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New AI-Assistant, Sentra Jagger, Is a Game Changer for DSPM and DDR

March 5, 2024
3
 Min Read
AI and ML

Evolution of Large Language Models (LLMs)

In the early 2000s, as Google, Yahoo, and others gained widespread popularity. Users found the search engine to be a convenient tool, effortlessly bringing a wealth of information to their fingertips. Fast forward to the 2020s, and we see Large Language Models (LLMs) are pushing productivity to the next level. LLMs skip the stage of learning, seamlessly bridging the gap between technology and the user.

LLMs create a natural interface between the user and the platform. By interpreting natural language queries, they effortlessly translate human requests into software actions and technical operations. This simplifies technology to make it close to invisible. Users no longer need to understand the technology itself, or how to get certain data — they can just input any query, and LLMs will simplify it.

Revolutionizing Cloud Data Security With Sentra Jagger

Sentra Jagger is an industry-first AI assistant for cloud data security based on the Large Language Model (LLM).

It enables users to quickly analyze and respond to security threats, cutting task times by up to 80% by answering data security questions, including policy customization and enforcement, customizing settings, creating new data classifiers, and reports for compliance. By reducing the time for investigating and addressing security threats, Sentra Jagger enhances operational efficiency and reinforces security measures.

Empowering security teams, users can access insights and recommendations on specific security actions using an interactive, user-friendly interface. Customizable dashboards, tailored to user roles and preferences, enhance visibility into an organization's data. Users can directly inquire about findings, eliminating the need to navigate through complicated portals or ancillary information.

Benefits of Sentra Jagger

  1. Accessible Security Insights: Simplified interpretation of complex security queries, offering clear and concise explanations in plain language to empower users across different levels of expertise. This helps users make informed decisions swiftly, and confidently take appropriate actions.
  1. Enhanced Incident Response: Clear steps to identify and fix issues, offering users clear steps to identify and fix issues, making the process faster and minimizing downtime, damage, and restoring normal operations promptly. 
  1. Unified Security Management: Integration with existing tools, creating a unified security management experience and providing a complete view of the organization's data security posture. Jagger also speeds solution customization and tuning.

Why Sentra Jagger Is Changing the Game for DSPM and DDR

Sentra Jagger is an essential tool for simplifying the complexities of both Data Security Posture Management (DSPM) and Data Detection and Response (DDR) functions. DSPM discovers and accurately classifies your sensitive data anywhere in the cloud environment, understands who can access this data, and continuously assesses its vulnerability to security threats and risk of regulatory non-compliance. DDR focuses on swiftly identifying and responding to security incidents and emerging threats, ensuring that the organization’s data remains secure. With their ability to interpret natural language, LLMs, such as Sentra Jagger, serve as transformative agents in bridging the comprehension gap between cybersecurity professionals and the intricate worlds of DSPM and DDR.

Data Security Posture Management (DSPM)

When it comes to data security posture management (DSPM), Sentra Jagger empowers users to articulate security-related queries in plain language, seeking insights into cybersecurity strategies, vulnerability assessments, and proactive threat management.

Meet Sentra Jagger, your new data security assistant

The language models not only comprehend the linguistic nuances but also translate these queries into actionable insights, making data security more accessible to a broader audience. This democratization of security knowledge is a pivotal step forward, enabling organizations to empower diverse teams (including privacy, governance, and compliance roles) to actively engage in bolstering their data security posture without requiring specialized cybersecurity training.

Data Detection and Response (DDR)

In the realm of data detection and response (DDR), Sentra Jagger contributes to breaking down technical barriers by allowing users to interact with the platform to seek information on DDR configurations, real-time threat detection, and response strategies. Our AI-powered assistant transforms DDR-related technical discussions into accessible conversations, empowering users to understand and implement effective threat protection measures without grappling with the intricacies of data detection and response technologies.

The integration of LLMs into the realms of DSPM and DDR marks a paradigm shift in how users will interact with and comprehend complex cybersecurity concepts. Their role as facilitators of knowledge dissemination removes traditional barriers, fostering widespread engagement with advanced security practices. 

Sentra Jagger is a game changer by making advanced technological knowledge more inclusive, allowing organizations and individuals to fortify their cybersecurity practices with unprecedented ease. It helps security teams better communicate with and integrate within the rest of the business. As AI-powered assistants continue to evolve, so will their impact to reshape the accessibility and comprehension of intricate technological domains.

How CISOs Can Leverage Sentra Jagger 

Consider a Chief Information Security Officer (CISO) in charge of cybersecurity at a healthcare company. To assess the security policies governing sensitive data in their environment, the CISO leverages Sentra’s Jagger AI assistant.. If the CISO, let's call her Sara, needs to navigate through the Sentra policy page, instead of manually navigating, Sara can simply queryJagger, asking, "What policies are defined in my environment?" In response, Jagger provides a comprehensive list of policies, including their names, descriptions, active issues, creation dates, and status (enabled or disabled).

Sara can then add a custom policy related to GDPR, by simply describing it. For example, "add a policy that tracks European customer information moving outside of Europe". Sentra Jagger will translate the request using Natural Language Processing (NLP) into a Sentra policy and inform Sara about potential non-compliant data movement based on the recently added policy.

Upon thorough review, Sara identifies a need for a new policy: "Create a policy that monitors instances where credit card information is discovered in a datastore without audit logs enabled." Sentra Jagger initiates the process of adding this policy by prompting Sara for additional details and confirmation. 

The LLM-assistant, Sentra Jagger, communicates, "Hi Sara, it seems like a valuable policy to add. Credit card information should never be stored in a datastore without audit logs enabled. To ensure the policy aligns with your requirements, I need more information. Can you specify the severity of alerts you want to raise and any compliance standards associated with this policy?" Sara responds, stating, "I want alerts to be raised as high severity, and I want the AWS CIS benchmark to be associated with it."

Having captured all the necessary information, Sentra Jagger compiles a summary of the proposed policy and sends it to Sara for her review and confirmation. After Sara confirms the details, the LLM-assistant, Sentra Jagger seamlessly incorporates the new policy into the system. This streamlined interaction with LLMs enhances the efficiency of policy management for CISOs, enabling them to easily navigate, customize, and implement security measures in their organizations.

Create a policy with Sentra Jagger
Creating a policy with Sentra Jagger

Conclusion 

The advent of Large Language Models (LLMs) has changed the way we interact with and understand technology. Building on the legacy of search engines, LLMs eliminate the learning curve, seamlessly translating natural language queries into software and technical actions. This innovation removes friction between users and technology, making intricate systems nearly invisible to the end user.

For Chief Information Security Officers (CISOs) and ITSecOps, LLMs offer a game-changing approach to cybersecurity. By interpreting natural language queries, Sentra Jagger bridges the comprehension gap between cybersecurity professionals and the intricate worlds of DSPM and DDR. This standardization of security knowledge allows organizations to empower a wider audience to actively engage in bolstering their data security posture and responding to security incidents, revolutionizing the cybersecurity landscape.

To learn more about Sentra, schedule a demo with one of our experts.

Discover Ron’s expertise, shaped by over 20 years of hands-on tech and leadership experience in cybersecurity, cloud, big data, and machine learning. As a serial entrepreneur and seed investor, Ron has contributed to the success of several startups, including Axonius, Firefly, Guardio, Talon Cyber Security, and Lightricks, after founding a company acquired by Oracle.

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But among the many privacy requirements, Data Subject Access Requests (DSARs) can be the most complex to support. DSARs give individuals the right to request access to the personal data that an organization holds about them—often with a firm deadline of just 30 days to respond. For large enterprises with data scattered across multiple systems, both in the cloud and on-premises, even a single request can trigger a chaotic search across different platforms, manual reviews and legal oversight—it quickly becomes a race against the clock, with compliance, trust, and reputation on the line.

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Data Discovery & Inventory
For large organizations, pinpointing where personal data resides across a diverse ecosystem of information systems, including databases, SaaS applications, data lakes, and legacy environments, is a complex challenge. The presence of fragmented IT infrastructure and third-party platforms often leads to limited visibility, which not only slows down the DSAR response process but also increases the likelihood of missing or overlooking critical personal data.

Linking Identities Across Systems
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Unstructured Data Handling
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Volume & Scalability
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Sentra is a modern data security platform dedicated to helping organizations gain complete visibility and control over their sensitive data. By continuously scanning and classifying data across all environments (including cloud, SaaS, and on-premises systems) Sentra maintains an always up-to-date data map, giving organizations a clear understanding of where sensitive data resides, how it flows, and who has access to it. This data map forms the foundation for efficient DSAR automation, enabling Sentra’s DSAR module to search for user identifiers only in locations where relevant data actually exists - ensuring high accuracy, completeness, and fast response times.

Data Security Platform example of US SSN finding

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Smart Search of Individual Data

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Leveraging its advanced classification and correlation capabilities, Sentra identifies all relevant records associated with the provided identifiers. Once the scan is complete, it compiles a comprehensive DSAR report that consolidates all discovered personal data linked to the data subject that can be downloaded as a PDF for manual review or securely retrieved via Sentra’s API.

DSAR Requests

Establishing a DSAR Processing Pipeline

Large organizations that receive a high volume of DSAR (Data Subject Access Request) submissions typically implement a robust, end-to-end DSAR processing pipeline. This pipeline is often initiated through a self-service privacy portal, allowing individuals to easily submit requests for access or deletion of their personal data. Once a request is received, an automated or semi-automated workflow is triggered to handle the request efficiently and in compliance with regulatory timelines.

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  2. Mapping Identifiers: Collect and map all known identifiers for the individual across systems (e.g., email, user ID, customer number).

  3. Environment-Wide Data Discovery (via Sentra): Use Sentra to search all relevant environments — cloud, SaaS, on-prem — for personal data tied to the individual. By using Sentra’s automated discovery and classification, Sentra can automatically identify where to search for.

  4. DSAR Report Generation (via Sentra): Compile a detailed report listing all personal data found and where it resides.

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  6. Final Response to Requester: Send a confirmation to the requester, outlining the actions taken and closing the request.

Sentra plays a key role in the DSAR pipeline by exposing a powerful API that enables automated, organization-wide searches for personal data. The search results can be programmatically used to trigger downstream actions like data deletion. After removal, the API can initiate a follow-up scan to verify that all data has been successfully deleted.

Benefits of DSAR Automation 

With privacy regulations constantly growing, and DSAR volumes continuing to rise, building an automated, scalable pipeline is no longer a luxury - it’s a necessity.


  • Automated and Cost-Efficient: Replaces costly, error-prone manual processes with a streamlined, automated approach.
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  • Seamless Integration: A powerful API allows integration with workflow systems, enabling a fully automated, end-to-end DSAR experience for end users.

By using Sentra to intelligently locate PII across all environments, organizations can eliminate manual bottlenecks and accelerate response times. Sentra’s powerful API and deep data awareness make it possible to automate every step of the DSAR journey - from discovery to deletion - enabling privacy teams to operate at scale, reduce costs, and maintain compliance with confidence. 

Turning DSAR Compliance into a Scalable Advantage

As privacy expectations grow and regulatory pressure intensifies, DSARs are no longer just a checkbox. They are a reflection of how seriously an organization takes user trust. Manual, reactive processes simply can’t keep up with the scale and complexity of modern data environments.

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Recently there has been a significant shift from standalone Data Security Posture Management (DSPM) solutions to comprehensive Data Security Platforms (DSPs). These platforms integrate DSPM functionality, but also encompass access governance, threat detection, and data loss prevention capabilities to provide a more holistic data protection solution. Additionally, the critical role of data in AI and LLM training requires holistic data security platforms that can manage data sensitivity, ensure security and compliance, and maintain data integrity.

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Below are outlined the must-have features for any DSP solution in the coming year:

  1. Cloud-Native Architecture

Modern DSPs are built for the cloud and address vast data scale with cloud-native technologies that leverage provider APIs and functions. This allows data discovery and classification to occur autonomously, within the customer cloud environment leveraging existing compute resources. Agentless approaches reduce administrative burdens as well.

  1. AI-Based Classification

AI has revolutionized data classification, providing context-aware accuracy exceeding 95%. By understanding data in its unique context, AI-driven DSP solutions ensure the right security measures are applied without overburdening teams with false positives.

  1. Anomaly Detection and Real-Time Threat Detection

Anomaly detection, powered by Data Detection and Response (DDR), identifies unusual patterns in data usage to spotlight risks such as ransomware and insider threats. Combined with real-time, data-aware detection of suspicious activities, modern DSP solutions proactively address cloud-native vulnerabilities, stopping breaches before they unfold and ensuring swift, effective action.

  1. Automatic Labeling

Manual tagging is too cumbersome and time consuming. When choosing DSP solutions, it’s critical to make sure that you choose ones that automate data tagging and labeling, seamlessly integrating with Data Loss Prevention (DLP), Secure Access Service Edge (SASE), and governance platforms. This reduces errors and accelerates compliance processes.

  1. Data Zones and Perimeters

As data moves across cloud environments, maintaining control is paramount. Leading DSP solutions monitor data movement, alerting teams when data crosses predefined perimeters or storage zones, ensuring compliance with internal and external policies.

  1. Automatic Remediation and Enforcement

Automation extends to remediation, with DSPs swiftly addressing data risks like excessive permissions or misconfigurations. By enforcing protection policies across cloud environments, organizations can prevent breaches before they occur.

The Business Case for DSP in 2025

Proactive Security

Cloud-native DSP represents a shift from reactive to proactive security practices. By identifying and addressing risks early, and across their entire data estate from cloud to on-premises, organizations can mitigate potential threats and strengthen their security posture.

Regulatory Compliance

As regulations such as GDPR and CCPA continue to evolve, DSPM solutions play a crucial role in simplifying compliance by automating data discovery and labeling. This automation reduces the manual effort required to meet regulatory requirements. In fact, 84% of security and IT professionals consider data protection frameworks like GDPR and CCPA to be mandatory for their industries, emphasizing the growing need for automated solutions to ensure compliance.

The Rise of Gen AI

The rise of Gen AI is expected to be a main theme in 2025. Gen AI is a driver for data proliferation in the cloud and for a transition between legacy data technologies and modern ones that require an updated data security program.

Operational Efficiency

By automating repetitive tasks, DSPM significantly reduces the workload for security teams. This efficiency allows teams to focus on strategic initiatives rather than firefighting. According to a 2024 survey, organizations using DSPM reported a 40% reduction in time spent on manual data management tasks, demonstrating its impact on operational productivity.

Future-Proofing Your Organization with Cloud-Native DSP

To thrive in the evolving security landscape, organizations must adopt forward-looking strategies. Cloud-native DSP tools integrate seamlessly with broader security frameworks, ensuring resilience and adaptability. As technology advances, features like predictive analytics and deeper AI integration will further enhance capabilities.

Conclusion

Data security challenges are only becoming more complex, but new Data Security Platforms (DSPs) provide the tools to meet them head-on. Now is the time for organizations to take a hard look at their security posture and consider how DSPs can help them stay protected, compliant, and trusted. DSPs are quickly becoming essential to business operations, influencing strategic decisions and enabling faster, more secure innovation.

Ready to see it in action?

Request a demo to discover how a modern DSP can strengthen your security and support your goals.

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