Vulnerability-Lookup

CNVD-2023-85609

Vulnerability from cnvd - Published: 2023-11-13

Title

Apache Airflow信息泄露漏洞（CNVD-2023-85609）

Description

Apache Airflow是美国阿帕奇（Apache）基金会的一套用于创建、管理和监控工作流程的开源平台。该平台具有可扩展和动态监控等特点。 Apache Airflow 2.4.0到2.7.0版本存在信息泄露漏洞，该漏洞源于敏感配置信息向经过身份验证的用户公开，即使在将hide_config选项设置为仅非敏感时，也能够通过Airflow REST API读取配置以进行配置，攻击者可利用该漏洞获取敏感信息。

Severity

中

Patch Name

Apache Airflow信息泄露漏洞（CNVD-2023-85609）的补丁

Patch Description

Formal description

厂商已发布了漏洞修复程序，请及时关注更新： https://lists.apache.org/thread/yw4vzm0c5lqkwm0bxv6qy03yfd1od4nw

Reference

https://github.com/apache/airflow/pull/32261

Impacted products

Name
Apache Airflow >=2.4.0，<=2.7.0

Show details on source website

JSON

To clipboard

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      "cveNumber": "CVE-2023-46288",
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  "submitTime": "2023-10-26",
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}

CVE-2023-46288 (GCVE-0-2023-46288)

Vulnerability from cvelistv5 – Published: 2023-10-23 18:13 – Updated: 2025-02-13 17:14

Title

Apache Airflow: Sensitive parameters exposed in API when "non-sensitive-only" configuration is set

Summary

Exposure of Sensitive Information to an Unauthorized Actor vulnerability in Apache Airflow.This issue affects Apache Airflow from 2.4.0 to 2.7.0. Sensitive configuration information has been exposed to authenticated users with the ability to read configuration via Airflow REST API for configuration even when the expose_config option is set to non-sensitive-only. The expose_config option is False by default. It is recommended to upgrade to a version that is not affected if you set expose_config to non-sensitive-only configuration. This is a different error than CVE-2023-45348 which allows authenticated user to retrieve individual configuration values in 2.7.* by specially crafting their request (solved in 2.7.2). Users are recommended to upgrade to version 2.7.2, which fixes the issue and additionally fixes CVE-2023-45348.

Severity

No CVSS data available.

SSVC

Exploitation: none Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2024-09-11 14:28 UTC

CWE

CWE-200 - Exposure of Sensitive Information to an Unauthorized Actor

Assigner

apache mitre root

References

3 references

URL	Tags
https://github.com/apache/airflow/pull/32261	patch
https://lists.apache.org/thread/yw4vzm0c5lqkwm0bx…	vendor-advisory
http://www.openwall.com/lists/oss-security/2024/0…

Impacted products

1 product

Vendor	Product	Version
Apache Software Foundation	Apache Airflow	Affected: 2.4.0 , < 2.7.0 (semver)

Credits

id_No2015429 of 3H Secruity Team Lee, Wei Lee, Wei

Show details on NVD website

JSON

To clipboard

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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.

Detection rules are retrieved from Rulezet.

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.

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.