Messaging Applications

Messaging Applications [T1213.004]

Information

Name: Customer Relationship Management Software
ID: T1213.004
Tactics:
Technique:

Introduction

Messaging Applications () is a sub-technique within the MITRE ATT&CK framework that refers to adversaries utilizing messaging services and applications to communicate, command, or exfiltrate data from compromised systems. Attackers often exploit widely used messaging platforms, such as Telegram, Slack, Discord, WhatsApp, or Signal, to blend malicious traffic into legitimate network communications, evade traditional detection mechanisms, and maintain persistent, covert communication channels.

Deep Dive Into Technique

Adversaries leveraging messaging applications typically use legitimate APIs or publicly available clients to establish command-and-control (C2) channels or to exfiltrate sensitive data. The technical execution of this sub-technique involves several key elements:

Legitimate Infrastructure Abuse:
- Attackers exploit messaging platforms' legitimate infrastructure and APIs to facilitate covert communication.
- Commonly abused platforms include Telegram, Slack, Discord, WhatsApp, Signal, and other similar messaging services.
API Integration and Bots:
- Adversaries create automated bots or scripts that interact with messaging application APIs.
- These bots receive commands, send status updates, or exfiltrate data in a structured format, often encoded or encrypted to evade detection.
Encrypted Channels:
- Messaging applications often provide end-to-end encryption, making detection and analysis difficult.
- Attackers leverage these encrypted channels to securely transmit sensitive data and commands.
Proxy and Anonymization:
- Attackers may use proxy servers or anonymization techniques to further obscure their source IP addresses and identities when communicating through messaging apps.
File and Data Exfiltration:
- Attackers leverage messaging platforms' built-in file sharing capabilities to exfiltrate sensitive documents, screenshots, logs, or credentials without triggering traditional data loss prevention (DLP) systems.
Command-and-Control (C2):
- Messaging applications may serve as covert channels for sending remote commands, updating malware configurations, or receiving status updates from infected systems.
- Malware families have been documented using messaging apps for C2, enabling attackers to maintain persistent access and control over victim systems.

When this Technique is Usually Used

Attackers typically employ messaging applications across various attack stages and scenarios, including:

Initial Access and Persistence:
- Establishing covert communication channels immediately after initial compromise to maintain persistent footholds within victim networks.
Command-and-Control (C2) Stage:
- Utilizing messaging platforms as covert C2 channels to remotely control compromised systems, execute commands, or deliver payloads.
Data Exfiltration Stage:
- Leveraging built-in messaging app file-sharing capabilities and encrypted channels to securely exfiltrate sensitive information.
Evasion and Defense Avoidance:
- Using legitimate messaging platforms to blend malicious traffic with legitimate network traffic, thus bypassing traditional network monitoring and detection systems.
Botnet Management:
- Managing botnets or large-scale infections remotely via messaging application bots, enabling attackers to efficiently control multiple compromised hosts simultaneously.

How this Technique is Usually Detected

Detection of adversaries using messaging applications requires advanced monitoring, analysis, and threat detection approaches, including:

Network Traffic Analysis:
- Monitoring and analyzing network traffic for unusual or unauthorized connections to messaging application domains, APIs, or IP addresses.
- Identifying anomalous patterns, such as regular beaconing behavior, unusual upload/download volumes, or encrypted traffic to known messaging platforms.
Endpoint Detection and Response (EDR) Tools:
- Leveraging EDR solutions to detect suspicious processes or scripts communicating with messaging application APIs or endpoints.
- Detecting unauthorized installation or execution of messaging application clients or bots on endpoints.
Application and API Usage Monitoring:
- Monitoring and auditing API access logs for unusual or unauthorized API calls, unusual frequency, or abnormal data volumes.
- Identifying unexpected or unauthorized bot creation or message-sending behaviors within messaging application platforms.
Behavioral Analytics and Anomaly Detection:
- Employing behavioral analytics solutions to identify anomalous endpoint or user behaviors indicative of unauthorized messaging application use.
- Detecting deviations from baseline messaging application usage patterns, such as unusual hours of activity, abnormal data transfers, or repeated connections to specific messaging APIs.
Indicators of Compromise (IoCs):
- Known suspicious IP addresses, domains, or URLs associated with messaging application abuse.
- Detection of specific malware or scripts known to leverage messaging applications for C2 or data exfiltration.
- Unusual outbound traffic to messaging application domains (e.g., api.telegram.org, discord.com/api, slack.com/api).

Why it is Important to Detect This Technique

Early detection of adversaries leveraging messaging applications is critical due to the following potential impacts and risks:

Data Exfiltration Risk:
- Messaging applications facilitate rapid, encrypted, and covert data exfiltration, significantly increasing the risk of sensitive information leakage and intellectual property theft.
Persistence and Long-Term Compromise:
- Attackers using messaging applications as C2 channels can maintain persistent, covert access to victim environments, enabling long-term espionage, data theft, or sabotage activities.
Evasion of Traditional Security Controls:
- Legitimate messaging platforms often bypass traditional network security controls, firewalls, and intrusion detection/prevention systems, making detection challenging and potentially prolonging the dwell time of attackers.
Reduced Visibility and Response Capabilities:
- Encrypted messaging channels reduce visibility into attacker communications, complicating incident response, forensic analysis, and threat hunting efforts.
Compliance and Regulatory Risks:
- Unauthorized use of messaging applications for data exfiltration or C2 activities can lead to compliance violations, regulatory fines, or reputational damage.
Operational Impact and Business Continuity:
- Malicious use of messaging applications can result in operational disruptions, loss of customer trust, and significant financial damages.

Examples

Real-world examples demonstrating adversaries' use of messaging applications include:

TeleBots (NotPetya) Malware:
- Attackers behind the TeleBots malware leveraged Telegram messaging platform APIs to control infected hosts, send commands, and exfiltrate sensitive information.
- Impact included widespread disruption, financial losses, and compromised sensitive data.
Discord as Malware C2:
- Multiple malware families, including AnarchyGrabber and various ransomware variants, have utilized Discord messaging APIs and webhooks to remotely control compromised hosts, deliver commands, and exfiltrate stolen credentials or sensitive data.
- Attackers leveraged Discord's legitimate infrastructure to evade detection and maintain persistent access.
Slack API Misuse in Targeted Attacks:
- Attackers have been documented using Slack APIs to exfiltrate sensitive data, communicate with compromised endpoints, and execute remote commands within targeted enterprise environments.
- Slack's legitimate infrastructure allowed attackers to blend malicious traffic with legitimate business communications, complicating detection and response efforts.
Signal and WhatsApp for Covert Communication:
- Advanced persistent threat (APT) groups have reportedly adopted encrypted messaging applications like Signal and WhatsApp for secure, covert communication channels during espionage operations and targeted attacks.
- Encryption provided by these platforms significantly hindered detection and forensic analysis.
Telegram-Based RATs and Infostealers:
- Malware variants such as Masad Stealer and TelegramRAT have leveraged Telegram APIs for command-and-control communications, data exfiltration, and remote command execution.
- Attackers benefited from Telegram's ease of use, encryption, and widespread adoption, increasing the effectiveness of their campaigns.

Last updated 1 month ago

Introduction

Deep Dive Into Technique

Legitimate Infrastructure Abuse:

Attackers exploit messaging platforms' legitimate infrastructure and APIs to facilitate covert communication.
Commonly abused platforms include Telegram, Slack, Discord, WhatsApp, Signal, and other similar messaging services.

API Integration and Bots:

Adversaries create automated bots or scripts that interact with messaging application APIs.
These bots receive commands, send status updates, or exfiltrate data in a structured format, often encoded or encrypted to evade detection.

Encrypted Channels:

Messaging applications often provide end-to-end encryption, making detection and analysis difficult.
Attackers leverage these encrypted channels to securely transmit sensitive data and commands.

Proxy and Anonymization:

Attackers may use proxy servers or anonymization techniques to further obscure their source IP addresses and identities when communicating through messaging apps.

File and Data Exfiltration:

Attackers leverage messaging platforms' built-in file sharing capabilities to exfiltrate sensitive documents, screenshots, logs, or credentials without triggering traditional data loss prevention (DLP) systems.

Command-and-Control (C2):

Messaging applications may serve as covert channels for sending remote commands, updating malware configurations, or receiving status updates from infected systems.
Malware families have been documented using messaging apps for C2, enabling attackers to maintain persistent access and control over victim systems.

When this Technique is Usually Used

Attackers typically employ messaging applications across various attack stages and scenarios, including:

Initial Access and Persistence:

Establishing covert communication channels immediately after initial compromise to maintain persistent footholds within victim networks.

Command-and-Control (C2) Stage:

Utilizing messaging platforms as covert C2 channels to remotely control compromised systems, execute commands, or deliver payloads.

Data Exfiltration Stage:

Leveraging built-in messaging app file-sharing capabilities and encrypted channels to securely exfiltrate sensitive information.

Evasion and Defense Avoidance:

Using legitimate messaging platforms to blend malicious traffic with legitimate network traffic, thus bypassing traditional network monitoring and detection systems.

Botnet Management:

Managing botnets or large-scale infections remotely via messaging application bots, enabling attackers to efficiently control multiple compromised hosts simultaneously.

How this Technique is Usually Detected

Detection of adversaries using messaging applications requires advanced monitoring, analysis, and threat detection approaches, including:

Network Traffic Analysis:

Monitoring and analyzing network traffic for unusual or unauthorized connections to messaging application domains, APIs, or IP addresses.
Identifying anomalous patterns, such as regular beaconing behavior, unusual upload/download volumes, or encrypted traffic to known messaging platforms.

Endpoint Detection and Response (EDR) Tools:

Leveraging EDR solutions to detect suspicious processes or scripts communicating with messaging application APIs or endpoints.
Detecting unauthorized installation or execution of messaging application clients or bots on endpoints.

Application and API Usage Monitoring:

Monitoring and auditing API access logs for unusual or unauthorized API calls, unusual frequency, or abnormal data volumes.
Identifying unexpected or unauthorized bot creation or message-sending behaviors within messaging application platforms.

Behavioral Analytics and Anomaly Detection:

Employing behavioral analytics solutions to identify anomalous endpoint or user behaviors indicative of unauthorized messaging application use.
Detecting deviations from baseline messaging application usage patterns, such as unusual hours of activity, abnormal data transfers, or repeated connections to specific messaging APIs.

Indicators of Compromise (IoCs):

Known suspicious IP addresses, domains, or URLs associated with messaging application abuse.
Detection of specific malware or scripts known to leverage messaging applications for C2 or data exfiltration.
Unusual outbound traffic to messaging application domains (e.g., api.telegram.org, discord.com/api, slack.com/api).

Why it is Important to Detect This Technique

Early detection of adversaries leveraging messaging applications is critical due to the following potential impacts and risks:

Data Exfiltration Risk:

Messaging applications facilitate rapid, encrypted, and covert data exfiltration, significantly increasing the risk of sensitive information leakage and intellectual property theft.

Persistence and Long-Term Compromise:

Attackers using messaging applications as C2 channels can maintain persistent, covert access to victim environments, enabling long-term espionage, data theft, or sabotage activities.

Evasion of Traditional Security Controls:

Legitimate messaging platforms often bypass traditional network security controls, firewalls, and intrusion detection/prevention systems, making detection challenging and potentially prolonging the dwell time of attackers.

Reduced Visibility and Response Capabilities:

Encrypted messaging channels reduce visibility into attacker communications, complicating incident response, forensic analysis, and threat hunting efforts.

Compliance and Regulatory Risks:

Unauthorized use of messaging applications for data exfiltration or C2 activities can lead to compliance violations, regulatory fines, or reputational damage.

Operational Impact and Business Continuity:

Malicious use of messaging applications can result in operational disruptions, loss of customer trust, and significant financial damages.

Examples

Real-world examples demonstrating adversaries' use of messaging applications include:

TeleBots (NotPetya) Malware:

Attackers behind the TeleBots malware leveraged Telegram messaging platform APIs to control infected hosts, send commands, and exfiltrate sensitive information.
Impact included widespread disruption, financial losses, and compromised sensitive data.

Discord as Malware C2:

Multiple malware families, including AnarchyGrabber and various ransomware variants, have utilized Discord messaging APIs and webhooks to remotely control compromised hosts, deliver commands, and exfiltrate stolen credentials or sensitive data.
Attackers leveraged Discord's legitimate infrastructure to evade detection and maintain persistent access.

Slack API Misuse in Targeted Attacks:

Attackers have been documented using Slack APIs to exfiltrate sensitive data, communicate with compromised endpoints, and execute remote commands within targeted enterprise environments.
Slack's legitimate infrastructure allowed attackers to blend malicious traffic with legitimate business communications, complicating detection and response efforts.

Signal and WhatsApp for Covert Communication:

Advanced persistent threat (APT) groups have reportedly adopted encrypted messaging applications like Signal and WhatsApp for secure, covert communication channels during espionage operations and targeted attacks.
Encryption provided by these platforms significantly hindered detection and forensic analysis.

Telegram-Based RATs and Infostealers:

Malware variants such as Masad Stealer and TelegramRAT have leveraged Telegram APIs for command-and-control communications, data exfiltration, and remote command execution.
Attackers benefited from Telegram's ease of use, encryption, and widespread adoption, increasing the effectiveness of their campaigns.