Mitigate AI security risks with Amazon Q Business and Securiti: Five-step governance framework

Organizations want to harness AI productivity gains but struggle with a fundamental challenge: how to give employees AI-powered insights by applying appropriate access controls across their data. Amazon Q Business helps address this challenge by applying your configured access controls to AI interactions. However, many organizations lack the visibility and automation needed to manage, review, and optimize their access controls, data classification, and quality policies before deployment at scale. Securiti’s third-party Security for Amazon Q Business solution, now available in AWS Marketplace, bridges this gap by providing automated data discovery, classification, and access management—helping you implement Amazon Q Business while maintaining appropriate security and compliance controls.

AWS Marketplace is a digital catalog of third-party software, services, and data that simplifies finding, buying, deploying, and managing software you need to build solutions and run your business on AWS. For organizations implementing Amazon Q Business, you can discover and deploy third-party data governance solutions like Securiti’s Security for Amazon Q Business in AWS Marketplace, maintaining the controls and governance you need to operate with confidence. Available now in AWS Marketplace, Securiti’s solution uses Data Command Center to help implement data security, privacy, and governance controls through automated data access management and file-level analysis—helping you configure Amazon Q Business responses based on authorized access across your environment.

This post demonstrates how Securiti’s five-step governance framework is applied when implementing the Security for Amazon Q solution:

1. Identifying and remediating unintended data access
2. Assessing and strengthening data security posture
3. Prioritizing sensitive data risks
4. Operationalizing Amazon Q Business security controls
5. Minimizing redundant, obsolete, and trivial (ROT) data

Prerequisites

• An AWS account with appropriate permissions
• Access to Amazon Q Business
• A subscription to Securiti’s Security for Amazon Q solution in AWS Marketplace
• Defined data governance policies
• Established data classification standards

Before implementing Securiti’s governance framework, consider these key questions about your environment:

• Access controls: How do you manage access to unstructured files?
  Amazon Q Business helps apply your access controls, so maintaining well-defined entitlements can help you manage data access according to your security and compliance objectives.
• Data visibility: Can you locate sensitive data across your environment?
  Having tools and processes to identify sensitive information can help you make informed decisions about what data to make available through Amazon Q Business.
• Access management: How do you administer data access permissions?
  Automated tools can help you review and update access permissions more consistently while reducing administrative overhead.
• Data classification: How do you approach file classification and labeling?
  Well-maintained metadata can help Amazon Q Business filter responses according to your data access policies and user permissions.
• Data lifecycle management: How do you maintain data quality?
  Regular review and updates of redundant, obsolete, and trivial (ROT) data can help improve the relevance of Amazon Q Business responses.

With these considerations in mind, let’s explore how Securiti’s five-step governance framework helps you evaluate and prepare your data environment and develop an effective strategy for Amazon Q Business implementation.

Implementing the framework with Securiti DSPM

Securiti’s Data Command Center is a service that unifies Data Security Posture Management (Securiti DSPM), privacy, and governance capabilities through a single interface, helping you manage sensitive data across cloud, software as a service (SaaS), and AI environments. Through this unified approach, you can monitor data access, implement classification policies, configure governance controls, and maintain data quality across your environment. This is done across more than 400 structured and unstructured data systems in hybrid, multi-cloud, and on-premises environments.

Let’s examine how each framework step is implemented, as shown in the following figure:

Figure 1 – Framework implementation overview

1. Identifying and remediating unintended data access

   You can use Amazon Q Business with your configured access controls to deliver responses based on user permissions. When you implement Amazon Q Business with unstructured data, you can use Securiti’s Data Command Graph to manage access controls through the following steps:
   
   Step 1 – Map environment: Review the current access configurations and analyze relationships between files, permissions, and access patterns to understand how data is accessed across your organization.
   
   Step 2 – Configure policies: Create custom policies and monitor access policies for Amazon Q Business, with automated monitoring of policy application and notifications for access activity based on your configured rules.

   Step 3 – Automate remediation: Continuously adjust access permissions using identity and file ownership information to align with your organization’s evolving needs.

   As shown in the following figure, the access control configuration displays policy counts, where each count represents the number of privileges a principal has on an object.

   

   Figure 2 – Access Control Configuration

   For example: You can configure role-based access policies for HR documents in Securiti’s solution to control Amazon Q Business responses based on user authorization levels within security boundaries.

2. Assessing and strengthening data security posture

   You can use Amazon Q Business with your configured access settings to control response delivery to users. Regularly reviewing and managing these configurations across your data systems helps maintain effective governance controls. You can use Securiti’s solution to implement and maintain these settings through the following steps:

   Step 1 – Monitor security posture: Review settings across your cloud and SaaS data systems to understand how data is accessed and managed, allowing comparison with your established baseline.

   Step 2 – Identify risks: Examine resource configurations and access patterns, focusing on newly created sites or folders to identify broader access than intended by your policies.

   Step 3 – Configure access settings: Implement configuration changes based on your security policies to align access controls with requirements as new resources are added.

   As shown in the following figure, the configuration management rule details display metrics including the number of policies, policy violations, external sharing status, and the total count of policies using this rule.

   

   Figure 3 – Configuration management rule details

   For example: You can configure automated reviews of new SharePoint sites in Securiti’s solution to identify overly permissive settings and alert security teams, helping align access controls with your security policies.

3. Prioritizing sensitive data risks

   You can use Amazon Q Business with metadata and classification labels to manage access to sensitive information. Organizations need effective tools to classify and organize their data landscape for appropriate AI interactions. You can use Securiti’s solution to implement these controls through the following steps:

   Step 1 – Classify sensitive data: Review and identify different types of information across your environment, such as regulated information, financial records, strategic plans, and other business-critical content according to your organization’s policies.

   Step 2 – Review access combinations: Examine permission configurations and access patterns to understand how different combinations of settings affect data access through Amazon Q Business interactions.

   Step 3 – Prioritize remediation: Collaborate with teams to prioritize and implement access policies that reflect your classification requirements and organizational needs, aligning Amazon Q Business access with your data governance framework.

   As shown in the following figure, the classification management dashboard displays file counts across three categories: files containing sensitive data, files with sensitive data accessible by all users, and all files accessible by all users.

   

   Figure 4 – Classification management dashboard

   For example: You can use Securiti’s Data Command Graph to automatically classify financial data in shared locations and align access controls with your security policies, helping manage appropriate data access through Amazon Q Business.

4. Operationalizing Amazon Q Business security controls

   You can use Amazon Q Business provided built-in security controls to help manage AI access based on metadata and classification labels. As your data landscape grows and changes, maintaining accurate labels become essential for effective access management. You can use Securiti’s solution to streamline this process through the following steps:

   Step 1 – Enable automated labeling: Apply classification labels to files based on multiple attributes, such as data classification, file type, content profile, and ownership to maintain consistency across your environment.

   Step 2 – Apply intelligent classification: Use attributes such as applicable regulations, file age, and usage patterns to implement classification rules across your data landscape.

   Step 3 – Enforce protection policies: Configure policies to manage file access through Amazon Q Business based on classification labels, supporting granular control according to your security requirements.

   For example: You can use Securiti’s Data Command Graph to automatically classify intellectual property documents as confidential and align Amazon Q Business access settings with your data protection policies.

5. Minimizing ROT data
   

   You can improve Amazon Q Business response reliability for your business needs by managing your data quality, including redundant, obsolete, and trivial (ROT) data. The quality of AI-assisted decisions depends on accurate and current information in your data sources. You can use Securiti’s solution to maintain data quality through these steps:

   Step 1 – Detect ROT data: Review duplicate and similar files across your environment using graph-based policies and attribute-based analysis to assess content relevance, file age, and usage patterns.

   Step 2 – Analyze usage patterns: Monitor access and modification patterns, ownership, and usage trends to understand which data is actively used in your environment to support your data management decisions.

   Step 3 – Automate data cleanup: Configure graph-based policies to manage data accuracy, supporting the availability of relevant information for Amazon Q Business responses according to your requirements.

   For example: You can use Securiti’s Data Command Graph to identify redundant files across your data sources, helping improve data quality for more accurate Amazon Q Business responses aligning with your data quality objectives.

Securiti’s Security for Amazon Q Business: Now available in AWS Marketplace

Securiti’s Security for Amazon Q solution available in AWS Marketplace helps organizations implement data governance controls, including data access management, sensitive information discovery, classification controls, and data lifecycle management across hybrid, multi-cloud, and SaaS systems. This enables faster time-to-value while maintaining the controls you need to operate effectively.

Want to learn more?

Schedule a Security for Amazon Q solution demo to see how Securiti helps secure data and AI workloads across your environment

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