Apache Airflow: Command injection in "example_dag_decorator"
Description
An example dag example_dag_decorator had non-validated parameter that allowed the UI user to redirect the example to a malicious server and execute code on worker. This however required that the example dags are enabled in production (not default) or the example dag code copied to build your own similar dag. If you used the example_dag_decorator please review it and apply the changes implemented in Airflow 3.0.5 accordingly.
AI Insight
LLM-synthesized narrative grounded in this CVE's description and references.
The example_dag_decorator in Apache Airflow had an unvalidated parameter that could allow command injection via a malicious server redirect, requiring example DAGs enabled in production.
Vulnerability
Description
CVE-2025-54941 describes a command injection vulnerability in the Apache Airflow example DAG example_dag_decorator. The DAG included a non-validated parameter that could be manipulated by a UI user to redirect the example to a malicious server, leading to arbitrary code execution on the Airflow worker. This vulnerability only exists in environments where example DAGs are explicitly enabled in production (which is not the default configuration) or where the example DAG code was copied and used as a template for custom DAGs [1][2][3].
Exploitation
Details
An attacker must have UI access to the Airflow instance and the ability to trigger the example DAG. The attack involves providing a malicious server URL through the unvalidated parameter. When the DAG executes, it connects to the attacker-controlled server, which can then deliver payloads that execute arbitrary code on the worker node. Successful exploitation requires that the victim's Airflow deployment has example DAGs enabled or has incorporated the vulnerable pattern from example_dag_decorator into their own DAGs [2][3].
Impact
If exploited, an attacker could achieve remote code execution on the Airflow worker, potentially compromising the entire Airflow environment, including access to sensitive data, credentials, and the ability to disrupt or manipulate workflows. The severity is rated low by the Apache project due to the prerequisite conditions required for exploitation [3].
Mitigation
Apache has addressed this vulnerability in Airflow version 3.0.5. Users are strongly advised to upgrade to this version or later. If upgrading is not immediately possible, users should review any DAGs derived from example_dag_decorator and apply the parameter validation changes introduced in the patch. Users who have not enabled example DAGs in production or copied the vulnerable code are not affected [2][3].
AI Insight generated on May 19, 2026. Synthesized from this CVE's description and the cited reference URLs; citations are validated against the source bundle.
Affected packages
Versions sourced from the GitHub Security Advisory.
| Package | Affected versions | Patched versions |
|---|---|---|
apache-airflowPyPI | >= 3.0.0, < 3.0.5 | 3.0.5 |
Affected products
1- Apache Software Foundation/Apache Airflowv5Range: 3.0.0
Patches
0No patches discovered yet.
Vulnerability mechanics
AI mechanics synthesis has not run for this CVE yet.
References
4- github.com/advisories/GHSA-v3c9-j6h9-66v4ghsaADVISORY
- lists.apache.org/thread/c6q6nofc6xl5bms039ks9b34v0v36df1ghsavendor-advisoryWEB
- nvd.nist.gov/vuln/detail/CVE-2025-54941ghsaADVISORY
- www.openwall.com/lists/oss-security/2025/10/29/6ghsaWEB
News mentions
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