Jira & GDPR: How to Reduce Sensitive Data Risks

[#1]

Atlassian is very clear about one thing: Jira is designed with compliance with GDPR in mind. 🛡️

At the same time, GDPR compliance is everyone's responsibility. Atlassian offers a secure and GDPR-ready platform; however, companies using Jira are responsible for how the personal data of their clients is collected, stored, used, and retained in Jira.

And this is where the risk of sensitive data appears.

📘What GDPR Means 

General Data Protection Regulation (GDPR) is a European regulation that aims to safeguard personal data and to give individuals greater control over the use of their information. It applies to any company that processes personal data of people in the EU, regardless of its location.

GDPR concerns principles such as lawful processing, data minimization, transparency, access control, and limited data retention. In practice, that means companies must know where the personal data of their clients is stored, why it is stored, who can access it, and for how long it is stored - including in internal systems like Jira.

⚠️Where GDPR Risks Appear in Jira in Practice

For companies that use Jira to handle customer requests, incidents, or service processes, the personal data may become part of everyday work.

Client data can be added to Jira:

• to investigate support cases
• to troubleshoot technical problems
• to keep track of incidents or bugs reported by customers
• to work internally with customers to perform customer-related tasks

In such circumstances, personal information is often added for convenience, and it is not how Jira is designed to be a customer database.

Common examples include:

• names and email addresses of customers added to work items
• phone numbers or account identifiers included in comments
• screenshots/logs attached to work items containing personal data
• client related information copied from emails or external systems

As time goes by, this data is accumulated in:

• work item descriptions
• comments 
• custom fields
• work item history

Because this often occurs, companies can lose sight of what personal data is stored in Jira and where it resides.

This lack of visibility is where GDPR risks usually occur - not Jira itself, but how client data is used and retained inside it.

🚫Why Removing Data from the Work Item View Is Not Enough

When sensitive or personal data is found in a Jira work item, the first reaction is often to edit the description or delete the comment where the data is found.

While this is an important first step, it is not always enough from a GDPR perspective.

In Jira, many changes are recorded in the work item's history. This means that even after data is removed from the current view:

• earlier versions of the description may still exist
• edited or deleted comments are retained in the change history

As long as personal data is stored and is accessible, it could still be relevant for:

• GDPR audits
• security investigations
• compliance assessments

This is where the companies often think the risk has been eliminated, but in fact, there is still a historical exposure that still exists.

For companies that store client data in Jira, this creates a blind spot: the work item appears "clean" today, but sensitive data may still remain in its previous versions.

Without visibility to the historical content, it is hard to:

• ensure that personal data was completely deleted
• understand what the extent of past exposure was
• ensure good handling of the data during audits

This is why GDPR risk management in Jira needs to focus not only on what is present in today's content but also on historical changes, rather than just on what is present in the work item view.

🔎How to Find Sensitive Data Across Jira Work Items and Their History

To manage GDPR and compliance risks effectively, the type of visibility companies have into current Jira content is not enough. They need safe access to historical data and a way to understand what changed, when, and where - across projects.

This is why many banks, financial institutions, healthcare organizations, and IT companies are relying on Issue History for Jira by SaaSJet as part of their audit and compliance setup.

The app is extensively used to support:

• audit readiness and regulatory reviews
• research of historical changes of work items
• traceability of user actions and modifications of data
• internal and external security assessment

As compliance requirements evolved, the need to go beyond change tracking and address data protection risks directly also evolved.

To help support this, Issue History for Jira increased its functionality with the introduction of Security Scanner View (PII & DLP).

Security Scanner View extends the app's powerful audit base and adds the ability to:

• scan existing work item content
• analyze the changes of work items through history
• find personal and sensitive data stored in Jira

This enables teams not only to have an overview of how data changed, but also to understand which types of data are available, including data that may no longer be visible in the current work item view.

🏦 Why This Matters for Regulated Industries

For companies that work in regulatory environments (such as finance or healthcare), this combined approach is critical.

It enables teams to:

• detect sensitive data across Jira projects without manual reviews
• understand the exposure in history, not only the current state
• provide evidence to support GDPR, security, and audit processes
• reduce compliance risks and maintain day-to-day use of Jira

Instead of working with assumptions, teams get a clear, structured insight into sensitive data stored in Jira - now and in the past.

🧠What Security Scanner View Detects and Why It Matters for GDPR

Security Scanner View (PII & DLP) is designed to detect data patterns that are particularly relevant for GDPR and data protection reviews.

From a GDPR point of view, Security Scanner View could identify personal data, such as:

• names and email addresses
• phone numbers
• IP addresses
• user identifiers and usernames

In addition, Security Scanner also identifies sensitive data that can increase the risk of GDPR incidents, such as:

• passwords and passphrases
• login credentials
• API keys and access tokens
• cloud service credentials
• credit card numbers

While such data is not, in itself, personal data, unauthorized access enabled by it can result in the exposure of personal data, making it relevant from a GDPR risk perspective.

👉 Test Security Scanner View in Issue History for Jira to see what sensitive data exists in your Jira work items and their changes.🚀

✅ Summing Up 

Sensitive data may be visible in the course of daily work and may persist in historical changes even after being removed from view.

Visibility into what is happening now and in the historical Jira content is key in reducing GDPR and compliance risks.

A clear overview of where such data exists helps teams take informed actions and demonstrate responsible data handling during audits.

[Elena_Communardo Products]

Hi @Natalia_Kovalchuk_SaaSJet_ , thanks for the detailed breakdown of where GDPR risks can surface in Jira, especially around historical data. The point about deleted or edited content still existing in history is easy to overlook and really important for compliance teams.