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The Data Security Posture Management Show: A Podcast-style Exploration of IBM Guardium Insights SaaS – DSPM

By Jim Venuto | Published: 01/28/2024

Title: The Data Security Posture Management Show: A Podcast-style Exploration of IBM Guardium Insights SaaS – DSPM

Podcast Outline: “Data Security Deep Dive: IBM Guardium Insights SaaS DSPM”

Host: Jim is an experienced podcast emcee and passionate about tech journalism.

Expert Guest: Alex Johnson, Chief Information Security Officer at CloudSecure Inc., specializing in hybrid cloud-native architectures with data sources in AWS, GCP, Azure, and SaaS apps like SharePoint, Slack, and Google Drive.

Format: Interview and Q&A sessions with commercial breaks.

Introduction [0:00-2:00]

Figure 1: GI-SaaS DSPM Overview Screen. This image displays the main interface of the GI-SaaS Data Security Posture Management (DSPM) system.

Segment 1: Overview of DSPM [2:00-10:00]

Segment 2: Deep Dive into IBM Guardium Insights SaaS DSPM Features [10:00-20:00]

Figure 2: illustrates the identification of unauthorized data duplication across cloud accounts, explicitly highlighting the copying of sensitive ‘DATE_OF_BIRTH’ information from ‘userdata3.parquet’ to another account. The graphic also includes a recommendation for remediation: removal of unnecessary data copies to mitigate the security risk.

Figure 3: Adding Cloud Accounts and SaaS Applications. This graphic illustrates the straightforward method for selecting and adding cloud accounts and SaaS applications.

Figure 4: Sensitive Data Exposure Alert – GI-SaaS DSPM detects a data vulnerability where sensitive data is publicly exposed online, potentially violating PCI compliance. The S3 configuration allows public access, which is the cause of the vulnerability. The provided Terraform script suggests remediation to secure the S3 bucket by blocking public access.

Figure 5: Inventory of Discovered and Classified Sensitive Data in GI-SaaS DSPM. This figure showcases a portion of identified cloud account sensitive data inventory and filters.

Segment 3: Listener Call-In Questions [20:00-30:00]

Figure 6: Third-Party Vulnerability Detection – This graphic identifies a vulnerability involving ‘SampleVendor,’ a third-party vendor erroneously granted access to sensitive data for which they lack appropriate certification. The depiction focuses on the scope of unauthorized access and its implications for data security.

Segment 4: Expert Insights [30:00-40:00]

Segment 5: Advanced Features and Future Outlook [40:00-50:00]

Segment 6: More Listener Call-In Questions [50:00-60:00]

Figure 7a: An AWS S3 bucket contains ten ‘potential’ sensitive data flows and one ‘actual’ (confirmed) sensitive data flow, indicating a need to investigate whether these are intentional or due to a cloud misconfiguration vulnerability.

Figure 7b: Shows the same AWS S3 account as in Figure 7a with focus on the ten potential read/write access flows to external accounts. A ‘potential flow’ represents a configuration allowing the movement of sensitive data, though no such movement has occurred yet.

Figure 7c: Displays the same AWS S3 account as in previous figures, focusing on a single actual flow of sensitive data to a third party with read access. An actual flow signifies a data movement event that has already taken place.

Concluding Segment [60:00-62:00]