Implant Internal Image
Implant Internal Image [T1525]
Information
Name: Implant Internal Image
ID: T1525
Tactics: TA0003
Introduction
Implant Internal Image is a sub-technique within the MITRE ATT&CK framework (Technique T1525.001), categorized under the broader technique of Implant Container Image. Attackers leverage this method by embedding malicious code or backdoors directly into container images, which are then deployed internally within the victim organization's infrastructure. This technique allows attackers to achieve persistence, maintain stealth, and facilitate lateral movement, all while evading traditional detection mechanisms.
Deep Dive Into Technique
Attackers employing the Implant Internal Image technique typically follow these steps:
Image Compromise: Attackers gain initial access to internal container registries or build pipelines, often through compromised credentials, vulnerabilities in CI/CD tools, or by exploiting misconfigured registries.
Embedding Malicious Payloads: Once access is obtained, attackers embed malicious payloads, backdoors, or scripts into container images. Common methods include:
Injecting malicious binaries or scripts into the container filesystem.
Modifying entrypoint scripts or runtime configurations to execute malicious payloads upon container startup.
Altering legitimate binaries within the image to include malicious functionality.
Deployment and Execution: The compromised container images are then deployed internally, either automatically through CI/CD pipelines or manually by unsuspecting administrators. Once deployed, the malicious payload executes, allowing attackers to:
Gain persistent access.
Perform lateral movement within the containerized environment.
Exfiltrate sensitive data.
Establish command and control (C2) communication.
Technical characteristics and mechanisms involved include:
Container Registries: Attackers target internal registries such as Docker Registry, Harbor, Azure Container Registry, Amazon ECR, or Google Container Registry.
CI/CD Pipelines: Exploitation or manipulation of tools like Jenkins, GitLab CI/CD, GitHub Actions, or Azure DevOps pipelines.
Payload Obfuscation: Attackers may obfuscate malicious payloads or scripts to evade detection by static analysis and scanning tools.
Persistence Mechanisms: Malicious payloads often include persistence mechanisms like cron jobs, systemd services, or modified entrypoint scripts.
When this Technique is Usually Used
Attackers typically leverage the Implant Internal Image technique during various stages of the attack lifecycle, including:
Persistence Stage: Embedding malicious payloads into container images helps attackers maintain persistent access even after initial compromise vectors are remediated.
Privilege Escalation and Lateral Movement: Once attackers gain initial footholds, compromised container images facilitate lateral movement across containerized environments and cloud infrastructures.
Supply Chain Attacks: Attackers targeting internal software supply chains embed malicious code into internal images, affecting multiple deployments and environments simultaneously.
Reconnaissance and Data Exfiltration: Malicious images may contain tools for network reconnaissance, credential harvesting, or data exfiltration, enabling attackers to expand their foothold and extract valuable information.
Common scenarios include:
Attacks against enterprises heavily reliant on containerized applications and microservices architectures.
Organizations using automated CI/CD pipelines with minimal security controls.
Environments with insufficient monitoring or scanning of internal container registries and images.
How this Technique is Usually Detected
Organizations can detect Implant Internal Image techniques through a combination of security controls, monitoring tools, and best practices:
Container Image Scanning:
Static analysis tools (e.g., Clair, Trivy, Anchore) to detect malicious payloads, vulnerabilities, or unauthorized changes in container images.
Dynamic analysis and sandboxing of container images prior to deployment to detect malicious behaviors.
Registry Monitoring & Auditing:
Regular auditing and monitoring of internal container registries to detect unauthorized image modifications or uploads.
Implementing registry access controls and logging to monitor suspicious activities and unauthorized access attempts.
Runtime Detection & Monitoring:
Container runtime security tools (e.g., Falco, Aqua Security, Sysdig Secure) to monitor container behavior, detect anomalous activities, and alert on suspicious execution patterns.
Network monitoring and intrusion detection systems (IDS/IPS) to detect unexpected outbound communication or command-and-control traffic from containers.
Indicators of Compromise (IoCs):
Unusual network connections from containerized workloads to external IP addresses or domains.
Suspicious processes or binaries running inside containers.
Unauthorized modifications to entrypoint scripts, binaries, or configuration files within container images.
Unexpected or anomalous image tags, layers, or metadata in container registries.
Why it is Important to Detect This Technique
Early detection of Implant Internal Image techniques is critical due to potential significant impacts on systems and networks, including:
Persistence & Stealth: Malicious images grant attackers persistent footholds within containerized infrastructures, making remediation challenging and potentially causing long-term compromise.
Lateral Movement & Privilege Escalation: Attackers can leverage compromised container images to move laterally across environments, escalate privileges, and expand their attack footprint.
Data Breaches & Exfiltration: Malicious containers facilitate unauthorized access to sensitive data, leading to data breaches, intellectual property theft, or regulatory compliance violations.
Service Disruption & Operational Impact: Compromised container workloads may cause service disruptions, downtime, or degraded performance, negatively impacting business operations and reputation.
Supply Chain Risks: Compromised internal images can propagate malicious payloads across multiple environments, amplifying the scope and severity of an attack.
Therefore, proactive detection and rapid response to compromised container images significantly reduce the risk of severe consequences and minimize operational disruption.
Examples
Real-world examples of Implant Internal Image attacks include:
SolarWinds Supply Chain Attack (2020):
Attackers compromised build environments and injected malicious code into legitimate software updates.
Malicious payload ("SUNBURST") embedded within software updates provided persistent backdoors.
Impact: Extensive compromise of multiple government and private sector organizations, data exfiltration, and long-term espionage.
Codecov Bash Uploader Compromise (2021):
Attackers modified the Codecov Bash Uploader script used in CI/CD pipelines, embedding malicious code.
Compromised CI/CD processes allowed attackers to exfiltrate sensitive environment variables, credentials, and source code.
Impact: Potential exposure of sensitive data for numerous companies using Codecov tools.
Docker Hub Breach (2019):
Attackers gained unauthorized access to Docker Hub repositories, potentially modifying container images.
Organizations using compromised images faced risks of deploying malicious containers internally.
Impact: Risk of persistent compromise, lateral movement, and data exfiltration for organizations relying on affected images.
Tools commonly used by attackers in Implant Internal Image scenarios:
Malicious payload injection tools: Custom scripts or binaries to modify container images, inject backdoors, or embed malicious code.
Credential harvesting tools: Scripts or binaries embedded in images to extract sensitive credentials or tokens from containerized workloads.
Command-and-Control frameworks: Tools like Cobalt Strike, Empire, or custom C2 frameworks embedded within container images to establish persistent communication channels.
Understanding these real-world examples, tools, and impacts helps organizations strengthen their defenses and detection capabilities against Implant Internal Image attacks.
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