Protecting Data when Migrating Confluence and Jira from On-Prem to Cloud in 2025

In early 2021, Atlassian announced a major shift: the discontinuation of new on-prem server licenses for products like Jira and Confluence. By 2024, official support for on-prem server instances reached its end. Now in 2025, any organization still relying on these outdated on-prem setups faces increased security gaps, compliance risks, and missed feature updates. It’s high time to migrate your Confluence and Jira instances to Atlassian’s cloud environment.

However, moving large volumes of data—often containing personal, financial, or proprietary information—carries significant risk if not managed properly. Data loss prevention (DLP) has become a cornerstone of secure cloud migrations, ensuring that sensitive information is discovered, classified, and protected at every stage of the journey.

Exfiltration Risks Rise with Cloud Adoption

Atlassian Cloud offers unlimited instances per customer, enabling business units to spin up new Jira projects or Confluence spaces rapidly. While this flexibility accelerates innovation, it can also widen your threat surface:

• Under tight deadlines, teams may focus on quick deployments rather than thorough security configurations.
• Multiple teams might create their own Confluence or Jira environments without formal security checks or consistent access controls.
• Some organizations believe the vendor alone secures all data. In reality, Atlassian follows a shared responsibility model: they handle infrastructure security, but it’s your job to control data usage and protect your own sensitive information.

Remote and hybrid work also play a role. Employees and contractors scattered across various locations might introduce misconfigurations or store personal data in the wrong spaces. Ultimately, API-based DLP solutions help you spot and fix these vulnerabilities swiftly—before they become costly breaches.

Atlassian’s Confluence & Jira: Treasure Troves for Sensitive Data

Confluence is your team’s source of truth, hosting everything from architectural diagrams to marketing strategies. Jira tracks operational and development tasks, with user stories, attachments, and comment threads that can contain intellectual property, personally identifiable information (PII), or even credentials.

Real-World Examples

• Misconfiguration Incidents: A Jira authorization error once exposed Fortune 500 companies’ corporate data and personal info. Oversights in “Global Permissions” meant private issues were inadvertently shared with the public.
• High-Profile Hacks: The April 2021 Codecov breach raised concerns when Atlassian was named among the tens of thousands of potentially exposed customers. While Atlassian was not found to be compromised, it served as a wake-up call that even best-in-class cloud platforms can be indirectly affected by supply chain attacks.

Human error remains a constant wildcard: a single mislabel, a single incorrect “share” setting in Confluence, or a single well-meaning user placing credentials into a Jira ticket can open the door to large-scale data exfiltration.

Getting Started: API-Based DLP for Confluence & Jira

The baseline approach for securing your Atlassian migration is to deploy an API-based DLP solution that directly connects to Confluence and Jira Cloud environments. Rather than relying on manual exports or network-level scanning, API-based solutions integrate at the application layer to continuously monitor, detect, and remediate sensitive data.

How API-Based DLP Works

1. Direct Integration: Through Atlassian-approved APIs, the DLP service scans pages, attachments, comments, and other objects in real time without needing complicated manual setups.
2. Automated Classification: Machine learning models classify data (e.g., PCI, PHI, PII, credentials, secrets) within Confluence and Jira content.
3. Real-Time Remediation: When policy violations occur (such as a leaked credit card number or social security number), the DLP can alert admins or end-users, redact the data, or quarantine the file immediately.
4. Audit & Reporting: The system maintains logs and dashboards, helping you demonstrate compliance with regulations like HIPAA, PCI DSS, or GDPR.

Why This Approach?

• Minimal Disruption: Users can continue working in Confluence and Jira without noticing any performance degradation or tedious manual checks.
• Comprehensive Coverage: API-based scanning covers historical and newly added content, ensuring that dormant or newly created sensitive data is detected.

Extending Coverage: All-in-One DLP

While API-based DLP for Atlassian Cloud is a great start, all-in-one DLP solutions offer end-to-end protection across multiple SaaS platforms and endpoints. Once you’ve established coverage for Confluence and Jira, it makes sense to extend the same policies, classification methods, and security controls to the rest of your environment.

1. Multiple SaaS Apps, Unified Policies

Chances are, your teams don’t just use Atlassian tools. They might also rely on Slack, Google Drive, Microsoft 365, Salesforce, GitHub, or dozens of other platforms. Maintaining separate DLP policies for each SaaS platform increases complexity and leaves room for inconsistent enforcement.

• Risk Example: An employee downloads a Confluence page containing sensitive IP to their desktop and uploads it to Google Drive that isn’t monitored—leading to an untracked leak.
• All-in-One DLP Benefit: A single pane of glass for detecting, classifying, and applying the same data protection rules across all your SaaS apps reduces blind spots and administrative overhead.

2. Endpoint Coverage to Thwart Advanced Exfiltration

A purely SaaS-focused DLP approach might miss threats that occur offline or on local devices. Malicious insiders or attackers with endpoint access can exfiltrate data using external drives, personal cloud accounts, or even printing sensitive documents.

• Risk Example: An engineer exports confidential Jira tickets and uploads them to a personal cloud store, or attempts to email them from a personal account while offsite.
• All-in-One DLP Benefit: Endpoint coverage tracks data movement wherever it flows—flagging or blocking unauthorized attempts to transfer critical files, even if they don’t involve Atlassian or other SaaS apps.

3. Data Lineage + AI-Based Classification: Seeing the “What” and the “How”

Combining data lineage with AI-driven classification provides a holistic understanding of both the content of data and how it moves:

• Data Lineage: Reveals where data originates, where it’s stored, who accesses it, and where it’s ultimately sent.
  • Risk Example: A marketing team member downloads a Confluence file containing customer PII, and another user uploads it to an external partner in Slack. Without lineage tracking, it’s hard to see the chain of custody.
• AI Classification: Precisely identifies PII, PCI data, intellectual property, or any other sensitive pattern within files and text.
  • Risk Example: If an employee inadvertently commits access keys or passwords in a Jira comment, advanced AI detectors can quickly catch these strings, even if they’re embedded in code blocks or hidden in attachments.

When combined, these technologies help prevent exfiltration by automatically pinpointing suspicious data transfers and enabling swift action—such as automatic encryption, quarantine, or policy enforcement.

Nightfall DLP for Confluence & Jira

Nightfall is one example of an AI-first, all-in-one data loss prevention solution that connects directly with Atlassian’s APIs to scan Confluence and Jira. Its key features include:

• Accurate AI-Trained Detectors: Identify hundreds of types of sensitive data, from PII to secrets, in real time.
• OCR and File Scanning: Recognize hidden text in PDFs, images, and over 100 other attachment file types.
• Automated Remediation: Remove or redact violations from Confluence pages, Jira attachments, comments, and more—keeping data safe without manual intervention.
• Historical & Continuous Scanning: Both older content and new additions are covered, giving you peace of mind during and after migration.

Action Steps for a Secure Atlassian Cloud Migration

1. Map Your Data
   • Inventory what’s in Confluence pages and Jira projects, focusing on regulated or sensitive information.
   • Atlassian’s own cloud migration checklist can assist in scoping tasks.
2. Deploy API-Based DLP First
   • Integrate a solution like Nightfall to cover Confluence and Jira from the start of your cloud journey.
   • Configure detection rules, policies, alerts, and remediation actions aligned with your compliance requirements.
3. Augment with an All-in-One DLP if Needed
   • Extend DLP coverage to other critical SaaS platforms for consistent enforcement.
   • Add endpoint monitoring to prevent advanced exfiltration attempts outside SaaS apps.
4. Train Employees
   • Explain the new DLP policies so they understand how to safely handle data in Jira and Confluence.
   • Highlight common pitfalls (e.g., accidentally uploading PII or credentials).
5. Maintain Vigilance
   • Regularly review DLP alerts, update policies as new apps or data types come online, and conduct periodic audits for compliance.

Migrating Confluence and Jira to the cloud is no longer optional—Atlassian has ended on-prem support, and the security risks of running unsupported environments are too great. Baseline, API-based DLP is crucial for scanning and securing your Atlassian ecosystem in real time, preventing leaks while enabling safe collaboration. From there, all-in-one DLP can unify data protection across multiple SaaS platforms, endpoints, and different data flows, with data lineage and AI-driven classification providing the end-to-end visibility and precision needed to guard against both accidental and malicious data exfiltration.

Whether you’re a small startup or a large enterprise, the key to a smooth Atlassian cloud migration is ensuring that sensitive data isn’t overlooked. By investing in the right DLP strategies—starting with Confluence and Jira and expanding to a comprehensive all-in-one solution—you’ll keep your valuable information secure, your team productive, and your organization protected well into the future. Schedule a demo with Nightfall to talk to a DLP expert and discuss your Atlassian migration strategy.