Vulnerability-Lookup

CNVD-2019-43891

Vulnerability from cnvd - Published: 2019-12-05

Title

IBM Security Privileged Identity Manager跨站请求伪造漏洞

Description

IBM Security Privileged Identity Manager（ISPIM）是美国IBM公司的一款身份监管解决方案（IBM Identity Governance and Management）中的身份管理产品。该产品主要用于保护、自动执行并审计特权身份的使用，以帮助抵御内部威胁并提高安全性。 IBM ISPIM 2.1.1版本中存在跨站请求伪造漏洞，该漏洞源于WEB应用未充分验证请求是否来自可信用户。攻击者可利用该漏洞通过受影响客户端向服务器发送非预期的请求。

Severity

中

Patch Name

IBM Security Privileged Identity Manager跨站请求伪造漏洞的补丁

Patch Description

Formal description

目前厂商已经发布了升级补丁以修复这个安全问题，请到厂商的主页下载： https://www-01.ibm.com/support/docview.wss?uid=ibm10742713

Reference

https://nvd.nist.gov/vuln/detail/CVE-2018-1622

Impacted products

Name
IBM IBM Security Privileged Identity Manager 2.1.1

Show details on source website

JSON

To clipboard

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  "cves": {
    "cve": {
      "cveNumber": "CVE-2018-1622",
      "cveUrl": "http://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2018-1622"
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  "number": "CNVD-2019-43891",
  "openTime": "2019-12-05",
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  "products": {
    "product": "IBM IBM Security Privileged Identity Manager 2.1.1"
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  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2018-1622",
  "serverity": "\u4e2d",
  "submitTime": "2018-12-06",
  "title": "IBM Security Privileged Identity Manager\u8de8\u7ad9\u8bf7\u6c42\u4f2a\u9020\u6f0f\u6d1e"
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CVE-2018-1622 (GCVE-0-2018-1622)

Vulnerability from cvelistv5 – Published: 2019-04-02 13:20 – Updated: 2024-09-17 02:52

Summary

IBM Security Privileged Identity Manager Virtual Appliance 2.2.1 is vulnerable to cross-site request forgery which could allow an attacker to execute malicious and unauthorized actions transmitted from a user that the website trusts. IBM X-Force ID: 144348.

Severity

4.3 (Medium)


                        
                          CVSS:3.0/I:L/A:N/AV:N/S:U/AC:L/PR:N/UI:R/C:N/E:U/RL:O/RC:C

CWE

Gain Access

Assigner

ibm mitre root

References

2 references

URL	Tags
http://www.ibm.com/support/docview.wss?uid=ibm10879093	x_refsource_CONFIRM
https://exchange.xforce.ibmcloud.com/vulnerabilit…	vdb-entryx_refsource_XF

Impacted products

1 product

Vendor	Product	Version
IBM	Security Privileged Identity Manager	Affected: 2.1.1

Date Public

2019-03-29 00:00

Show details on NVD website

JSON

To clipboard

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        {
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            "attackComplexity": "LOW",
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            "availabilityImpact": "NONE",
            "baseScore": 4.3,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "NONE",
            "exploitCodeMaturity": "UNPROVEN",
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            "remediationLevel": "OFFICIAL_FIX",
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            "scope": "UNCHANGED",
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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.