Vulnerability-Lookup

CNVD-2017-32196

Vulnerability from cnvd - Published: 2017-11-01

Title

Oracle Fusion Middleware Oracle Virtual Directory组件存在漏洞

Description

Oracle Fusion Middleware（Oracle融合中间件）是美国甲骨文（Oracle）公司的一套面向企业和云环境的业务创新平台，该平台提供了中间件、软件集合等功能。Oracle Virtual Directory是其中的一个虚拟目录组件。 Oracle Fusion Middleware中的Oracle Virtual Directory组件11.1.1.7.0版本和11.1.1.9.0版本的Virtual Directory Server子组件存在安全漏洞。攻击者可利用该漏洞控制组件，影响数据的完整性、保密性和可用性。

Severity

中

Patch Name

Oracle Fusion Middleware Oracle Virtual Directory组件存在漏洞的补丁

Patch Description

Formal description

目前厂商已发布升级补丁以修复漏洞，补丁获取链接： http://www.oracle.com/technetwork/security-advisory/cpuoct2017-3236626.html

Reference

http://www.oracle.com/technetwork/security-advisory/cpuoct2017-3236626.html

Impacted products

Name
['Oracle Virtual Directory 11.1.1.7.0', 'Oracle Virtual Directory 11.1.1.9.0']

Show details on source website

JSON

To clipboard

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  "discovererName": "Travis Emmert of Exodus Intelligence",
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CVE-2017-10369 (GCVE-0-2017-10369)

Vulnerability from cvelistv5 – Published: 2017-10-19 17:00 – Updated: 2024-10-04 16:46

Summary

Vulnerability in the Oracle Virtual Directory component of Oracle Fusion Middleware (subcomponent: Virtual Directory Server). Supported versions that are affected are 11.1.1.7.0 and 11.1.1.9.0. Difficult to exploit vulnerability allows low privileged attacker with network access via HTTP to compromise Oracle Virtual Directory. Successful attacks of this vulnerability can result in takeover of Oracle Virtual Directory. CVSS 3.0 Base Score 7.5 (Confidentiality, Integrity and Availability impacts). CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H).

Severity

No CVSS data available.

SSVC

Exploitation: none Automatable: no Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2024-10-04 15:38 UTC

CWE

Difficult to exploit vulnerability allows low privileged attacker with network access via HTTP to compromise Oracle Virtual Directory. Successful attacks of this vulnerability can result in takeover of Oracle Virtual Directory.

Assigner

oracle mitre root

References

3 references

URL	Tags
http://www.securitytracker.com/id/1039602	vdb-entryx_refsource_SECTRACK
http://www.oracle.com/technetwork/security-adviso…	x_refsource_CONFIRM
http://www.securityfocus.com/bid/101301	vdb-entryx_refsource_BID

Impacted products

1 product

Vendor	Product	Version
Oracle Corporation	Oracle Virtual Directory	Affected: 11.1.1.7.0 Affected: 11.1.1.9.0

Date Public

2017-10-17 00:00

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.