AN0929: Analytic 0929
EndpointSecurity/Unified Logs show processes generating custom alphabets or long high-entropy, non-standard tokens → network logs (PF/Zeek/EDR) show asymmetric beacons, protocol mismatches, or periodic fixed-size posts.
Analyst context for executives and security teams
This analytic is about spotting macOS processes that appear to create unusual encoded or high-entropy tokens and then correlate that endpoint behavior with suspicious outbound network patterns such as asymmetric beaconing, protocol mismatches, or periodic fixed-size posts. For leaders, the value is not the token itself; it is the opportunity to connect host behavior and network behavior early enough to support triage before an incident becomes harder to scope.
Executive priority
Prioritize this as a visibility and correlation question for macOS environments. Security leaders should ask whether endpoint logging, network monitoring, and SOC workflows can join process-level evidence with outbound network patterns. The business decision value is in validating whether managed detection, incident response, and compliance evidence can show what process generated suspicious traffic, when it happened, and whether it was isolated to one host or part of a broader pattern.
Technical view
For SOC and detection teams, validate collection from macOS EndpointSecurity and Unified Logs, then correlate process activity indicating custom alphabets or long high-entropy, non-standard tokens with network telemetry from PF, Zeek, or EDR. Because no ATT&CK tactic or relationship context is supplied, treat this as a behavioral analytic rather than a complete incident conclusion. Triage should focus on parent process, command context where available, destination, timing regularity, payload size patterns, and protocol consistency.
Likely telemetry
- macOS EndpointSecurity process telemetry
- macOS Unified Logs
- Process creation and process ancestry evidence from EDR where available
- Outbound network connection logs
- PF firewall logs
Detection direction
- Validate that macOS endpoint logs retain enough process context to identify the process associated with suspicious token generation.
- Correlate endpoint evidence with outbound network behavior instead of alerting on high entropy alone, which may occur in legitimate software, encryption, authentication, compression, or developer tools.
- Tune for combinations of unusual token generation plus asymmetric beaconing, protocol mismatch, or periodic fixed-size posts.
- Review false positives from legitimate applications that generate identifiers, session tokens, telemetry payloads, or encoded data.
- Confirm whether SOC tooling can pivot from a network event back to the originating macOS process and host timeline.
Mitigation priorities
- Establish or improve macOS endpoint logging coverage before relying on this analytic.
- Ensure network telemetry sources such as PF, Zeek, or EDR are retained and searchable with timestamps that support host-to-network correlation.
- Define triage playbooks for suspicious macOS process-to-network correlations, including containment decision points and evidence preservation.
- Use findings to harden monitoring gaps in managed detection, incident response readiness, and compliance evidence collection.
- Where suspicious behavior is confirmed locally, apply standard response actions such as host isolation, scope analysis, and review of related process and network activity.
Analyst notes and limits
The supplied object is a detection analytic for macOS and provides a compact behavioral description but no formal detection logic, tactic mapping, technique relationship, or adversary relationship. The strongest use is as a detection engineering prompt: test whether endpoint and network telemetry can be correlated well enough to investigate unusual token generation paired with suspicious outbound traffic patterns.
No official detection field, ATT&CK tactics, related techniques, groups, software, or campaigns were supplied. This take cannot infer active exploitation, attribution, impact, or coverage. Local baselining is required because high-entropy strings and periodic network posts can be legitimate in many macOS applications.
Analytic 0929
EndpointSecurity/Unified Logs show processes generating custom alphabets or long high-entropy, non-standard tokens → network logs (PF/Zeek/EDR) show asymmetric beacons, protocol mismatches, or periodic fixed-size posts.
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 | d8feedafc863… |
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.
-
[1]
mitre-attack AN0929Open source URL
Source: MITRE ATT&CK®. © 2026 The MITRE Corporation. This work is reproduced and distributed with the permission of The MITRE Corporation. MITRE ATT&CK and ATT&CK are registered trademarks of The MITRE Corporation. Glexia is not affiliated with or endorsed by MITRE.