Remote Data Staging
Remote Data Staging [T1074.002]
Last updated
Remote Data Staging [T1074.002]
Last updated
Name: Remote Data Staging
ID: T1074.002
Tactics:
Technique:
Remote Data Staging (T1074.002) is a sub-technique within MITRE ATT&CK's "Data Staged" technique (T1074), which involves adversaries temporarily placing collected data in remote locations before exfiltration. Attackers often stage data remotely to evade detection, minimize direct connections between compromised hosts and attacker infrastructure, and facilitate data exfiltration at a later, more convenient time. This sub-technique specifically focuses on staging data on remote systems or cloud storage services, rather than locally on compromised hosts.
Remote Data Staging involves attackers temporarily storing stolen data on remote systems or cloud-based storage platforms to facilitate later exfiltration. Attackers typically perform the following steps:
Data Collection and Aggregation:
Adversaries first identify and collect valuable data from compromised hosts or networks.
Data is often compressed or encrypted to reduce size and obfuscate content.
Remote Storage Selection:
Attackers select remote storage locations, which could include:
Compromised third-party servers.
Cloud storage services (e.g., Dropbox, Google Drive, AWS S3, Azure Blob Storage).
Attacker-controlled infrastructure hosted by cloud providers or compromised infrastructure.
Data Transfer and Staging:
Attackers transfer the collected data to remote staging locations using various protocols and methods, including:
FTP/SFTP/SCP.
HTTP/HTTPS POST requests.
Cloud API calls (e.g., AWS CLI, Azure CLI).
Remote desktop or SSH sessions.
Data may be stored temporarily to avoid immediate detection or to wait for optimal exfiltration windows.
Data Exfiltration:
After staging, attackers typically perform final exfiltration from the remote staging location to their controlled infrastructure at a later time.
This method reduces the risk of detection by limiting direct communication between compromised hosts and attacker-controlled external infrastructure.
Attackers may also leverage legitimate cloud platforms and services to blend malicious traffic with regular business activities, making detection more challenging.
Remote Data Staging commonly occurs during the following attack scenarios and stages:
Data Exfiltration Stage:
Attackers use remote staging as a preliminary step before final exfiltration to evade detection.
Advanced Persistent Threat (APT) Operations:
State-sponsored threat actors commonly leverage remote staging to obscure operational infrastructure and maintain stealth.
Ransomware Attacks:
Attackers may stage sensitive data remotely to threaten data leaks and increase ransom demands.
Cyber Espionage Campaigns:
Espionage-focused attackers stage sensitive intellectual property or classified data remotely to minimize detection risks.
Supply Chain Attacks:
Attackers exploit trusted third-party infrastructure or cloud services to stage data remotely, further complicating attribution and detection efforts.
Detecting Remote Data Staging requires monitoring multiple aspects of network and endpoint behavior, including:
Network Traffic Analysis:
Monitor outbound network connections to uncommon cloud storage platforms or unknown external IP addresses.
Detect unusual data transfers via FTP, SCP, HTTP(S), or cloud APIs.
Endpoint Detection and Response (EDR):
Identify unusual processes or scripts initiating network connections to remote storage services.
Monitor file system activity for suspicious data compression or encryption before transmission.
Cloud Service Monitoring:
Audit cloud storage access logs for unusual API calls or access from unfamiliar IP addresses or clients.
Implement anomaly detection tools to identify abnormal upload/download patterns.
Data Loss Prevention (DLP) Solutions:
Deploy DLP tools to detect and alert on sensitive data transfers to unauthorized external locations.
Indicators of Compromise (IoCs):
Suspicious domain names, IP addresses, or URLs associated with known attacker infrastructure or cloud services.
Unusual user-agent strings or API access patterns.
Abnormal spikes in outbound network traffic volume or frequency.
Early detection of Remote Data Staging is critical due to the following potential impacts on systems and networks:
Sensitive Data Loss:
Undetected remote staging can lead to significant financial, intellectual property, or reputational losses.
Operational Disruption:
Attackers staging data remotely may disrupt normal business operations or degrade network performance.
Regulatory and Compliance Risks:
Data breaches involving personally identifiable information (PII), protected health information (PHI), or financial data can lead to severe regulatory penalties and compliance issues.
Increased Difficulty in Attribution and Response:
Remote staging complicates incident response and attribution efforts, making it more challenging to identify attackers and remediate breaches.
Potential Escalation of Attack Severity:
Attackers who successfully stage data remotely may escalate their operations, expanding their foothold and increasing the severity of the breach.
Detecting this technique early allows organizations to quickly contain threats, mitigate damage, and reduce the overall impact of data breaches.
Real-world examples and attack scenarios involving Remote Data Staging include:
APT29 (Cozy Bear):
This Russian state-sponsored actor has used cloud storage platforms to temporarily stage stolen data before exfiltration, leveraging public cloud providers to blend in with legitimate network traffic.
Tools used: Custom malware, cloud storage APIs, encrypted HTTP POST requests.
Impact: Exfiltration of sensitive government and diplomatic data.
Cloud Hopper Campaign (APT10):
APT10, a Chinese state-sponsored group, compromised Managed Service Providers (MSPs) and staged sensitive data remotely on cloud infrastructure before exfiltration.
Tools used: Remote Access Trojans (RATs), compromised MSP infrastructure, cloud storage services.
Impact: Theft of intellectual property, trade secrets, and sensitive business data from multiple global organizations.
DarkSide Ransomware Attacks:
DarkSide ransomware operators staged stolen data remotely on attacker-controlled cloud infrastructure, threatening victims with data leaks to increase ransom demands.
Tools used: Custom ransomware, cloud storage APIs, encrypted file transfers.
Impact: Significant financial losses, operational disruptions, reputation damage to victim organizations.
FIN7 Cybercrime Group:
FIN7 staged stolen payment card data remotely on compromised third-party servers and cloud services before exfiltration.
Tools used: Carbanak malware, compromised cloud servers, encrypted FTP transfers.
Impact: Large-scale theft of payment card data, significant financial and reputational damage to affected businesses.
These real-world examples illustrate the diverse methods attackers use to remotely stage data, highlighting the importance of robust detection and response capabilities.