Adversaries may exfiltrate data by transferring the data, including through sharing/syncing and creating backups of cloud environments, to another cloud account they control on the same service. A defender who is monitoring for large transfers to outside the cloud environment through normal file transfers or over command and control channels may not be watching for data transfers to another account within the same cloud provider. Such transfers may utilize existing cloud provider APIs and the internal address space of the cloud provider to blend into normal traffic or avoid data transfers over external network interfaces.(Citation: TLDRSec AWS Attacks) Adversaries may also use cloud-native mechanisms to share victim data with adversary-controlled cloud accounts, such as creating anonymous file sharing links or, in Azure, a shared access signature (SAS) URI.(Citation: Microsoft Azure Storage Shared Access Signature) Incidents have been observed where adversaries have created backups of cloud instances and transferred them to separate accounts.(Citation: DOJ GRU Indictment Jul 2018)
Data Loss Prevention (DLP) involves implementing strategies and technologies to identify, categorize, monitor, and control the movement of sensitive data within an organization. This includes protecting data formats indicative of Personally Identifiable Information (PII), intellectual property, or financial data from unauthorized access, transmission, or exfiltration. DLP solutions integrate with network, endpoint, and cloud platforms to enforce security policies and prevent accidental or malicious data leaks. (Citation: PurpleSec Data Loss Prevention) This mitigation can be implemented through the following measures: Sensitive Data Categorization: - Use Case: Identify and classify data based on sensitivity (e.g., PII, financial data, trade secrets). - Implementation: Use DLP solutions to scan and tag files containing sensitive information using predefined patterns, such as Social Security Numbers or credit card details. Exfiltration Restrictions: - Use Case: Prevent unauthorized transmission of sensitive data. - Implementation: Enforce policies to block unapproved email attachments, unauthorized USB usage, or unencrypted data uploads to cloud storage. Data-in-Transit Monitoring: - Use Case: Detect and prevent the transmission of sensitive data over unapproved channels. - Implementation: Deploy network-based DLP tools to inspect outbound traffic for sensitive content (e.g., financial records or PII) and block unapproved transmissions. Endpoint Data Protection: - Use Case: Monitor and control sensitive data usage on endpoints. - Implementation: Use endpoint-based DLP agents to block copy-paste actions of sensitive data and unauthorized printing or file sharing. Cloud Data Security: - Use Case: Protect data stored in cloud platforms. - Implementation: Integrate DLP with cloud storage platforms like Google Drive, OneDrive, or AWS to monitor and restrict sensitive data sharing or downloads.
M1018User Account ManagementUser Account Management involves implementing and enforcing policies for the lifecycle of user accounts, including creation, modification, and deactivation. Proper account management reduces the attack surface by limiting unauthorized access, managing account privileges, and ensuring accounts are used according to organizational policies. This mitigation can be implemented through the following measures: Enforcing the Principle of Least Privilege - Implementation: Assign users only the minimum permissions required to perform their job functions. Regularly audit accounts to ensure no excess permissions are granted. - Use Case: Reduces the risk of privilege escalation by ensuring accounts cannot perform unauthorized actions. Implementing Strong Password Policies - Implementation: Enforce password complexity requirements (e.g., length, character types). Require password expiration every 90 days and disallow password reuse. - Use Case: Prevents adversaries from gaining unauthorized access through password guessing or brute force attacks. Managing Dormant and Orphaned Accounts - Implementation: Implement automated workflows to disable accounts after a set period of inactivity (e.g., 30 days). Remove orphaned accounts (e.g., accounts without an assigned owner) during regular account audits. - Use Case: Eliminates dormant accounts that could be exploited by attackers. Account Lockout Policies - Implementation: Configure account lockout thresholds (e.g., lock accounts after five failed login attempts). Set lockout durations to a minimum of 15 minutes. - Use Case: Mitigates automated attack techniques that rely on repeated login attempts. Multi-Factor Authentication (MFA) for High-Risk Accounts - Implementation: Require MFA for all administrative accounts and high-risk users. Use MFA mechanisms like hardware tokens, authenticator apps, or biometrics. - Use Case: Prevents unauthorized access, even if credentials are stolen. Restricting Interactive Logins - Implementation: Restrict interactive logins for privileged accounts to specific secure systems or management consoles. Use group policies to enforce logon restrictions. - Use Case: Protects sensitive accounts from misuse or exploitation. *Tools for Implementation* Built-in Tools: - Microsoft Active Directory (AD): Centralized account management and RBAC enforcement. - Group Policy Object (GPO): Enforce password policies, logon restrictions, and account lockout policies. Identity and Access Management (IAM) Tools: - Okta: Centralized user provisioning, MFA, and SSO integration. - Microsoft Azure Active Directory: Provides advanced account lifecycle management, role-based access, and conditional access policies. Privileged Account Management (PAM): - CyberArk, BeyondTrust, Thycotic: Manage and monitor privileged account usage, enforce session recording, and JIT access.
M1054Software ConfigurationSoftware configuration refers to making security-focused adjustments to the settings of applications, middleware, databases, or other software to mitigate potential threats. These changes help reduce the attack surface, enforce best practices, and protect sensitive data. This mitigation can be implemented through the following measures: Conduct a Security Review of Application Settings: - Review the software documentation to identify recommended security configurations. - Compare default settings against organizational policies and compliance requirements. Implement Access Controls and Permissions: - Restrict access to sensitive features or data within the software. - Enforce least privilege principles for all roles and accounts interacting with the software. Enable Logging and Monitoring: - Configure detailed logging for key application events such as authentication failures, configuration changes, or unusual activity. - Integrate logs with a centralized monitoring solution, such as a SIEM. Update and Patch Software Regularly: - Ensure the software is kept up-to-date with the latest security patches to address known vulnerabilities. - Use automated patch management tools to streamline the update process. Disable Unnecessary Features or Services: - Turn off unused functionality or components that could introduce vulnerabilities, such as debugging interfaces or deprecated APIs. Test Configuration Changes: - Perform configuration changes in a staging environment before applying them in production. - Conduct regular audits to ensure that settings remain aligned with security policies. *Tools for Implementation* Configuration Management Tools: - Ansible: Automates configuration changes across multiple applications and environments. - Chef: Ensures consistent application settings through code-based configuration management. - Puppet: Automates software configurations and audits changes for compliance. Security Benchmarking Tools: - CIS-CAT: Provides benchmarks and audits for secure software configurations. - Aqua Security Trivy: Scans containerized applications for configuration issues. Vulnerability Management Solutions: - Nessus: Identifies misconfigurations and suggests corrective actions. Logging and Monitoring Tools: - Splunk: Aggregates and analyzes application logs to detect suspicious activity.
M1037Filter Network TrafficEmploy network appliances and endpoint software to filter ingress, egress, and lateral network traffic. This includes protocol-based filtering, enforcing firewall rules, and blocking or restricting traffic based on predefined conditions to limit adversary movement and data exfiltration. This mitigation can be implemented through the following measures: Ingress Traffic Filtering: - Use Case: Configure network firewalls to allow traffic only from authorized IP addresses to public-facing servers. - Implementation: Limit SSH (port 22) and RDP (port 3389) traffic to specific IP ranges. Egress Traffic Filtering: - Use Case: Use firewalls or endpoint security software to block unauthorized outbound traffic to prevent data exfiltration and command-and-control (C2) communications. - Implementation: Block outbound traffic to known malicious IPs or regions where communication is unexpected. Protocol-Based Filtering: - Use Case: Restrict the use of specific protocols that are commonly abused by adversaries, such as SMB, RPC, or Telnet, based on business needs. - Implementation: Disable SMBv1 on endpoints to prevent exploits like EternalBlue. Network Segmentation: - Use Case: Create network segments for critical systems and restrict communication between segments unless explicitly authorized. - Implementation: Implement VLANs to isolate IoT devices or guest networks from core business systems. Application Layer Filtering: - Use Case: Use proxy servers or Web Application Firewalls (WAFs) to inspect and block malicious HTTP/S traffic. - Implementation: Configure a WAF to block SQL injection attempts or other web application exploitation techniques.
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