Attack Ent T1059 013 Container CLI API

MITRE ATT&CK T1059.013: Container CLI/API

When to use this skill

Use this skill when the task involves T1059.013, Container CLI/API, enterprise ATT&CK, TTP mapping, detection engineering, hunting, incident-response enrichment, control validation, or authorized adversary-emulation planning. Treat it as a defensive analysis aid: keep outputs focused on understanding, detecting, mitigating, and safely validating this ATT&CK sub-technique.

Technique context

• ATT&CK domain: enterprise
• ATT&CK ID: T1059.013
• Technique name: Container CLI/API
• Type: sub-technique
• ATT&CK URL: https://attack.mitre.org/techniques/T1059/013
• Tactics: execution
• Platforms: Containers
• Required permissions: Not specified
• Effective permissions: Not specified
• Defenses bypassed: Not specified

ATT&CK description

Adversaries may abuse built-in CLI tools or API calls to execute malicious commands in containerized environments.

The Docker CLI is used for managing containers via an exposed API point from the dockerd daemon. Some common examples of Docker CLI include Docker Desktop CLI and Docker Compose, but users are also able to use SDKs to interact with the API. For example, Docker SDK for Python can be used to run commands within a Python application.(Citation: Docker Desktop CLI)

Adversaries may leverage the Docker CLI, API, or SDK to pull or build Docker images (i.e., Ingress Tool Transfer, Build Image on Host), run containers (i.e., Deploy Container), or execute commands inside running containers (i.e., Container Administration Command). In some cases, threat actors may pull legitimate images that include scripts or tools that they can leverage - for example, using an image that includes the curl command to download payloads.(Citation: Intezer) Adversaries may also utilize docker inspect and docker ps to scan for cloud environment variables and other running containers (i.e., Container and Resource Discovery).(Citation: Cisco Talos Blog)(Citation: aquasec)

Kubernetes is responsible for the management and orchestration of containers across clusters. The Kubernetes control plane, which manages the state of the cluster and is responsible for scheduling, communication, and resource monitoring, can be invoked directly via the API or indirectly via CLI tools such as kubectl. It may also be accessed within client libraries such as Go or Python. By utilizing the API, administrators can interact with resources within the cluster such as listing or creating pods, which is a group of one or more containers. Adversaries call the API server via curl or other tools, allowing them to obtain further information about the environment such as pods, deployments, daemonsets, namespaces, or sysvars.(Citation: aquasec) They may also run various commands regarding resource management.

Agent workflow

1. Clarify scope: identify the system, asset class, log sources, cloud or endpoint platform, and whether the user wants triage, detection, coverage assessment, or safe emulation planning.
2. Load bundled resources as needed: use references/technique-profile.json for structured metadata, references/detection-and-mitigation.md for triage and telemetry guidance, references/known-threat-context.md for ATT&CK relationship context, and templates/ for repeatable outputs.
3. Map observations to ATT&CK: compare the user's evidence to the ATT&CK description, tactics, platforms, and known procedure patterns before asserting a match.
4. Produce defensive outputs: prioritize hypotheses, telemetry requirements, detection logic ideas, validation steps, containment guidance, and mitigations.
5. Preserve uncertainty: distinguish confirmed evidence, plausible indicators, assumptions, and gaps. Recommend what to collect next.
6. Stay safe: do not provide malware, credential theft, persistence, evasion, destructive automation, or unauthorized exploitation instructions. For adversary emulation, keep steps bounded to approved lab or control-validation contexts and omit operational abuse details.

Bundled resources

• references/technique-profile.json: machine-readable ATT&CK metadata for this technique.
• references/detection-and-mitigation.md: detection notes, telemetry checklist, triage questions, mitigation candidates, and false-positive considerations.
• references/known-threat-context.md: ATT&CK relationship context with attribution cautions.
• templates/detection-brief.md: detection engineering brief template.
• templates/hunt-plan.md: threat hunt plan template.
• templates/incident-response-note.md: incident response note template.
• templates/coverage-assessment.md: ATT&CK coverage assessment template.
• scripts/render_brief.py: local helper that renders a Markdown defensive brief from technique-profile.json.
• assets/output-schema.json: JSON schema for structured technique analysis outputs.

To generate a quick brief, run python scripts/render_brief.py --output brief.md from inside this skill directory, or adapt the templates directly.

Detection guidance

No ATT&CK detection guidance was present in the source STIX object.

Useful telemetry and data sources

• Not specified in the STIX object.

Mitigations to consider

• Execution Prevention
• Privileged Account Management

Known threat context

Use these examples only as contextual leads, not as proof that an observed event is this technique:

• TeamTNT (intrusion-set)

Recommended output pattern

When responding with this skill, structure the answer as:

• Assessment: whether the evidence supports this ATT&CK mapping and why.
• Evidence: specific indicators, logs, behaviors, and assumptions.
• Detection: telemetry sources, analytic logic, and tuning considerations.
• Response: containment, eradication, recovery, and validation actions.
• Coverage gaps: missing logs, sensors, controls, or environmental details.
• References: include the ATT&CK URL and any user-provided evidence references.

ATT&CK contributors

• Liran Ravich, CardinalOps