GSD-2023-50943
Vulnerability from gsd - Updated: 2023-12-17 06:01Details
Apache Airflow, versions before 2.8.1, have a vulnerability that allows a potential attacker to poison the XCom data by bypassing the protection of "enable_xcom_pickling=False" configuration setting resulting in poisoned data after XCom deserialization. This vulnerability is considered low since it requires a DAG author to exploit it. Users are recommended to upgrade to version 2.8.1 or later, which fixes this issue.
Aliases
{
"gsd": {
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"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
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"modified": "2023-12-17T06:01:18.193913Z",
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"credits": [
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"name": "https://github.com/apache/airflow/pull/36255",
"refsource": "MISC",
"url": "https://github.com/apache/airflow/pull/36255"
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"value": "Apache Airflow, versions before 2.8.1, have a vulnerability that allows a potential attacker to poison the XCom data by bypassing the protection of \"enable_xcom_pickling=False\" configuration setting resulting in poisoned data after XCom deserialization. This vulnerability is considered low since it requires a DAG author to exploit it. Users are recommended to upgrade to version 2.8.1 or later, which fixes this issue.\n"
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{
"lang": "es",
"value": "Apache Airflow, versiones anteriores a 2.8.1, tienen una vulnerabilidad que permite a un atacante potencial envenenar los datos de XCom al evadir la protecci\u00f3n de la configuraci\u00f3n \"enable_xcom_pickling=False\", lo que genera datos envenenados despu\u00e9s de la deserializaci\u00f3n de XCom. Esta vulnerabilidad se considera baja ya que requiere un autor de DAG para explotarla. Se recomienda a los usuarios actualizar a la versi\u00f3n 2.8.1 o posterior, que soluciona este problema."
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"id": "CVE-2023-50943",
"lastModified": "2024-01-30T22:57:59.310",
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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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