Track Data Movement

Gaining insight into how your data moves and who can access it is critical to securing sensitive assets and maintaining compliance.

With Bedrock, organizations can detect risks as they arise —such as when production data is mistakenly copied to a QA environment—while enforcing least privilege access and accelerating response to security and compliance violations. Map entitlements and data flows in detail to stay ahead of threats and ensure reliable protection.
82
%

% of cybersecurity professionals report gaps in finding and classifying organizational data

53
%

% of security teams lack up-to-date data visibility

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Complete Data Access & Usage Visibility

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Track Data Movement: Continuous Visibility & Risk Detection

Bedrock seamlessly maps data flows across SaaS, PaaS, and IaaS, detecting unauthorized transfers, enforcing movement policies, and alerting security teams. Correlate data movement with identity entitlements to pinpoint overexposed assets and prevent compliance violations and enforce Trust Boundaries to keep sensitive data out of unauthorized locations, AI models, and apps.
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  • Security & Compliance: Rapid data flow tracking and security enforcement across cloud environments

  • Dynamic Data Mapping & Flow Analysis: Detect unauthorized data transfers, compliance violations, and overexposures 

  • Integrated Risk Context & Prioritization: Link data movement to entitlements to uncover risks and exposure

  • Policy-Based Data Movement Controls: Prevent sensitive data from reaching unauthorized locations with Trust Boundaries

Right-Size Data Entitlements: Full Access Chain Analysis

Misconfigured access increases security risks. Bedrock maps entitlements, detects over-provisioning, and enforces least privilege to ensure only the right identities access critical data. Automated risk-based controls streamline access management, while real-time identity analysis detects privilege escalations and insider threats before they become breaches.
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  • End-to-end Visibility of Entitlements:  Detect over-provisioning and enforce least privilege with automated controls

  • Identity & Access Visibility: Achieve full visibility into data access, entitlements, and escalations

  • Least Privilege Enforcement: Reduce excessive permissions and insider threats with automated entitlement right-sizing

  • Real-Time Identity Risk Analysis: Detect identity risks by analyzing access behaviors and privilege escalations.

Determine Data Lineage: AI-Driven Context & Precision

Bedrock automates lineage mapping, enriches metadata, and categorizes data to enforce governance, prevent unauthorized exposure, and protect IP. AI-powered classification enhances regulatory risk assessment, while continuous metadata enrichment and policy-driven retention ensure seamless security and compliance.
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  • Automated Lineage Mapping: Enforce governance, prevent exposure, and maintain full data visibility

  • Automated Content Categorization: AI-powered classification enhances data identification and regulatory compliance

  • End-to-End Data Traceability: Track data lineage to enforce governance, protect IP, and prevent exposure

  • Dynamic Metadata Enrichment: Leverage fresh metadata for context-aware security and governance

  • Policy-Driven Data Retention & Expiry: Align data retention with regulations to ensure compliant data management
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Why Bedrock for Tracking Data Movement & Access?

 

Dynamic Data Flow Analysis: Bedrock maps where data resides and how it moves, detecting unauthorized transfers in real time.

Integrated Risk Context: Our platform correlates identity entitlements and access activity, prioritizing high-risk exposures to accelerate response.

Policy-Based Movement Controls: Enforce custom Trust Boundaries with Bedrock, preventing sensitive data from flowing into AI models or unauthorized locations.

 
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Generative Al poses a unique data challenge because once data goes into a model, it's challenging to control the output.

Andrew Kuhn,  Product Security Engineer, House Rx

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Generative AI poses a unique data challenge because once data goes into a model, it’s challenging to control the output. Enterprises need assurances that GenAI models are compliant and secure, and that they will not divulge sensitive information. Bedrock’s ability to automatically learn what data is most material to the business and put boundaries between sensitive data and GenAI models is a game-changer. This capability reduces friction and enables us to safely and responsibly bring GenAI to customers faster.

Suha Can, CISO at Grammarly

 

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I believe that effective security requires looking at the full lifecycle of how customer data is handled. This means getting accurate visibility, enabling data perimeters, and proactively reducing data risk. Bedrock’s innovation excites me and aligns with how I think about protecting data and managing risk effectively.

Mukund Sarma, Sr. Director Product Security, Fastest Growing US Fintech Co.

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Dive Deeper

Learn more about how Bedrock is transforming data movement and access.

See the Difference with Bedrock
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