How to Protect Sensitive Data in Large Jira/Confluence Instances

Hi @Utkarsh Chandel while reviews have their place, i see that is a post fact check. I would prefere gating access as the first steps. 

User permissions in both jira and confluence, especially around delete, should be checked and made up to a standard. i woulld set delete permissions with only several users in the organization to constrain that with a bottle neck.

You cant guard against personal pages that user create in their blogs from being deleted, but as a practice, important documents should not be personal documents.

Another option is using a backup, in case something was lost unintentionally.  there are several options to consider here, from 3rd party apps, atlassian's own backup/restore solution, and doing manual backsups to a sandbox from which you can restore data.

I think a mix of both works well. High-risk projects and spaces should be monitored more frequently, while lower-risk areas can be checked on a regular schedule. That helps catch sensitive data early without putting too much load on larger Jira and Confluence instances.

It also makes sense to adjust the scan frequency based on the type of data and how often that area changes.

To answer directly: neither daily nor monthly on its own is quite right, most mature setups use a hybrid.
Scan frequency is usually tied to two things, how sensitive the space is and how much external or uncontrolled input it gets. A legal or HR space with restricted access might only need daily scans since the risk of accidental exposure is lower. A space open to contractors or external Jira users, on the other hand, benefits from scanning on creation or edit, since that's exactly where sensitive data tends to slip in unnoticed, in a comment, an attachment, or a copy pasted log file.

The decision usually comes down to three questions for each space or project:

• Who can post content there, internal only or external too
• What kind of data realistically ends up there (PII, secrets, financial info)
• Has this space had a past DLP or audit flag

On performance, the practical answer is incremental scanning (only new/changed content) plus scheduling full sweeps outside peak hours. Trying to deep scan an entire large instance in real time is usually what causes the performance complaints people bring up.

Disclosure: I work at miniOrange, and our DLP for Data Center app for Jira and Confluence lets you set exactly this kind of tiered scanning, real time for high risk spaces, scheduled for the rest, so admins aren't forced into a single instance wide policy. Mentioning it since it directly addresses what you're asking, not as a blanket recommendation. Interested to see how others are tiering their spaces in practice.

We also have a similar DLP solution for Jira and Confluence cloud as well.

Feel free to reach out to us at atlassiansupport@xecurify.com