up to speed. But for now, let's delve into why DSPM is becoming indispensable for modern cloud enterprises.

Why is DSPM Important?

DSPM is an innovative cybersecurity approach designed to safeguard and monitor sensitive data as it traverses different environments. This technology focuses on the discovery of sensitive data across the entire data estate, including cloud platforms such as SaaS, IaaS, and PaaS, as well as on-premises systems. DSPM assesses exposure risks, identifies who has access to company data, classifies how data is used, ensures compliance with regulatory requirements like GDPR, PCI-DSS, and HIPAA, and continuously monitors data for emerging threats.

As organizations scale up their data estate and add multiple cloud environments, on-prem databases, and third-party SaaS applications, DSPM also helps them automate key data security practices and keep pace with this rapid scaling. For instance, DSPM offers automated data tags that help businesses better understand the deeper context behind their most valuable assets — regardless of location within the data estate. It leverages integrations with other security tools (DLP, CNAPP, etc.) to collect this valuable data context, allowing teams to confidently remediate the security issues that matter most to the business.

What are the Benefits of DSPM?

DSPM empowers all security stakeholders to monitor data flow, access, and security status, preventing risks associated with data duplication or movement in various cloud environments. It simplifies robust data protection, making it a vital asset for modern cloud-based data management.

Now, you might be wondering, why do we need another acronym? 

Let's explore the top five benefits of implementing DSPM:

1) Sharpen Visibility When Identifying Data Risk

DSPM enables you to continuously analyze your security posture and automate risk assessment across your entire landscape. It can detect data concerns across all cloud-native and unmanaged databases, data warehouses, data lakes, data pipelines, and metadata catalogs. By automatically discovering and classifying sensitive data, DSPM helps teams prioritize actions based on each asset’s sensitivity and relationship to policy guidelines.

Automating the data discovery and classification process takes a fraction of the time and effort it would take to manually catalog all sensitive data. It’s also far more accurate, especially when using a DSPM solution that leverages LLMs to classify data with more granularity and rich meta-data. In addition, it ensures that you stay up-to-date with the frequent changes in your modern data landscape.

2) Strengthen Adherence with Security & Compliance Requirements 

DSPM can also automate the process of identifying regulatory violations and ensuring adherence to custom and pre-built policies (including policies that map to common compliance frameworks). By contrast, manually implementing policies is prone to errors and inaccuracies. It’s common for teams to misconfigure policies that either overalert and inhibit daily work or miss significant user activities and changes to access permissions.

Instead, DSPM offers policies that travel with your data and automatically reveal compliance gaps. It ensures that sensitive data stays within the correct environments and doesn’t travel to regions with retention policies or without data encryption.

3) Improve Data Access Governance

Many DSPM solutions also offer data access governance (DAG). This functionality enforces the appropriate access permissions for all user identities, third parties, and applications within your organization. DAG automatically ensures that the proper controls follow your data, mitigating risks such as excessive permission, unauthorized access, inactive or unused identities and API keys, and improper provisioning/deprovisioning for services and users.

By using DSPM to govern data access, teams can successfully achieve the least privilege within an ever-changing and growing data ecosystem. 


4) Minimize your Data Attack Surface

DSPM also enables teams to detect unmanaged sensitive data, including mislocated, shadow, or duplicate assets. Its powerful data detection capabilities ensure that sensitive data, such as historical assets stored within legacy apps, development test data, or information within shadow IT apps, don’t go unnoticed in a lower environment. By automatically finding and classifying these unknown assets, DSPM minimizes your data attack surface, controls data sprawl, and better protects your most valuable assets from breaches and leaks.


5) Protect Data Used by LLMs

DSPM also extends to LLM applications, enabling you to maintain a strong risk posture as your team adopts new technologies. It considers LLMs as part of the data attack surface, applying the same DAG and data discovery/classification capabilities to any training data leveraged within these applications. 

By including LLMs in your overarching data security approach, DSPM alleviates any GenAI data privacy concerns and sets up your organization for future success as these technologies continue to evolve.

Enhance Your DSPM Strategy with Sentra

Sentra offers an AI-powered DSPM platform that moves at the speed of data, enabling you to strengthen your data risk posture across your entire hybrid ecosystem. Our platform can identify and mitigate data risks and threats with deep context, map identities to permissions, prevent exfiltration with a modern DLP, and maintain a rich data catalog with details on both known and unknown data. 

In addition, our platform runs autonomously and only requires minimal administrative support. It also adds a layer of security by discovering and intelligently categorizing all data with removing it from your environment. 

Conclusion

DSPM is quickly becoming an essential tool for modern cloud enterprises, offering comprehensive benefits to the complex challenges of data protection. By focusing on discovering and monitoring sensitive information, DSPM helps organizations mitigate risks and maintain compliance across various environments, including cloud and on-premises systems.

The rise of DSPM in the past few years highlights its importance in enhancing security. It allows security teams to monitor data flow, access, and status, effectively preventing data duplication or movement risks. With advanced threat detection, improved compliance and governance, detailed access control, rapid incident response, and seamless integration with cloud services, DSPM provides significant benefits and advantages over other data security solutions. Implementing DSPM is a strategic move for organizations aiming to fortify their data protection strategies in today's digital landscape.

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Meni Besso
Meni Besso
September 16, 2024
4
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Compliance

GDPR Compliance Failures Lead to Surge in Fines

GDPR Compliance Failures Lead to Surge in Fines

In recent years, the landscape of data privacy and protection has become increasingly stringent, with regulators around the world cracking down on companies that fail to comply with local and international standards. 

The latest high-profile case involves Uber, which was recently fined a staggering €290 million ($324 million) by the Dutch Data Protection Authority (DPA) for violations related to the General Data Protection Regulation (GDPR). This is a wake up call for multinational companies. 

Graph showing the rise of GDPR fines from 2018-2024

What is GDPR?

The General Data Protection Regulation (GDPR) is a data protection law that came into effect in the EU in May 2018. Its goal is to give individuals more control over their personal data and unify data protection rules across the EU.

GDPR gives extra protection to special categories of sensitive data. Both 'controllers' (who decide how data is processed) and 'processors' (who act on their behalf) must comply. Joint controllers may share responsibility when multiple entities manage data.

Who Does the GDPR Apply To?

GDPR applies to both EU-based and non-EU organizations that handle the data of EU residents. The regulation requires organizations to get clear consent for data collection and processing, and it gives individuals rights to access, correct, and delete their data. Organizations must also ensure strong data security and report any data breaches promptly.

What Are the Penalties for Non-Compliance with GDPR?

Non-compliance with the General Data Protection Regulation (GDPR) can result in substantial penalties.

Article 83 of the GDPR establishes the fine framework, which includes the following:

Maximum Fine: The maximum fine for GDPR non-compliance can reach up to 20 million euros, or 4% of the company’s total global turnover from the preceding fiscal year, whichever is higher.

Alternative Penalty: In certain cases, the fine may be set at 10 million euros or 2% of the annual global revenue, as outlined in Article 83(4).

Additionally, individual EU member states have the authority to impose their own penalties for breaches not specifically addressed by Article 83, as permitted by the GDPR’s flexibility clause.

So far, the maximum fine given under GDPR was to Meta in 2023, which was fined $1.3 billion for violating GDPR laws related to data transfers. We’ll delve into the details of that case shortly.

Can Individuals Be Fined for GDPR Breaches?

While fines are typically imposed on organizations, individuals can be fined under certain circumstances. For example, if a person is self-employed and processes personal data as part of their business activities, they could be held responsible for a GDPR breach. However, UK-GDPR and EU-GDPR do not apply to data processing carried out by individuals for personal or household activities. 

According to GDPR Chapter 1, Article 4, “any natural or legal person, public authority, agency, or body” can be held accountable for non-compliance. This means that GDPR regulations do not distinguish significantly between individuals and corporations when it comes to breaches.

Specific scenarios where individuals within organizations may be fined include:

  • Obstructing a GDPR compliance investigation.
  • Providing false information to the ICO or DPA.
  • Destroying or falsifying evidence or information.
  • Obstructing official warrants related to GDPR or privacy laws.
  • Unlawfully obtaining personal data without the data controller's permission.

The Top 3 GDPR Fines and Their Impact

1.  Meta - €1.2 Billion ($1.3 Billion), 2023 

In May 2023, Meta, the U.S. tech giant, was hit with a staggering $1.3 billion fine by an Irish court for violating GDPR regulations concerning data transfers between the E.U. and the U.S. This massive penalty came after the E.U.-U.S. Privacy Shield Framework, which previously provided legal cover for such transfers, was invalidated in 2020. The court found that the framework failed to offer sufficient protection for EU citizens against government surveillance. This fine now stands as the largest ever under GDPR, surpassing Amazon’s 2021 record.

2. Amazon - €746 million ($781 million), 2021

Which leads us to Amazon at number 2, not bad. In 2021, Amazon Europe received the second-largest GDPR fine to date from Luxembourg’s National Commission for Data Protection (CNPD). The fine was imposed after it was determined that the online retailer was storing advertisement cookies without obtaining proper consent from its users.

3. Instagram - €405 million ($427 million), 2022

The Irish Data Protection Commission (DPC) fined Instagram for violating children’s privacy online in September 2022. The violations included the public exposure of kids' phone numbers and email addresses. The DPC found that Instagram’s user registration system could default child users' accounts to "public" instead of "private," contradicting GDPR’s privacy by design principles and the regulations aimed at safeguarding children's information.

Uber currently ranks at number 6 with the latest €290 million fine they received from the Dutch Data Protection Authority (DPA) for the GDPR related violations.

Uber’s GDPR Violation

The Dutch DPA accused Uber of transferring sensitive data of European drivers to the United States without implementing appropriate safeguards. This included personal information such as account details, location data, payment information, and even sensitive documents like taxi licenses, criminal records, and medical data. The failure to protect this data adequately, especially after the invalidation of the E.U.-U.S. Privacy Shield in 2020, constituted a serious violation of GDPR.

Despite Uber's claim that its cross-border data transfer process was compliant with GDPR, the DPA's decision to impose the record fine underscores the growing importance of adhering to stringent data protection regulations. Uber has since ceased the practice, but the financial and reputational damage is already done.

The Implications for Global Companies

The growing frequency of such fines sends a clear message to global companies: compliance with data protection regulations is non-negotiable. As European regulators continue to enforce GDPR rigorously, companies that fail to implement adequate data protection measures risk facing severe financial penalties and reputational harm.

In the case of Uber, the company’s failure to use appropriate mechanisms for data transfers, such as Standard Contractual Clauses, led to significant repercussions. This situation emphasizes the importance of staying current with regulatory changes, such as the introduction of the E.U.-U.S. Data Privacy Framework, and ensuring that all data transfer practices are fully compliant.

How Sentra Helps Orgs Stay Compliant with GDPR

Sentra helps organizations maintain GDPR compliance by effectively tagging data belonging to European citizens.

When EU citizens' Personally Identifiable Information (PII) is moved or stored outside of EU data centers, Sentra will detect and alert you in near real-time. Our continuous monitoring and scanning capabilities ensure that any data violations are identified and flagged promptly.

Example of EU citizens PII stored outside of EU data centers

Unlike traditional methods where data replication can obscure visibility and lead to issues during audits, Sentra provides ongoing visibility into data storage. This proactive approach significantly reduces the risk by alerting you to potential compliance issues as they arise.

Sentra does automatic classification of localized data - specifically in this case, EU data. Below you can see an example of how we do this. 

Sentra's automatic classification of localized data

The Rise of Compliance Violations: A Wake-up Call

The increasing number of compliance violations and the related hefty fines should serve as a wake-up call for companies worldwide. As the regulatory environment becomes more complex, it is crucial for organizations to prioritize data protection and privacy. By doing so, they can avoid costly penalties and maintain the trust of their customers and stakeholders.

Solutions such as Sentra provide a cost-effective means to ensure sensitive data always has the right posture and security controls - no matter where the data travels - and can alert on exceptions that require rapid remediation. In this way, organizations can remain regulatory compliant, avoid the steep penalties for violations, and ensure the proper, secure use of data throughout their ecosystem. 

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