Network segmentation involves dividing a network into smaller, isolated segments to control and limit the flow of traffic between devices, systems, and applications. By segmenting networks, organizations can reduce the attack surface, restrict lateral movement by adversaries, and protect critical assets from compromise. Effective network segmentation leverages a combination of physical boundaries, logical separation through VLANs, and access control policies enforced by network appliances like firewalls, routers, and cloud-based configurations. This mitigation can be implemented through the following measures: Segment Critical Systems: - Identify and group systems based on their function, sensitivity, and risk. Examples include payment systems, HR databases, production systems, and internet-facing servers. - Use VLANs, firewalls, or routers to enforce logical separation. Implement DMZ f…
MITRE mitigation sourceAdversaryGraph public intelligence page
This page is part of Threat Matrix, the public browser workspace for the main AdversaryGraph platform. Use it for ATT&CK pivots, actor and technique context, similarity leads, detection coverage review, and analyst-ready investigation paths.
Validation disclaimer: TTP overlap, actor similarity, generated summaries, and coverage findings are investigation leads, not attribution proof or operational validation without analyst review.
Main AdversaryGraph project Documentation Malware Analysis GitHub
Container and Resource Discovery
Adversaries may attempt to discover containers and other resources that are available within a containers environment. Other resources may include images, deployments, pods, nodes, and other information such as the status of a cluster. These resources can be viewed within web applications such as the Kubernetes dashboard or can be queried via the Docker and Kubernetes APIs. In Docker, logs may leak information about the environment, such as the environment’s configuration, which services are available, and what cloud provider the victim may be utilizing. The discovery of these resources may inform an adversary’s next steps in the environment, such as how to perform lateral movement and which methods to utilize for execution.
Open detection, hunting, mitigation, and evidence workspace
Detection logic
Establish centralized logging for the activity of container and Kubernetes cluster components. This can be done by deploying logging agents on Kubernetes nodes and retrieving logs from sidecar proxies for application pods to detect malicious activity at the cluster level. Monitor logs for actions that could be taken to gather information about container infrastructure, including the use of discovery API calls by new or unexpected users. Monitor account activity logs to see actions performed and activity associated with the Kubernetes dashboard and other web applications.
Observed actors
Correlated CTI and IR reports
Cyber Knowledge context
Use these routes to move from the ATT&CK behavior into explanation, implementation, evidence handling, validation, and defensive operations. Relevance is generated from explicit identifiers/names and governed topic mappings; it is not attribution evidence.
Cloud Security · Governed topic match · 81/100Cloud logging, detection engineering, ATT CK, and response automation
Cloud Security · Governed topic match · 78/100Internet exposure, service indexes, and infrastructure search
OSINT & Reconnaissance · Tactic learning route · 24/100Module 5 — Cloud, containers, and Kubernetes
Red Team & Offensive Security · Tactic learning route · 24/100
MITRE mitigations
Restrict access to network resources, such as file shares, remote systems, and services, to only those users, accounts, or systems with a legitimate business requirement. This can include employing technologies like network concentrators, RDP gateways, and zero-trust network access (ZTNA) models, alongside hardening services and protocols. This mitigation can be implemented through the following measures: Audit and Restrict Access: - Regularly audit permissions for file shares, network services, and remote access tools. - Remove unnecessary access and enforce least privilege principles for users and services. - Use Active Directory and IAM tools to restrict access based on roles and attributes. Deploy Secure Remote Access Solutions: - Use RDP gateways, VPN concentrators, and ZTNA solutions to aggregate and secure remote access connections. - Configure access controls to restrict connect…
MITRE mitigation sourceUser 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…
MITRE mitigation sourceMITRE detection strategies and analytics
- AN1352 · Analytic 1352 — Detection of adversary attempts to enumerate containers, pods, nodes, and related resources within containerized environments. Defenders may observe anomalous API calls to Docker or Kubernetes (e.g., 'docker ps', 'kubectl get pods', 'kubectl get nodes'), unusual account activity against the Kubernetes dashboard, or unexpected queries against container metadata endpoints. These events should be correlated with user context and network activity to reveal resource discovery attempts.