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MITRE ATT&CK® Analytic

AN1793: Analytic 1793

A defender observes an application establishing application-layer network sessions (e.g., HTTP(S), WebSocket, DNS, SMTP/IMAP) with destinations and request patterns that deviate from the enterprise baseline for that app category, especially when sessions occur during background execution or while the device is locked and exhibit beacon-like periodicity, anomalous SNI/Host patterns, or suspicious request/response size symmetry consistent with command polling and tasking over legitimate-looking protocols.

MobileAN1793AnalyticObject v1.1 Modified
Glexia's Take

Analyst context for executives and security teams

Analyst confidence High

This analytic is about spotting Android apps whose network behavior no longer looks normal for their app category, especially background or locked-device traffic that resembles periodic command polling over common protocols such as HTTP(S), WebSocket, DNS, or email protocols. For leaders, the value is not the protocol itself; it is whether the organization can distinguish expected mobile app activity from covert, legitimate-looking communications that may evade simple allow/block controls.

Executive priority

Prioritize this as a mobile visibility and resilience question: do security teams have enough baseline, device-state, and network-session evidence to recognize abnormal Android application communications before they become an incident decision problem? It is relevant to managed detection, incident response readiness, mobile security governance, and compliance evidence where the organization must show monitoring of enterprise mobile devices or managed apps.

Technical view

For SOC and detection teams, validate whether Android network telemetry can be tied to the originating application and enriched with device state such as background execution or locked-screen activity. Detection engineering should focus on deviations from enterprise baselines for app categories, including unusual destinations, SNI/Host values, request timing, beacon-like periodicity, and suspicious request/response size symmetry. Because no official detection logic is provided and no relationships are supplied, teams should treat this as an analytic design requirement rather than a ready-to-run rule.

Likely telemetry

  • Android application-to-network session metadata
  • HTTP(S), WebSocket, DNS, SMTP, and IMAP connection or request metadata where available
  • Destination domains, IPs, SNI, Host headers, and URL/request pattern metadata where policy permits
  • Request and response sizes or byte counts
  • Connection timing, recurrence, and periodicity data

Detection direction

  • Build baselines by managed Android app or app category before alerting on deviations; generic anomaly alerts without baseline context are likely to be noisy.
  • Correlate network sessions with application identity and device state, especially background or locked-device execution.
  • Look for combinations of indicators rather than a single feature: unusual destinations plus periodic timing, anomalous SNI/Host patterns, or symmetric request/response sizes.
  • Tune for legitimate background services, push notifications, synchronization, and enterprise apps that naturally communicate while devices are idle.
  • Validate blind spots where encrypted traffic limits content inspection, where DNS/SNI visibility is reduced, or where telemetry cannot attribute sessions to a specific app.

Mitigation priorities

  • Establish approved mobile app inventories and expected network behavior baselines for managed Android environments.
  • Ensure mobile device management, mobile threat defense, network monitoring, or equivalent controls can associate traffic with Android applications and device state.
  • Restrict or review unmanaged applications and unexpected background network activity according to enterprise mobile policy.
  • Create incident response playbooks for suspicious mobile app communications, including device isolation, app review, evidence preservation, and user/business-owner coordination.
  • Use findings to support compliance evidence for mobile monitoring and policy enforcement, while documenting telemetry gaps where full packet or app attribution is unavailable.
Analyst notes and limits

The ATT&CK object is a mobile detection analytic for Android, external ID AN1793, associated with DET0685. It describes anomalous application-layer network sessions that deviate from enterprise baselines and may resemble command polling over legitimate-looking protocols. No tactics, relationships, aliases, labels, or official detection logic were supplied.

This take is limited to the supplied official STIX fields and external reference. It does not establish active exploitation, threat actor attribution, impact, or guaranteed detection coverage. Local mobile management scope, privacy constraints, app inventory quality, and available network telemetry will determine whether this analytic is actionable.

Official MITRE ATT&CK definition

Analytic 1793

A defender observes an application establishing application-layer network sessions (e.g., HTTP(S), WebSocket, DNS, SMTP/IMAP) with destinations and request patterns that deviate from the enterprise baseline for that app category, especially when sessions occur during background execution or while the device is locked and exhibit beacon-like periodicity, anomalous SNI/Host patterns, or suspicious request/response size symmetry consistent with command polling and tasking over legitimate-looking protocols.

View the same entry on attack.mitre.org (MITRE-hosted reference; in-page links above use the Glexia ATT&CK library.)

Glexia analysis

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.

Relationship explorer

All related ATT&CK context

No relationships are available in the current normalized data for this object.

Change history

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 .

ATT&CK release
19.1
Object version
1.1
Created
Modified
Raw hash
935ab7370260d64d...
Imported snapshots across ATT&CK releases (1)
Release Bundle imported Object version Modified Status Raw hash
19.1 1.1 Current bundle 935ab7370260…
Raw source

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.

Source references

External references and citations

MITRE external references are preserved separately from Glexia analysis so citations remain traceable to their original source records.

  1. [1]
    mitre-attack AN1793
    Open source URL
Source and licensing

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