Data from Network Shared Drive

Data from Network Shared Drive [T1039]

Information

  • Name: Data from Network Shared Drive

  • ID: T1039

  • Tactics: TA0009

Introduction

In the MITRE ATT&CK framework, adversaries may leverage data stored on network shared drives to access, exfiltrate, or manipulate sensitive information. This technique, identified as T1039 ("Data from Network Shared Drive"), involves attackers targeting shared network resources to achieve their objectives, such as obtaining credentials, intellectual property, or other sensitive organizational data. The prevalence of network shares in enterprise environments makes this technique particularly attractive to threat actors, as it allows them to exploit legitimate network functionalities for malicious purposes.

Deep Dive Into Technique

Adversaries exploiting data from network shared drives typically utilize legitimate network protocols such as SMB (Server Message Block), CIFS (Common Internet File System), or NFS (Network File System) to access shared resources. Attackers may employ multiple methods to achieve their objectives:

  • Credential Theft and Abuse:

    • Attackers often use compromised or stolen credentials to authenticate to network shares.

    • Credential dumping tools (e.g., Mimikatz) can facilitate access to network shares by providing valid credentials.

  • Enumeration of Network Shares:

    • Attackers scan the network to identify accessible shared drives.

    • Tools such as PowerSploit, BloodHound, or built-in operating system commands (net view, net use, smbclient) may be used for enumeration.

  • Data Exfiltration:

    • Once access is established, adversaries may copy or transfer sensitive information from the shared drive to external locations.

    • Data can be exfiltrated through encrypted channels, cloud storage services, or even by leveraging legitimate file transfer utilities.

  • Data Manipulation or Destruction:

    • Attackers may modify, delete, or corrupt files stored on network shares to disrupt operations or cover their tracks.

    • Ransomware frequently targets network shares to encrypt data, thereby maximizing impact and potential ransom payments.

When this Technique is Usually Used

Adversaries typically leverage data from network shared drives during various stages of an attack lifecycle, including:

  • Initial Reconnaissance:

    • Identifying valuable data stored on accessible network shares to plan further attacks.

  • Lateral Movement:

    • Using credentials to access additional network shares and systems to expand the scope of the attack.

  • Collection and Exfiltration:

    • Gathering sensitive data from network shares as part of espionage, intellectual property theft, or financial gain.

  • Impact Stage:

    • Deploying ransomware or destructive malware to encrypt or destroy data stored on network shares, causing operational disruption.

Common attack scenarios include:

  • Insider threats accessing shared drives to steal or leak sensitive information.

  • Advanced Persistent Threat (APT) groups conducting espionage operations by targeting network-shared intellectual property.

  • Criminal groups deploying ransomware to encrypt data on network shares, maximizing the affected systems and data.

How this Technique is Usually Detected

Detection of unauthorized or malicious access to network shared drives involves monitoring, analysis, and alerting on suspicious activities. Detection methods include:

  • Audit and Event Logging:

    • Monitoring access logs for unusual patterns, failed authentication attempts, and unexpected user behaviors.

    • Windows Event Logs (Event IDs 5140, 5145) and SMB audit logs can highlight suspicious accesses.

  • Network Traffic Analysis:

    • Tools (e.g., Wireshark, Zeek, Suricata) to analyze SMB/NFS traffic for anomalous connections or data transfers.

    • Monitoring for large or unusual file transfers from network shares to external IP addresses or uncommon internal hosts.

  • Endpoint Detection and Response (EDR):

    • EDR tools (CrowdStrike Falcon, Microsoft Defender for Endpoint, SentinelOne) can detect suspicious file access patterns, credential misuse, or unusual processes accessing network shares.

  • Behavioral Analytics and SIEM Solutions:

    • Security Information and Event Management (SIEM) systems (Splunk, IBM QRadar, Elastic Security) correlate events to detect anomalies and alert security teams.

    • User and Entity Behavior Analytics (UEBA) can detect deviations from normal user behavior, such as accessing unusual network shares or accessing data outside typical working hours.

Indicators of Compromise (IoCs):

  • Unusual SMB/NFS traffic patterns (high volume, irregular timings, external IP connections).

  • Access attempts from unexpected or unauthorized user accounts.

  • Large data transfers from network shares to external IP addresses or cloud storage providers.

  • Suspicious scripts or tools (e.g., smbclient, PowerSploit, BloodHound) detected on endpoints or network devices.

Why it is Important to Detect This Technique

Detecting unauthorized access and malicious activities involving network shared drives is critical due to the potential severe impacts on organizations, including:

  • Data Breach and Intellectual Property Theft:

    • Unauthorized access can lead to loss of sensitive data, trade secrets, or protected intellectual property, causing significant financial and reputational damage.

  • Operational Disruption:

    • Attackers modifying or deleting critical files can disrupt business operations, resulting in downtime, loss of productivity, and financial losses.

  • Ransomware Attacks:

    • Network shares are prime targets for ransomware, as encrypting shared data can cripple multiple departments or even entire organizations simultaneously.

  • Compliance and Regulatory Violations:

    • Unauthorized access and data breaches involving network shares can result in regulatory fines, legal actions, and loss of customer trust.

  • Early Detection and Mitigation:

    • Timely detection allows security teams to respond swiftly, contain the incident, minimize damage, and prevent further lateral movement and escalation.

Examples

Real-world examples demonstrating the use and impact of data from network shared drives include:

  • WannaCry Ransomware (2017):

    • Attack Scenario: Exploited SMB vulnerabilities (EternalBlue) to propagate across network shares.

    • Tools Used: EternalBlue exploit, SMB protocol for lateral movement.

    • Impact: Over 200,000 computers affected globally, causing significant operational disruption and financial losses across multiple industries.

  • NotPetya Ransomware (2017):

    • Attack Scenario: Leveraged SMB shares to spread rapidly within internal networks, encrypting data and rendering systems unusable.

    • Tools Used: EternalBlue exploit, Mimikatz for credential harvesting, SMB protocols.

    • Impact: Massive operational disruption, estimated damages exceeding $10 billion globally, affecting major corporations like Maersk, FedEx, and Merck.

  • APT10 (Cloud Hopper) Espionage Campaign:

    • Attack Scenario: Targeted managed service providers (MSPs) and accessed network shares containing sensitive intellectual property and confidential client data.

    • Tools Used: Credential theft tools, custom malware, legitimate network protocols (SMB/CIFS).

    • Impact: Intellectual property theft, sensitive data exfiltration, and significant reputational damage to affected organizations and their clients.

  • Insider Threat Incident (Tesla, 2018):

    • Attack Scenario: Insider accessed internal network shares to steal confidential data and transferred it externally.

    • Tools Used: Legitimate user credentials, standard file transfer utilities.

    • Impact: Theft of proprietary information, potential competitive harm, internal investigations, and legal proceedings.

These cases illustrate the severity and variety of impacts adversaries can achieve by exploiting data from network shared drives, emphasizing the importance of proactive detection and robust security measures.

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