Query: detection engineering for Poisoned Pipeline Execution
Matching passage: T1677 Poisoned Pipeline Execution. Tactics: execution. 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 <b>Direct Pipeline Execution</b> 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 <b>Indirect Pipeline Execution</b> 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 <b>Public Pipeline Execution</b> 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 Staw
Near-miss passage: T1129 Shared Modules. Tactics: execution. Description: Adversaries may execute malicious payloads via loading shared modules. Shared modules are executable files that are loaded into processes to provide access to reusable code, such as specific custom functions or invoking OS API functions (i.e., [Native API](https://attack.mitre.org/techniques/T1106)). Adversaries may use this functionality as a way to execute arbitrary payloads on a victim system. For example, adversaries can modularize functionality of their malware into shared objects that perform various functions such as managing C2 network communications or execution of specific actions on objective. The Linux & macOS module loader can load and execute shared objects from arbitrary local paths. This functionality resides in `dlfcn.h` in functions such as `dlopen` and `dlsym`. Although macOS can execute `.so` files, common practice uses `.dylib` files.(Citation: Apple Dev Dynamic Libraries)(Citation: Linux Shared Libraries)(Citation: RotaJakiro 2021 netlab360 analysis)(Citation: Unit42 OceanLotus 2017) The Windows module loader can be instructed to load DLLs from arbitrary local paths and arbitrary Universal Naming Convention (UNC) network paths. This functionality resides in `NTDLL.dll` and is part of the Windows [Native API](https://attack.mitre.org/techniques/T1106) which is called from functions like `LoadLibrary` at run time.(Citation: Microsoft DLL)