Exfiltration to Cloud Storage

Exfiltration to Cloud Storage [T1567.002]

Information

Name: Exfiltration to Cloud Storage
ID: T1567.002
Tactics:
Technique:

Introduction

Exfiltration to Cloud Storage [T1567.002] is a sub-technique within the MITRE ATT&CK framework that involves adversaries transferring stolen data from compromised systems to cloud storage services. Attackers leverage legitimate cloud platforms such as Amazon Web Services (AWS), Google Cloud Storage, Dropbox, Microsoft Azure, and other cloud providers to store exfiltrated data. This technique enables adversaries to conceal their activities within normal traffic, complicating detection and response efforts.

Deep Dive Into Technique

Adversaries commonly utilize legitimate cloud storage providers to exfiltrate sensitive data due to ease of use, availability, scalability, and the ability to blend in with normal network traffic. Technical methods and mechanisms typically include:

Cloud APIs and SDKs: Attackers may use provider-specific APIs or software development kits (SDKs) to automate data uploads directly from compromised hosts or through intermediate command-and-control (C2) servers.
Command-Line Tools and Scripts: Attackers frequently employ native command-line utilities (e.g., AWS CLI, Azure CLI, gsutil for Google Cloud Storage) or custom scripts to upload data to cloud storage buckets.
Web-based Uploads: Adversaries may manually or automatically upload data via web interfaces provided by cloud storage services, often using stolen or compromised credentials.
Encryption and Obfuscation: Attackers frequently encrypt or obfuscate data before uploading to cloud storage to evade detection by data loss prevention (DLP) tools or network monitoring solutions.
Use of Stolen or Compromised Credentials: Attackers may use stolen credentials, API keys, tokens, or OAuth tokens to authenticate to cloud storage providers, making detection more difficult because activities appear legitimate.
Scheduled Tasks and Automation: Attackers may set up scheduled tasks or cron jobs on compromised systems to regularly upload data to cloud storage providers, ensuring continuous exfiltration.
Proxying and Redirection: Attackers might route data through multiple compromised hosts or proxies before uploading to cloud storage, further obscuring their origin.

When this Technique is Usually Used

This sub-technique commonly appears in the following attack scenarios and stages:

Data Exfiltration Stage: After attackers have successfully gained initial access, escalated privileges, and collected sensitive information, they typically exfiltrate data to cloud storage services.
Advanced Persistent Threat (APT) Operations: Nation-state-sponsored threat actors frequently leverage cloud storage providers to exfiltrate sensitive intellectual property, classified information, or strategic data.
Cyber Espionage Campaigns: Attackers targeting specific sectors (government, finance, healthcare, technology) regularly use cloud storage platforms to transfer stolen information.
Financially Motivated Attacks: Attackers performing ransomware or extortion attacks may exfiltrate sensitive data to cloud storage platforms as leverage to demand ransom payments.
Insider Threat Scenarios: Malicious insiders may use personal cloud storage accounts or third-party cloud providers to transfer sensitive data out of the organization.
Supply Chain Attacks: Adversaries compromising third-party vendors may exfiltrate sensitive information from victims to cloud storage services for later retrieval.

How this Technique is Usually Detected

Detection methods, tools, and indicators of compromise (IoCs) for exfiltration to cloud storage include:

Network Traffic Monitoring and Analysis:
- Identify unusual or significant data transfers to known cloud storage provider IP ranges or domains (e.g., AWS S3, Azure Blob Storage, Google Cloud Storage).
- Monitor for outbound HTTPS connections to cloud storage endpoints from hosts that typically do not communicate externally.
Endpoint Detection and Response (EDR):
- Detect processes or command-line utilities (e.g., awscli, gsutil, azcopy) executed from unusual locations or by unexpected users.
- Monitor file system activities for unusual archiving or encryption of files prior to upload.
Data Loss Prevention (DLP) Solutions:
- Configure DLP policies to identify sensitive data uploads to unauthorized or suspicious cloud storage providers.
- Detect encrypted or compressed files containing sensitive data being uploaded.
Cloud Access Security Brokers (CASB):
- Monitor cloud service usage and detect unauthorized cloud storage providers or unusual access patterns.
- Identify anomalous login attempts or use of compromised credentials.
Authentication and Access Logs:
- Review cloud storage provider logs for unusual access patterns, uploads from unfamiliar IP addresses, or abnormal account behavior.
- Monitor for authentication from unexpected geographical locations or at unusual times.
Indicators of Compromise (IoCs):
- Presence of cloud storage CLI tools (e.g., awscli, azcopy, gsutil) on endpoints without legitimate business need.
- Suspicious scheduled tasks or cron jobs running scripts that upload data to cloud storage.
- Unusual API calls or uploads to cloud storage providers detected in firewall or proxy logs.
- Unusual outbound data volume spikes or persistent connections to cloud storage domains.

Why it is Important to Detect This Technique

Early detection of exfiltration to cloud storage is critical due to the significant impacts on systems, networks, and organizational assets, including:

Data Loss and Intellectual Property Theft: Attackers may exfiltrate sensitive, proprietary, or confidential information, causing severe financial loss, competitive disadvantage, or reputational damage.
Regulatory and Compliance Violations: Unauthorized data exfiltration may expose organizations to regulatory fines, legal actions, and compliance violations (e.g., GDPR, HIPAA, PCI DSS).
Operational Disruption: Data exfiltration events often lead to operational disruptions, incident response efforts, and costly recovery processes.
Ransomware and Extortion Risks: Attackers may leverage exfiltrated data for extortion, demanding ransom payments to avoid public disclosure or sale of sensitive data.
Difficulty in Attribution and Response: Cloud storage exfiltration complicates attribution, as attackers leverage legitimate cloud services, making it challenging to differentiate malicious activities from genuine business operations.
Insider Threat Mitigation: Early detection helps identify and mitigate insider threats, preventing further loss or damage.
Reducing Attacker Dwell Time: Early detection significantly reduces attacker dwell time, limiting the scope of compromise and minimizing damage.

Examples

Real-world examples involving exfiltration to cloud storage include:

APT10 (Cloud Hopper Campaign):
- Attack Scenario: APT10 compromised managed service providers (MSPs) and their clients, exfiltrating sensitive data via cloud storage providers.
- Tools and Techniques: Leveraged legitimate cloud storage services to upload stolen intellectual property and sensitive data.
- Impact: Significant intellectual property theft, financial loss, and reputational damage to multiple global organizations.
FIN7 Cybercrime Group:
- Attack Scenario: FIN7 targeted retail and hospitality sectors, exfiltrating payment card data and customer information to cloud storage platforms.
- Tools and Techniques: Used scripts and command-line utilities to automate data uploads to AWS and Google Cloud Storage.
- Impact: Millions of payment card records compromised, financial losses, regulatory fines, and reputational damage.
DarkSide Ransomware Attacks:
- Attack Scenario: DarkSide operators exfiltrated sensitive data from victims to cloud storage services before encrypting systems, using data for extortion.
- Tools and Techniques: Utilized cloud storage APIs and command-line tools to upload data, encrypted files before transmission.
- Impact: Severe operational disruption, ransom payments, data leaks, and reputational damage.
Insider Threat Case (Tesla Incident, 2018):
- Attack Scenario: Malicious insider exfiltrated proprietary data from Tesla to personal cloud storage accounts.
- Tools and Techniques: Used personal cloud storage accounts and automation scripts to transfer sensitive data.
- Impact: Intellectual property theft, legal actions, and reputational harm.
Operation Aurora (Google Incident, 2010):
- Attack Scenario: Attackers targeted Google and other technology companies, exfiltrating sensitive data to external cloud storage services.
- Tools and Techniques: Leveraged custom malware and automated scripts to upload data to cloud storage.
- Impact: Intellectual property theft, significant security enhancements across affected organizations, and heightened awareness of cloud exfiltration threats.

Last updated 1 month ago

Introduction

Deep Dive Into Technique

Cloud APIs and SDKs: Attackers may use provider-specific APIs or software development kits (SDKs) to automate data uploads directly from compromised hosts or through intermediate command-and-control (C2) servers.

Command-Line Tools and Scripts: Attackers frequently employ native command-line utilities (e.g., AWS CLI, Azure CLI, gsutil for Google Cloud Storage) or custom scripts to upload data to cloud storage buckets.

Web-based Uploads: Adversaries may manually or automatically upload data via web interfaces provided by cloud storage services, often using stolen or compromised credentials.

Encryption and Obfuscation: Attackers frequently encrypt or obfuscate data before uploading to cloud storage to evade detection by data loss prevention (DLP) tools or network monitoring solutions.

Use of Stolen or Compromised Credentials: Attackers may use stolen credentials, API keys, tokens, or OAuth tokens to authenticate to cloud storage providers, making detection more difficult because activities appear legitimate.

Scheduled Tasks and Automation: Attackers may set up scheduled tasks or cron jobs on compromised systems to regularly upload data to cloud storage providers, ensuring continuous exfiltration.

Proxying and Redirection: Attackers might route data through multiple compromised hosts or proxies before uploading to cloud storage, further obscuring their origin.

When this Technique is Usually Used

This sub-technique commonly appears in the following attack scenarios and stages:

Data Exfiltration Stage: After attackers have successfully gained initial access, escalated privileges, and collected sensitive information, they typically exfiltrate data to cloud storage services.

Advanced Persistent Threat (APT) Operations: Nation-state-sponsored threat actors frequently leverage cloud storage providers to exfiltrate sensitive intellectual property, classified information, or strategic data.

Cyber Espionage Campaigns: Attackers targeting specific sectors (government, finance, healthcare, technology) regularly use cloud storage platforms to transfer stolen information.

Financially Motivated Attacks: Attackers performing ransomware or extortion attacks may exfiltrate sensitive data to cloud storage platforms as leverage to demand ransom payments.

Insider Threat Scenarios: Malicious insiders may use personal cloud storage accounts or third-party cloud providers to transfer sensitive data out of the organization.

Supply Chain Attacks: Adversaries compromising third-party vendors may exfiltrate sensitive information from victims to cloud storage services for later retrieval.

How this Technique is Usually Detected

Detection methods, tools, and indicators of compromise (IoCs) for exfiltration to cloud storage include:

Network Traffic Monitoring and Analysis:

Identify unusual or significant data transfers to known cloud storage provider IP ranges or domains (e.g., AWS S3, Azure Blob Storage, Google Cloud Storage).
Monitor for outbound HTTPS connections to cloud storage endpoints from hosts that typically do not communicate externally.

Endpoint Detection and Response (EDR):

Detect processes or command-line utilities (e.g., awscli, gsutil, azcopy) executed from unusual locations or by unexpected users.
Monitor file system activities for unusual archiving or encryption of files prior to upload.

Data Loss Prevention (DLP) Solutions:

Configure DLP policies to identify sensitive data uploads to unauthorized or suspicious cloud storage providers.
Detect encrypted or compressed files containing sensitive data being uploaded.

Cloud Access Security Brokers (CASB):

Monitor cloud service usage and detect unauthorized cloud storage providers or unusual access patterns.
Identify anomalous login attempts or use of compromised credentials.

Authentication and Access Logs:

Review cloud storage provider logs for unusual access patterns, uploads from unfamiliar IP addresses, or abnormal account behavior.
Monitor for authentication from unexpected geographical locations or at unusual times.

Indicators of Compromise (IoCs):

Presence of cloud storage CLI tools (e.g., awscli, azcopy, gsutil) on endpoints without legitimate business need.
Suspicious scheduled tasks or cron jobs running scripts that upload data to cloud storage.
Unusual API calls or uploads to cloud storage providers detected in firewall or proxy logs.
Unusual outbound data volume spikes or persistent connections to cloud storage domains.

Why it is Important to Detect This Technique

Early detection of exfiltration to cloud storage is critical due to the significant impacts on systems, networks, and organizational assets, including:

Data Loss and Intellectual Property Theft: Attackers may exfiltrate sensitive, proprietary, or confidential information, causing severe financial loss, competitive disadvantage, or reputational damage.

Regulatory and Compliance Violations: Unauthorized data exfiltration may expose organizations to regulatory fines, legal actions, and compliance violations (e.g., GDPR, HIPAA, PCI DSS).

Operational Disruption: Data exfiltration events often lead to operational disruptions, incident response efforts, and costly recovery processes.

Ransomware and Extortion Risks: Attackers may leverage exfiltrated data for extortion, demanding ransom payments to avoid public disclosure or sale of sensitive data.

Difficulty in Attribution and Response: Cloud storage exfiltration complicates attribution, as attackers leverage legitimate cloud services, making it challenging to differentiate malicious activities from genuine business operations.

Insider Threat Mitigation: Early detection helps identify and mitigate insider threats, preventing further loss or damage.

Reducing Attacker Dwell Time: Early detection significantly reduces attacker dwell time, limiting the scope of compromise and minimizing damage.

Examples

Real-world examples involving exfiltration to cloud storage include:

APT10 (Cloud Hopper Campaign):

Attack Scenario: APT10 compromised managed service providers (MSPs) and their clients, exfiltrating sensitive data via cloud storage providers.
Tools and Techniques: Leveraged legitimate cloud storage services to upload stolen intellectual property and sensitive data.
Impact: Significant intellectual property theft, financial loss, and reputational damage to multiple global organizations.

FIN7 Cybercrime Group:

Attack Scenario: FIN7 targeted retail and hospitality sectors, exfiltrating payment card data and customer information to cloud storage platforms.
Tools and Techniques: Used scripts and command-line utilities to automate data uploads to AWS and Google Cloud Storage.
Impact: Millions of payment card records compromised, financial losses, regulatory fines, and reputational damage.

DarkSide Ransomware Attacks:

Attack Scenario: DarkSide operators exfiltrated sensitive data from victims to cloud storage services before encrypting systems, using data for extortion.
Tools and Techniques: Utilized cloud storage APIs and command-line tools to upload data, encrypted files before transmission.
Impact: Severe operational disruption, ransom payments, data leaks, and reputational damage.

Insider Threat Case (Tesla Incident, 2018):

Attack Scenario: Malicious insider exfiltrated proprietary data from Tesla to personal cloud storage accounts.
Tools and Techniques: Used personal cloud storage accounts and automation scripts to transfer sensitive data.
Impact: Intellectual property theft, legal actions, and reputational harm.

Operation Aurora (Google Incident, 2010):

Attack Scenario: Attackers targeted Google and other technology companies, exfiltrating sensitive data to external cloud storage services.
Tools and Techniques: Leveraged custom malware and automated scripts to upload data to cloud storage.
Impact: Intellectual property theft, significant security enhancements across affected organizations, and heightened awareness of cloud exfiltration threats.