It's important to keep sensitive data safe throughout its entire lifecycle, from the time it's created to the time it's no longer needed. This involves defining processes and procedures to secure the data, as well as using the right technical controls. While it takes effort, protecting sensitive data is essential for organizations of all sizes.

Where did this come from?

This control comes from the CSA Cloud Controls Matrix v4.0.10 released on 2023-09-26. You can download the full matrix here: https://cloudsecurityalliance.org/artifacts/cloud-controls-matrix-v4

The Cloud Security Alliance is a not-for-profit organization dedicated to defining best practices to help ensure a secure cloud computing environment. The Cloud Controls Matrix provides a controls framework for cloud providers and cloud consumers.

Who should care?

Anyone responsible for safeguarding sensitive data should care about this control, including:

• CISOs and security managers responsible for the organization's overall data protection strategy
• Data owners who are accountable for specific datasets
• Developers building applications that handle sensitive data
• Cloud security architects designing secure cloud environments

What is the risk?

Failing to adequately protect sensitive data throughout its lifecycle could lead to:

• Data breaches resulting in disclosure of private information, intellectual property, or regulated data
• Compliance violations and regulatory fines
• Reputational damage and loss of customer trust

Malicious insiders, external attackers, misconfiguration, or human error could all potentially compromise data if lifecycle protections are lacking.

What's the care factor?

For organizations dealing with large volumes of sensitive data, this should be a high priority control. Even a single data breach can be hugely damaging. Highly regulated industries like healthcare and finance are required to demonstrate strong data lifecycle controls.

However, the level of effort should be tailored to the type and quantity of sensitive data involved. Overprotecting low-risk datasets wastes resources.

When is it relevant?

Data lifecycle protection is most relevant when:

• Handling regulated data like PII, PHI, or cardholder data
• Dealing with highly sensitive intellectual property
• Migrating data to the cloud for the first time
• Merging datasets during a corporate acquisition

It may be less critical for smaller organizations with minimal sensitive data or datasets with very short lifespans.

What are the trade-offs?

Protecting data throughout its lifecycle requires additional processes, controls, and technologies. This means:

• More time and effort to classify data and define policies
• Reduced agility if strict controls slow down data flows
• Frustrated users if security creates friction
• Higher cloud costs for dedicated security tools

How to make it happen?

1. Discover and classify sensitive data across the organization
2. Define policies for each data class and lifecycle stage
3. Implement access controls, encryption, tokenization, and other technical measures
4. Use tools like Azure Information Protection to label and protect individual files
5. Monitor data access and movement using DLP and CASB solutions
6. Implement secure data erasure when data is no longer needed
7. Train users on data handling best practices
8. Assess, audit, and continuously improve the program

What are some gotchas?

• Classification can be challenging for large, diverse datasets
• Legacy applications may not support modern data protection controls
• Encryption key management requires careful planning
• Cross-border data flows introduce extra regulatory complexity

Specific permissions like Microsoft Graph DLP API access may be required for certain tools:
https://docs.microsoft.com/en-us/graph/api/resources/dlp-api-overview

What are the alternatives?

Avoiding the cloud or relying purely on the provider for security are risky alternatives. Tokenization or format-preserving encryption can sometimes be used instead of traditional encryption to protect structured data.

Explore further

• NIST SP 800-53 includes several related controls like SC-28 (https://csrc.nist.gov/Projects/risk-management/sp800-53-controls/release-search#/control?version=5.1&number=SC-28)
• CIS Control 13 focuses on data protection (https://www.cisecurity.org/controls/data-protection)
• Microsoft's Azure Information Protection is one example of a cloud-based data lifecycle protection solution (https://docs.microsoft.com/en-us/azure/information-protection/what-is-information-protection)

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