T1643: Generate Traffic from Victim
Adversaries may generate outbound traffic from devices. This is typically performed to manipulate external outcomes, such as to achieve carrier billing fraud or to manipulate app store rankings or ratings. Outbound traffic is typically generated as SMS messages or general web traffic, but may take other forms as well.
If done via SMS messages, Android apps must hold the `SEND_SMS` permission. Additionally, sending an SMS message requires user consent if the recipient is a premium number. Applications cannot send SMS messages on iOS
Security context for executives and security teams
T1643: Generate Traffic from Victim describes Adversaries may generate outbound traffic from devices. This is typically performed to manipulate external outcomes, such as to achieve carrier billing fraud or to manipulate app store rankings or ratings. Outbound traffic is typically generated as SMS messages or general web traffic, but may take other forms as well. If done via SMS messages, Android apps must hold the `SEND_SMS` permission. Additionally, sending an SMS message requires user consent if the recipient is a premium number. Applications cannot send SM...
Executive priority
T1643: Generate Traffic from Victim is an official MITRE ATT&CK technique. Glexia treats it as defensive behavior context for prioritizing monitoring, control validation, and response planning without using the object by itself as an attribution claim.
Technical view
Security teams should validate T1643: Generate Traffic from Victim by reviewing the official ATT&CK relationships, mapped tactics (impact), supported platforms (Android, iOS), and available local telemetry before making detection or mitigation decisions.
Likely telemetry
- Official ATT&CK relationships and object metadata
Detection direction
- Validate whether T1643: Generate Traffic from Victim appears in your detection coverage and tabletop scenarios.
- Use the object to align executive risk language with SOC, incident response, and detection engineering work.
- Do not treat ATT&CK relationship context as attribution without corroborating evidence.
Mitigation priorities
- Map the object to existing controls and identify missing telemetry or response ownership.
- Prioritize mitigations that reduce exposure on the listed platforms and tactics.
- Review adjacent ATT&CK relationships before changing policy, detections, or reporting language.
Additional notes and limits
Baseline Glexia take generated from the official MITRE ATT&CK STIX object, source hash, tactics, platforms, and detection fields. It is safe to replace with a richer model-generated take for the same source hash later.
This baseline take is source-grounded and schema-validated, but it does not include environment-specific telemetry, incident evidence, or threat-intelligence corroboration.
Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.
Generate Traffic from Victim
Adversaries may generate outbound traffic from devices. This is typically performed to manipulate external outcomes, such as to achieve carrier billing fraud or to manipulate app store rankings or ratings. Outbound traffic is typically generated as SMS messages or general web traffic, but may take other forms as well.
If done via SMS messages, Android apps must hold the `SEND_SMS` permission. Additionally, sending an SMS message requires user consent if the recipient is a premium number. Applications cannot send SMS messages on iOS
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.
Related techniques
This mirrors the MITRE pattern of making group, software, campaign, and technique relationships scannable. Relationship notes come from mirrored ATT&CK relationship text when available.
| Domain | ID | Name | Relationship / procedure |
|---|---|---|---|
| Mobile | T1472 | Generate Fraudulent Advertising Revenue | Generate Fraudulent Advertising Revenue revoked by this object. |
| Mobile | T1448 | Carrier Billing Fraud | Carrier Billing Fraud revoked by this object. |
| Mobile | T1452 | Manipulate App Store Rankings or Ratings | Manipulate App Store Rankings or Ratings revoked by this object. |
Groups, software, and campaigns
S0525: Android/AdDisplay.Ashas
Android/AdDisplay.Ashas is a variant of adware that has been distributed through multiple apps in the Google Play Store. [1]
S0545: TERRACOTTA
TERRACOTTA is an ad fraud botnet that has been capable of generating over 2 billion fraudulent requests per week.[1]
S0325: Judy
S0326: RedDrop
S0290: Gooligan
Gooligan is a malware family that runs privilege escalation exploits on Android devices and then uses its escalated privileges to steal authentication tokens that can be used to access data from many Google applications. Gooligan has been described as part of the Ghost Push Android malware family. [1] [2] [3]
S0291: PJApps
S0440: Agent Smith
Agent Smith is mobile malware that generates financial gain by replacing legitimate applications on devices with malicious versions that include fraudulent ads. As of July 2019 Agent Smith had infected around 25 million devices, primarily targeting India though effects had been observed in other Asian countries as well as Saudi Arabia, the United Kingdom, and the United States.[1]
S0303: MazarBOT
S0293: BrainTest
S0419: SimBad
SimBad was a strain of adware on the Google Play Store, distributed through the RXDroider Software Development Kit. The name "SimBad" was derived from the fact that most of the infected applications were simulator games. The adware was controlled using an instance of the open source framework Parse Server.[1]
S0321: HummingWhale
HummingWhale is an Android malware family that performs ad fraud. [1]
S0432: Bread
Bread was a large-scale billing fraud malware family known for employing many different cloaking and obfuscation techniques in an attempt to continuously evade Google Play Store’s malware detection. 1,700 unique Bread apps were detected and removed from the Google Play Store before being downloaded by users.[1]
All related ATT&CK context
Mitigation direction
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(3)
| Release | Bundle imported | Object version | Modified | Status | Raw hash |
|---|---|---|---|---|---|
| 20.0 | 1.1 | Current bundle | cbcb33d85a08… | ||
| 19.2 | 1.1 | Older bundle | cbcb33d85a08… | ||
| 19.1 | 1.1 | Older bundle | cbcb33d85a08… |
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]NIST Mobile Threat CatalogueAPP-16Open source URL
- [2]mitre-attackT1643Open 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.