Vulnerability-Lookup

CNVD-2018-25037

Vulnerability from cnvd - Published: 2018-12-11

Title

IBM QRadar Incident Forensics信息泄露漏洞（CNVD-2018-25037）

Description

IBM QRadar Incident Forensics是美国IBM公司的一套安全取证调查软件。该软件支持对疑似恶意网络安全事件进行深入取证调查，及修复网络安全漏洞。 IBM QRadar Incident Forensics 7.2.0版本至7.2.8 Patch 13版本和7.3.0版本至7.3.1 Patch 5版本中存在安全漏洞，该漏洞源于程序使用了过时的不安全的加密算法或专有的加密标准。攻击者可利用该漏洞解密高度敏感的信息。

Severity

中

Patch Name

IBM QRadar Incident Forensics信息泄露漏洞（CNVD-2018-25037）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: https://www-01.ibm.com/support/docview.wss?uid=ibm10737027

Reference

https://nvd.nist.gov/vuln/detail/CVE-2018-1648

Impacted products

Name
['IBM QRadar Incident Forensics >=7.2.0，<=7.2.8 Patch 13', 'IBM QRadar Incident Forensics >=7.3.0，<=7.3.1 Patch 5']

Show details on source website

JSON

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  "number": "CNVD-2018-25037",
  "openTime": "2018-12-11",
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  "patchName": "IBM QRadar Incident Forensics\u4fe1\u606f\u6cc4\u9732\u6f0f\u6d1e\uff08CNVD-2018-25037\uff09\u7684\u8865\u4e01",
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  "submitTime": "2018-12-05",
  "title": "IBM QRadar Incident Forensics\u4fe1\u606f\u6cc4\u9732\u6f0f\u6d1e\uff08CNVD-2018-25037\uff09"
}

CVE-2018-1648 (GCVE-0-2018-1648)

Vulnerability from cvelistv5 – Published: 2018-12-05 17:00 – Updated: 2024-08-05 04:07

Summary

IBM QRadar SIEM 7.2 and 7.3 uses weaker than expected cryptographic algorithms that could allow an attacker to decrypt highly sensitive information. IBM X-Force ID: 144653.

Severity

No CVSS data available.

CWE

Assigner

ibm mitre root

References

2 references

URL	Tags
https://exchange.xforce.ibmcloud.com/vulnerabilit…	vdb-entryx_refsource_XF
http://www.ibm.com/support/docview.wss?uid=ibm10737027	x_refsource_CONFIRM

Date Public

2018-12-03 00:00

Show details on NVD website

JSON

To clipboard

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          },
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          ],
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        },
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          "tags": [
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          ],
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      ],
      "x_legacyV4Record": {
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          "ASSIGNER": "psirt@us.ibm.com",
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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.