Attack Ent T1677 Poisoned Pipeline Execution

MITRE ATT&CK T1677: Poisoned Pipeline Execution

When to use this skill

Use this skill when the task involves T1677, Poisoned Pipeline Execution, 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 technique.

Technique context

• ATT&CK domain: enterprise
• ATT&CK ID: T1677
• Technique name: Poisoned Pipeline Execution
• Type: technique
• ATT&CK URL: https://attack.mitre.org/techniques/T1677
• Tactics: execution
• Platforms: SaaS
• Required permissions: Not specified
• Effective permissions: Not specified
• Defenses bypassed: Not specified

ATT&CK description

Adversaries may manipulate continuous integration / continuous development (CI/CD) processes by injecting malicious code into the build process. There are several mechanisms for poisoning pipelines:

• In a Direct Pipeline Execution scenario, the threat actor directly modifies the CI configuration file (e.g., gitlab-ci.yml in GitLab). They may include a command to exfiltrate credentials leveraged in the build process to a remote server, or to export them as a workflow artifact.(Citation: Unit 42 Palo Alto GitHub Actions Supply Chain Attack 2025)(Citation: OWASP CICD-SEC-4)
• In an Indirect Pipeline Execution scenario, the threat actor injects malicious code into files referenced by the CI configuration file. These may include makefiles, scripts, unit tests, and linters.(Citation: OWASP CICD-SEC-4)
• In a Public Pipeline Execution scenario, the threat actor does not have direct access to the repository but instead creates a malicious pull request from a fork that triggers a part of the CI/CD pipeline. For example, in GitHub Actions, the pull_request_target trigger allows workflows running from forked repositories to access secrets. If this trigger is combined with an explicit pull request checkout and a location for a threat actor to insert malicious code (e.g., an npm build command), a threat actor may be able to leak pipeline credentials.(Citation: Unit 42 Palo Alto GitHub Actions Supply Chain Attack 2025)(Citation: GitHub Security Lab GitHub Actions Security 2021) Similarly, threat actors may craft pull requests with malicious inputs (such as branch names) if the build pipeline treats those inputs as trusted.(Citation: Wiz Ultralytics AI Library Hijack 2024)(Citation: Synactiv Hijacking GitHub Runners)(Citation: GitHub Security Labs GitHub Actions Security Part 2 2021) Finally, if a pipeline leverages a self-hosted runner, a threat actor may be able to execute arbitrary code on a host inside the organization’s network.(Citation: John Stawinski PyTorch Supply Chain Attack 2024)

By poisoning CI/CD pipelines, threat actors may be able to gain access to credentials, laterally move to additional hosts, or input malicious components to be shipped further down the pipeline (i.e., Supply Chain Compromise).

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

• Software Configuration
• User Account Management

Known threat context

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

• Shai-Hulud (malware)

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

• Arun Seelagan, CISA