AN1019: Analytic 1019
Detection of excessive or programmatic access to Confluence spaces or pages, particularly by privileged users, through a combination of access logs, API usage, and identity context. Correlates logon sessions, user roles, and abnormal document viewing or export behavior. Identifies burst access patterns and tools/scripts abusing the Confluence API for mass enumeration or data scraping.
Analyst context for executives and security teams
This analytic matters because Confluence often contains sensitive operational, engineering, legal, and incident-response knowledge. Excessive or scripted access to spaces and pages—especially by privileged users—can indicate mass enumeration or data scraping in a SaaS collaboration environment. For leaders, the key question is whether the organization can distinguish normal knowledge-work activity from abnormal bulk viewing, exporting, or API-driven access.
Executive priority
Prioritize this where Confluence holds business-critical or regulated information. The decision value is in validating whether access logs, API activity, login sessions, user roles, and identity context can be correlated quickly enough to support incident triage, audit evidence, and data exposure assessment. This is especially relevant for SaaS security governance and privileged-user oversight.
Technical view
SOC and detection teams should validate monitoring for Confluence access patterns across page and space views, exports, API usage, logon sessions, and user role context. Because no ATT&CK tactic or formal detection logic is supplied, implementation should focus on baselining normal user and privileged-user behavior, then identifying bursts, unusual volume, abnormal export behavior, or scripted/API access inconsistent with expected job function.
Likely telemetry
- Confluence access logs for page and space views
- Confluence export activity logs where available
- Confluence API usage records
- User logon/session records
- Identity and role context, especially privileged-user status
Detection direction
- Confirm that Confluence SaaS logs are collected with enough detail to correlate users, sessions, roles, API activity, document views, and exports.
- Baseline normal access volume by user, role, team, and business process before alerting on excessive access.
- Tune for burst access patterns and programmatic API behavior that may indicate mass enumeration or scraping.
- Review privileged-user activity separately because administrative or elevated access can create broader data exposure risk.
- Account for false positives from migrations, indexing, audits, backup workflows, integrations, or legitimate bulk documentation work.
Mitigation priorities
- Ensure Confluence access logging and API activity logging are enabled and retained for investigation and compliance needs.
- Review privileged access and role assignments for least-privilege alignment.
- Apply identity governance controls around privileged users, including periodic access review and session accountability.
- Define acceptable bulk export, API, and automation use cases so detections can distinguish sanctioned activity from suspicious behavior.
- Prepare incident-response procedures for rapid scoping of viewed, exported, or scraped Confluence content.
Analyst notes and limits
This is a detection analytic for SaaS Confluence activity. Its value is strongest when paired with identity context and a local understanding of normal collaboration patterns. The supplied object provides a behavioral description but no explicit ATT&CK tactic, technique relationship, or official detection query.
Official detection logic is not provided, and no relationships are supplied. The take is therefore limited to the described Confluence SaaS behavior and cannot assert specific adversary attribution, active exploitation, impact, or coverage. Local telemetry availability and Confluence logging configuration will determine practical usefulness.
Analytic 1019
Detection of excessive or programmatic access to Confluence spaces or pages, particularly by privileged users, through a combination of access logs, API usage, and identity context. Correlates logon sessions, user roles, and abnormal document viewing or export behavior. Identifies burst access patterns and tools/scripts abusing the Confluence API for mass enumeration or data scraping.
How security teams should use this page
Treat this object as behavior context, not an attribution claim. Validate the related groups, software, data sources, and mitigations against official ATT&CK relationships and your own telemetry before making control-coverage decisions.
All related ATT&CK context
No relationships are available in the current normalized data for this object.
Object version and sync metadata
The fields below describe the current mirrored snapshot. When Glexia retains multiple ATT&CK source imports, you can open the table to compare the same object across releases (hashes and MITRE timestamps). For MITRE’s own release notes and roadmap, see ATT&CK resources — Updates .
Imported snapshots across ATT&CK releases (1)
| Release | Bundle imported | Object version | Modified | Status | Raw hash |
|---|---|---|---|---|---|
| 19.1 | 1.0 | Current bundle | e50fa3cdbac3… |
Mirrored ATT&CK source object
The raw object is retained through the mirrored ATT&CK source bundle and object hash. The raw endpoint returns the exact object from the mirrored bundle when available.
External references and citations
MITRE external references are preserved separately from Glexia analysis so citations remain traceable to their original source records.
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mitre-attack AN1019Open source URL
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