BDU:2024-01591 (CVE-2023-49109)
Vulnerability from fstec – Published: 2024-02-27 – Updated: 2024-02-27 – View on bdu.fstec.ru Fixed
VLAI
Title
Уязвимость платформы планировщика рабочих процессов Apache DolphinScheduler, связанная с некорректным управлением генерацией кода, позволяющая нарушителю выполнить произвольный код
Summary
Уязвимость платформы планировщика рабочих процессов Apache DolphinScheduler связана с некорректным управлением генерацией кода. Эксплуатация уязвимости может позволить нарушителю, действующему удалённо, выполнить произвольный код
Severity
Class
Code vulnerability
Status
Confirmed by the vendor
Exploitation
Injection
Incidents
Being clarified
Remediation
Software update
CWE
- CWE-94 - Неверное управление генерацией кода (Внедрение кода)
Aliases
References
6 references
Impacted products
1 product
from 1 vendor
Vendors
Apache Software Foundation
Products
DolphinScheduler
Versions
от 3.0.0 до 3.2.1 (DolphinScheduler)
Product types
Application software
Mitigations
Использование рекомендаций:
https://github.com/apache/dolphinscheduler/pull/14991
https://github.com/apache/dolphinscheduler/pull/14991/files#diff-98f3973739c66cd3d14af5c1a248d46d54b1f2e9004122766b4b445a8d12e775
https://github.com/apache/dolphinscheduler/pull/14991/files#diff-7c10cc303c239c94200904f5d5c299c3dbde4924cf6ec98e38e5cf55233c0fc3
https://lists.apache.org/thread/6kgsl93vtqlbdk6otttl0d8wmlspk0m5
https://lists.apache.org/thread/5b6yq2gov0fsy9x5dkvo8ws4rr45vkn8
https://dolphinscheduler.apache.org/en-us/download/3.2.1
{
"CVSS 2.0": "AV:N/AC:L/Au:N/C:C/I:C/A:C",
"CVSS 3.0": "AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"CVSS 4.0": null,
"remediation_\u0418\u0434\u0435\u043d\u0442\u0438\u0444\u0438\u043a\u0430\u0442\u043e\u0440": null,
"remediation_\u041d\u0430\u0438\u043c\u0435\u043d\u043e\u0432\u0430\u043d\u0438\u0435": null,
"\u0412\u0435\u043d\u0434\u043e\u0440 \u041f\u041e": "Apache Software Foundation",
"\u0412\u0435\u0440\u0441\u0438\u044f \u041f\u041e": "\u043e\u0442 3.0.0 \u0434\u043e 3.2.1 (DolphinScheduler)",
"\u0412\u043e\u0437\u043c\u043e\u0436\u043d\u044b\u0435 \u043c\u0435\u0440\u044b \u043f\u043e \u0443\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u0438\u044e": "\u0418\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u0440\u0435\u043a\u043e\u043c\u0435\u043d\u0434\u0430\u0446\u0438\u0439:\nhttps://github.com/apache/dolphinscheduler/pull/14991\nhttps://github.com/apache/dolphinscheduler/pull/14991/files#diff-98f3973739c66cd3d14af5c1a248d46d54b1f2e9004122766b4b445a8d12e775\nhttps://github.com/apache/dolphinscheduler/pull/14991/files#diff-7c10cc303c239c94200904f5d5c299c3dbde4924cf6ec98e38e5cf55233c0fc3\nhttps://lists.apache.org/thread/6kgsl93vtqlbdk6otttl0d8wmlspk0m5\nhttps://lists.apache.org/thread/5b6yq2gov0fsy9x5dkvo8ws4rr45vkn8\nhttps://dolphinscheduler.apache.org/en-us/download/3.2.1",
"\u0414\u0430\u0442\u0430 \u0432\u044b\u044f\u0432\u043b\u0435\u043d\u0438\u044f": "08.11.2023",
"\u0414\u0430\u0442\u0430 \u043f\u043e\u0441\u043b\u0435\u0434\u043d\u0435\u0433\u043e \u043e\u0431\u043d\u043e\u0432\u043b\u0435\u043d\u0438\u044f": "27.02.2024",
"\u0414\u0430\u0442\u0430 \u043f\u0443\u0431\u043b\u0438\u043a\u0430\u0446\u0438\u0438": "27.02.2024",
"\u0418\u0434\u0435\u043d\u0442\u0438\u0444\u0438\u043a\u0430\u0442\u043e\u0440": "BDU:2024-01591",
"\u0418\u0434\u0435\u043d\u0442\u0438\u0444\u0438\u043a\u0430\u0442\u043e\u0440\u044b \u0434\u0440\u0443\u0433\u0438\u0445 \u0441\u0438\u0441\u0442\u0435\u043c \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0439 \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438": "CVE-2023-49109",
"\u0418\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u044f \u043e\u0431 \u0443\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u0438\u0438": "\u0423\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u044c \u0443\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u0430",
"\u041a\u043b\u0430\u0441\u0441 \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438": "\u0423\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u044c \u043a\u043e\u0434\u0430",
"\u041d\u0430\u0437\u0432\u0430\u043d\u0438\u0435 \u041f\u041e": "DolphinScheduler",
"\u041d\u0430\u0438\u043c\u0435\u043d\u043e\u0432\u0430\u043d\u0438\u0435 \u041e\u0421 \u0438 \u0442\u0438\u043f \u0430\u043f\u043f\u0430\u0440\u0430\u0442\u043d\u043e\u0439 \u043f\u043b\u0430\u0442\u0444\u043e\u0440\u043c\u044b": null,
"\u041d\u0430\u0438\u043c\u0435\u043d\u043e\u0432\u0430\u043d\u0438\u0435 \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438": "\u0423\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u044c \u043f\u043b\u0430\u0442\u0444\u043e\u0440\u043c\u044b \u043f\u043b\u0430\u043d\u0438\u0440\u043e\u0432\u0449\u0438\u043a\u0430 \u0440\u0430\u0431\u043e\u0447\u0438\u0445 \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0432 Apache DolphinScheduler, \u0441\u0432\u044f\u0437\u0430\u043d\u043d\u0430\u044f \u0441 \u043d\u0435\u043a\u043e\u0440\u0440\u0435\u043a\u0442\u043d\u044b\u043c \u0443\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u0438\u0435\u043c \u0433\u0435\u043d\u0435\u0440\u0430\u0446\u0438\u0435\u0439 \u043a\u043e\u0434\u0430, \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u044e\u0449\u0430\u044f \u043d\u0430\u0440\u0443\u0448\u0438\u0442\u0435\u043b\u044e \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u043b\u044c\u043d\u044b\u0439 \u043a\u043e\u0434",
"\u041d\u0430\u043b\u0438\u0447\u0438\u0435 \u044d\u043a\u0441\u043f\u043b\u043e\u0439\u0442\u0430": "\u0414\u0430\u043d\u043d\u044b\u0435 \u0443\u0442\u043e\u0447\u043d\u044f\u044e\u0442\u0441\u044f",
"\u041e\u043f\u0438\u0441\u0430\u043d\u0438\u0435 \u043e\u0448\u0438\u0431\u043a\u0438 CWE": "\u041d\u0435\u0432\u0435\u0440\u043d\u043e\u0435 \u0443\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u0433\u0435\u043d\u0435\u0440\u0430\u0446\u0438\u0435\u0439 \u043a\u043e\u0434\u0430 (\u0412\u043d\u0435\u0434\u0440\u0435\u043d\u0438\u0435 \u043a\u043e\u0434\u0430) (CWE-94)",
"\u041e\u043f\u0438\u0441\u0430\u043d\u0438\u0435 \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438": "\u0423\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u044c \u043f\u043b\u0430\u0442\u0444\u043e\u0440\u043c\u044b \u043f\u043b\u0430\u043d\u0438\u0440\u043e\u0432\u0449\u0438\u043a\u0430 \u0440\u0430\u0431\u043e\u0447\u0438\u0445 \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0432 Apache DolphinScheduler \u0441\u0432\u044f\u0437\u0430\u043d\u0430 \u0441 \u043d\u0435\u043a\u043e\u0440\u0440\u0435\u043a\u0442\u043d\u044b\u043c \u0443\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u0438\u0435\u043c \u0433\u0435\u043d\u0435\u0440\u0430\u0446\u0438\u0435\u0439 \u043a\u043e\u0434\u0430. \u042d\u043a\u0441\u043f\u043b\u0443\u0430\u0442\u0430\u0446\u0438\u044f \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438 \u043c\u043e\u0436\u0435\u0442 \u043f\u043e\u0437\u0432\u043e\u043b\u0438\u0442\u044c \u043d\u0430\u0440\u0443\u0448\u0438\u0442\u0435\u043b\u044e, \u0434\u0435\u0439\u0441\u0442\u0432\u0443\u044e\u0449\u0435\u043c\u0443 \u0443\u0434\u0430\u043b\u0451\u043d\u043d\u043e, \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u043b\u044c\u043d\u044b\u0439 \u043a\u043e\u0434",
"\u041f\u043e\u0441\u043b\u0435\u0434\u0441\u0442\u0432\u0438\u044f \u044d\u043a\u0441\u043f\u043b\u0443\u0430\u0442\u0430\u0446\u0438\u0438 \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438": null,
"\u041f\u0440\u043e\u0447\u0430\u044f \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u044f": null,
"\u0421\u0432\u044f\u0437\u044c \u0441 \u0438\u043d\u0446\u0438\u0434\u0435\u043d\u0442\u0430\u043c\u0438 \u0418\u0411": "\u0414\u0430\u043d\u043d\u044b\u0435 \u0443\u0442\u043e\u0447\u043d\u044f\u044e\u0442\u0441\u044f",
"\u0421\u043e\u0441\u0442\u043e\u044f\u043d\u0438\u0435 \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438": "\u041e\u043f\u0443\u0431\u043b\u0438\u043a\u043e\u0432\u0430\u043d\u0430",
"\u0421\u043f\u043e\u0441\u043e\u0431 \u0443\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u0438\u044f": "\u041e\u0431\u043d\u043e\u0432\u043b\u0435\u043d\u0438\u0435 \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u043d\u043e\u0433\u043e \u043e\u0431\u0435\u0441\u043f\u0435\u0447\u0435\u043d\u0438\u044f",
"\u0421\u043f\u043e\u0441\u043e\u0431 \u044d\u043a\u0441\u043f\u043b\u0443\u0430\u0442\u0430\u0446\u0438\u0438": "\u0418\u043d\u044a\u0435\u043a\u0446\u0438\u044f",
"\u0421\u0441\u044b\u043b\u043a\u0438 \u043d\u0430 \u0438\u0441\u0442\u043e\u0447\u043d\u0438\u043a\u0438": "https://vuldb.com/ru/?id.254176\nhttp://www.openwall.com/lists/oss-security/2024/02/20/4 \nhttps://github.com/apache/dolphinscheduler/pull/14991 \nhttps://lists.apache.org/thread/5b6yq2gov0fsy9x5dkvo8ws4rr45vkn8 \nhttps://lists.apache.org/thread/6kgsl93vtqlbdk6otttl0d8wmlspk0m5\nhttps://github.com/advisories/GHSA-qwxx-xww6-8q8m",
"\u0421\u0442\u0430\u0442\u0443\u0441 \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438": "\u041f\u043e\u0434\u0442\u0432\u0435\u0440\u0436\u0434\u0435\u043d\u0430 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u0435\u043c",
"\u0422\u0438\u043f \u041f\u041e": "\u041f\u0440\u0438\u043a\u043b\u0430\u0434\u043d\u043e\u0435 \u041f\u041e \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u043e\u043d\u043d\u044b\u0445 \u0441\u0438\u0441\u0442\u0435\u043c",
"\u0422\u0438\u043f \u043e\u0448\u0438\u0431\u043a\u0438 CWE": "CWE-94",
"\u0423\u0440\u043e\u0432\u0435\u043d\u044c \u043e\u043f\u0430\u0441\u043d\u043e\u0441\u0442\u0438 \u0443\u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0438": "\u041a\u0440\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u0443\u0440\u043e\u0432\u0435\u043d\u044c \u043e\u043f\u0430\u0441\u043d\u043e\u0441\u0442\u0438 (\u0431\u0430\u0437\u043e\u0432\u0430\u044f \u043e\u0446\u0435\u043d\u043a\u0430 CVSS 2.0 \u0441\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 10)\n\u041a\u0440\u0438\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u0443\u0440\u043e\u0432\u0435\u043d\u044c \u043e\u043f\u0430\u0441\u043d\u043e\u0441\u0442\u0438 (\u0431\u0430\u0437\u043e\u0432\u0430\u044f \u043e\u0446\u0435\u043d\u043a\u0430 CVSS 3.0 \u0441\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 9,8)"
}
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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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