Container Runtime Threat Hunting Techniques for SOC Analysts

Container runtimes present unique challenges in cybersecurity that necessitate specialized threat hunting techniques.

Unlike traditional environments, containers operate differently due to their lightweight and ephemeral nature.

They can be rapidly deployed and dismantled, providing attackers with opportunities to exploit vulnerabilities quickly.

Standard security practices may not effectively address the complexities introduced by containerization, making it vital for security operations center (SOC) analysts to adopt focused threat hunting strategies.

Overview of adversary tactics in Kubernetes and Docker environments

Adversaries utilize a variety of tactics when targeting Kubernetes and Docker environments. Understanding these tactics is crucial for effective threat hunting.

Attackers often leverage weaknesses in these platforms to gain unauthorized access, escalate privileges, and move laterally within the environment.

This complexity underscores the importance of implementing vulnerability management best practices tailored specifically to container runtimes, equipping SOC analysts with the tools and techniques needed to effectively monitor and defend against evolving threat landscapes.

The Container Runtime Threat Landscape

Understanding the vulnerabilities within container runtimes is crucial for effective threat hunting.

This section outlines the primary attack surfaces and common techniques employed by adversaries to escape containers and move laterally within environments.

Attack surfaces: container engine, runtime shim, host kernel

The container runtime environment includes several attack surfaces that can be exploited by malicious actors.

Below are the key components and their associated vulnerabilities:

Each of these surfaces presents unique risks. An attacker may exploit a vulnerability in the container engine to issue commands that affect multiple containers.

A runtime shim vulnerability could allow an attacker to manipulate container behavior.

Conversely, a kernel-level vulnerability can provide direct access to the host system.

Typical escape and lateral movement techniques

Adversaries use various techniques to escape containers and traverse laterally through environments.

Understanding these methods helps security teams enhance their monitoring strategies.

Awareness of these techniques is essential for cybersecurity professionals tasked with vulnerability management.

Suggested mitigations may include regular security audits, patching known vulnerabilities, and continuous monitoring of container activity.

Identifying these behaviors early can significantly reduce the risk of security breaches.

Instrumentation and Data Sources

Effective threat hunting in container environments requires robust instrumentation and data sourcing.

By utilizing tools and techniques specifically designed for container runtimes, analysts can enhance their ability to detect and respond to potential threats.

Leveraging eBPF and Falco for syscall tracing

eBPF (extended Berkeley Packet Filter) and Falco can be leveraged for syscall tracing, providing visibility into container activities.

These tools allow analysts to monitor system calls and identify suspicious behavior in real time.

Parsing containerd and cri-o audit logs and gRPC streams

Parsing audit logs and gRPC streams from containerd and cri-o is essential for gathering insights into container operations.

These logs provide detailed records of container actions, which can be crucial for incident response and forensics.

Collecting cgroup, namespace, and LSM telemetry

Collecting telemetry data from cgroups (control groups), namespaces, and Linux Security Modules (LSM) is critical for monitoring resource allocation and access controls in containerized environments.

This data provides a comprehensive view of the system's state and can highlight security policy violations.

By harnessing these data sources and instrumentation techniques, cybersecurity professionals can better understand the threat landscape surrounding container runtimes and implement effective vulnerability management best practices.

Syscall-Level Threat Hunting

In the realm of cybersecurity, syscall-level threat hunting plays a critical role in identifying suspicious activities within containerized environments.

By monitoring system calls, analysts can detect unauthorized actions and potential compromises.

Two important areas of focus are the detection of anomalous execve, ptrace, and bpf syscalls, as well as identifying seccomp and capability violations.

Detecting anomalous execve ptrace and bpf syscalls

The execve syscall is commonly used to execute programs, and monitoring its usage can reveal abnormal behavior.

Ptrace is often employed for debugging and may be leveraged by malicious actors to manipulate processes.

Bpf syscalls can be indicative of attempts to hook or trace execution, which is a tactic often utilized during attacks.

Identifying seccomp and capability violations

Seccomp (secure computing mode) is a Linux kernel feature that restricts the system calls a process can make.

Analyzing seccomp violations can assist in detecting unauthorized attempts to bypass security controls.

Similarly, capability violations occur when processes attempt to perform actions outside their assigned privileges.

By closely monitoring these syscalls and their associated behaviors, cybersecurity professionals can enhance their vulnerability management strategies, ensuring that any deviations from the norm are promptly investigated and addressed.

Filesystem and Process Anomaly Detection

Effective detection of threats in containerized environments involves monitoring filesystem activities and process behaviors.

This section covers important techniques for identifying anomalies related to overlay filesystem structures, setuid/setgid binaries, and unexpected shell executions.

Monitoring overlayfs and union mount artifacts

Overlay filesystem (overlayfs) and union mounts are often used in container environments to manage layers of files.

While these technologies facilitate efficient storage management, they can be manipulated in malicious ways.

Monitoring overlayfs artifacts helps identify unauthorized changes or suspicious file modifications that could signal an intrusion.

To effectively monitor these artifacts, one should focus on:

• Changes in filesystem metadata
• Unexpected file creation or deletion
• Modifications to critical binaries or scripts

Hunting setuid setgid binaries within container layers

Setuid and setgid bits on binaries can allow processes to execute with elevated permissions, posing a significant security risk in containerized systems.

Monitoring for these types of files is crucial, as they can be used by attackers to escalate privileges within a container.

When hunting for setuid and setgid binaries, it is important to:

• Regularly scan container images for sensitive files
• Identify any unauthorized binaries with elevated permissions
• Retain logs of when and how these binaries were accessed

Spotting unexpected shell spawns and binary drops

Unexpected shell spawns and unauthorized binary drops can indicate malicious activity within a container.

Attackers may utilize these tactics to execute commands or deploy additional payloads. Detecting such behavior is key in maintaining the security of container environments.

Key strategies for spotting these anomalies include:

• Monitoring logs for unexpected shell executions
• Identifying new or modified binaries in real-time
• Correlating process execution with known malicious patterns

By employing these techniques, SOC analysts can strengthen their detection capabilities and respond to potential threats in containerized systems more effectively.

Network-Based Hunting Techniques

Monitoring network activity is crucial in container environments for identifying malicious behavior and potential vulnerabilities.

This section focuses on employing advanced techniques to enhance visibility into network interactions within containerized systems.

eBPF Socket Hooks for DNS, HTTP, and TLS Anomaly Detection

Extended Berkeley Packet Filter (eBPF) technology can be employed for real-time monitoring of network calls.

By placing socket hooks, analysts can capture and analyze DNS queries, HTTP requests, and TLS connections.

This enables the identification of unusual traffic patterns that may indicate malicious activity.

Tracking Lateral Movement via Container Network Logs

Lateral movement refers to the technique employed by adversaries to navigate through a network after gaining initial access.

By analyzing container network logs, analysts can identify unusual connections between containers that may signify suspicious activity.

Fingerprinting Outbound Connections from Pods

By profiling outbound connections from pods, analysts can discern which services are being accessed and if they align with expected behavior.

This can help pinpoint unauthorized data exfiltration or contact with known malicious servers.

By implementing these network-based hunting techniques, cybersecurity professionals can enhance their ability to identify and respond to threats within containerized environments.

Memory and In-Memory Artifact Analysis

Memory analysis is crucial in detecting and understanding potential threats within containerized environments.

This section focuses on live memory capture and the detection of code injection through memory anomalies.

Live memory capture with cri-tools and forensic tools

Live memory capture involves obtaining a snapshot of the memory used by containerized applications.

This process is essential for identifying malicious activities and analyzing in-memory artifacts.

Tools such as cri-tools can facilitate the acquisition of memory images, providing analysts with valuable insights into running processes and potential exploits.

To perform live memory capture effectively, it is important to follow a structured approach, ensuring that data integrity is maintained. Key steps may include:

1. Identifying the target container and its associated processes.
2. Utilizing cri-tools to capture memory without disrupting the execution environment.
3. Analyzing the captured memory image using forensic techniques.

A sample workflow for live memory capture can be outlined as follows:

Hunting code injection via mmap and mprotect anomalies

Code injection is a common tactic used by attackers to execute malicious payloads in memory.

By monitoring system calls such as mmap and mprotect, analysts can identify potential anomalies that suggest code injection attempts.

Mmap is used to map files or devices into memory, while mprotect changes the access protections for a region of memory.

Abnormal patterns or unexpected changes in memory permissions could indicate an attempt to execute unauthorized code.

Key indicators to watch for include:

By correlating these anomalies with other telemetry data, analysts can enhance their detection capabilities and respond effectively to potential security incidents.

Monitoring these indicators creates a robust framework for identifying and mitigating code injection threats.

Behavioral Baselines and Anomaly Scoring

Establishing behavioral baselines is critical for effective threat hunting in container runtimes. By understanding what normal behavior looks like, analysts can better identify anomalies that may indicate security incidents.

Building per-image syscall and network baselines

Creating baselines for each container image allows for granular monitoring of system calls and network activity.

This process involves collecting data on normal syscall patterns and network traffic specific to each image.

The following table outlines typical parameters that can be monitored to establish baselines:

With these baselines in place, analysts can detect deviations from normal behavior that may signify potential security threats.

Applying ML time-series models for drift and anomaly detection

Machine learning (ML) time-series models can facilitate the detection of drift in the established baselines.

These models analyze historical behavior patterns and adapt to new data over time, allowing for the identification of changes that may indicate malicious activity.

The following table illustrates the application of ML models for anomaly detection:

By implementing ML-based methods, organizations can enhance their ability to respond to threats effectively, ensuring that they remain vigilant in an ever-evolving threat landscape.

Integrating with SIEM and SOAR Workflows

Incorporating container telemetry data into Security Information and Event Management (SIEM) systems and Security Orchestration, Automation, and Response (SOAR) workflows is essential for effective threat management.

This integration enhances the visibility and responsiveness of security operations, especially in environments using container runtimes.

Normalizing container telemetry into ECS/OpenTelemetry

Normalizing telemetry data allows for consistent reporting and analysis across different systems.

The Elastic Common Schema (ECS) and OpenTelemetry provide standardized formats for events, logs, and metrics.

This standardization enables security analysts to easily correlate container activity with broader security events, leading to more efficient investigations.

Enriching alerts with Kubernetes metadata and image digests

Enhancing alerts with additional context improves situational awareness for cybersecurity teams.

Including Kubernetes metadata, such as pod names, namespaces, and deployment details, provides analysts with critical information for rapidly assessing the impact of an alert.

Image digests serve as unique identifiers for container images, helping to trace vulnerabilities back to their source.

Automated playbooks: pod isolation token revocation and image rollback

Automated response playbooks streamline incident response processes, minimizing the time to react to threats.

For instance, pod isolation token revocation prevents further access once a compromise is detected.

Image rollback allows organizations to revert to a known secure state, mitigating potential damage from exploited vulnerabilities.

Integrating container telemetry with SIEM and SOAR workflows reinforces an organization's capability to manage vulnerabilities efficiently and effectively.

These practices play a crucial role in enhancing security posture and readiness against threats in containerized environments.

Case Study: Hunting a Container Escape

Falco Alert Triage and Host Namespace Compromise

In the context of container security, a container escape occurs when an attacker successfully breaks out of the confines of a container and gains access to the host system.

This case study examines a specific incident where a Falco alert indicated a potential compromise of the host namespace.

When a Falco alert is triggered, it is essential to follow a standardized triage process to assess the severity of the alert.

The key steps in this triage process include the identification of alert type, affected resources, and related events.

Upon investigation of these alerts, the analysts discovered unauthorized changes in the namespace settings of the affected container.

This indicated that the container process attempted to access or modify resources that should have been restricted.

Forensic Indicators and Remediation Steps

To effectively respond to the compromise, analysts gathered forensic indicators that could shed light on the scope and impact of the incident.

Key indicators included:

• Unusual process execution patterns.
• Changes to container security settings.
• Access logs indicating lateral movement within the host system.

The following table summarizes the forensic indicators collected during the investigation:

After gathering and analyzing the forensic indicators, remediation steps were implemented to contain the threat and prevent future occurrences. These steps included:

1. Isolating the affected container and revoking its access to the host.
2. Restoring the original container security settings.
3. Updating the incident response playbook with lessons learned from the investigation.
4. Conducting a review of existing vulnerability management best practices to strengthen overall security posture.

By following these protocols, the organization mitigated the immediate threat and improved its defenses against future vulnerabilities in its containerized environment.

Elevate Your Container Runtime Threat Hunting with Managed SOC Services

Organizations looking to enhance their container runtime threat hunting capabilities can consider leveraging specialized Managed Security Operations Center (SOC) services.

These services provide dedicated resources and expertise to monitor, detect, and respond to threats in containerized environments, ensuring elevated security postures.

Benefits of Using Managed SOC Services

Organizations interested in fortifying their defenses should reach out for a comprehensive consultation to explore how Managed SOC services can be tailored to meet their unique security challenges.