Vulnerability-Lookup

CNVD-2022-65317

Vulnerability from cnvd - Published: 2022-09-23

Title

USU Oracle Optimization命令注入漏洞

Description

USU Oracle Optimization是用于提升Oracle查询性能。 USU Oracle Optimization 5.17.5之前版本存在命令注入漏洞，该漏洞源于一些常见的OS命令被阻止，但用于base64解码的OS命令未被阻止，经过身份验证的DataCollection攻击者可利用该漏洞在代理上以root身份从服务器启动任何shell命令。

Severity

高

Patch Name

USU Oracle Optimization命令注入漏洞的补丁

Patch Description

Formal description

厂商已发布了漏洞修复程序，请及时关注更新： https://www.usu.com/en-us/solutions/usu-software-asset-management/oracle-optimization/

Reference

https://github.com/orangecertcc/security-research/security/advisories/GHSA-xw3r-mq8p-fjv5

Impacted products

Name
USU Oracle Optimization USU Oracle Optimization <5.17.5

Show details on source website

JSON

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{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2022-29937",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2022-29937"
    }
  },
  "description": "USU Oracle Optimization\u662f\u7528\u4e8e\u63d0\u5347Oracle\u67e5\u8be2\u6027\u80fd\u3002\n\nUSU Oracle Optimization 5.17.5\u4e4b\u524d\u7248\u672c\u5b58\u5728\u547d\u4ee4\u6ce8\u5165\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u4e00\u4e9b\u5e38\u89c1\u7684OS\u547d\u4ee4\u88ab\u963b\u6b62\uff0c\u4f46\u7528\u4e8ebase64\u89e3\u7801\u7684OS\u547d\u4ee4\u672a\u88ab\u963b\u6b62\uff0c\u7ecf\u8fc7\u8eab\u4efd\u9a8c\u8bc1\u7684DataCollection\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5728\u4ee3\u7406\u4e0a\u4ee5root\u8eab\u4efd\u4ece\u670d\u52a1\u5668\u542f\u52a8\u4efb\u4f55shell\u547d\u4ee4\u3002",
  "formalWay": "\u5382\u5546\u5df2\u53d1\u5e03\u4e86\u6f0f\u6d1e\u4fee\u590d\u7a0b\u5e8f\uff0c\u8bf7\u53ca\u65f6\u5173\u6ce8\u66f4\u65b0\uff1a\r\nhttps://www.usu.com/en-us/solutions/usu-software-asset-management/oracle-optimization/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2022-65317",
  "openTime": "2022-09-23",
  "patchDescription": "USU Oracle Optimization\u662f\u7528\u4e8e\u63d0\u5347Oracle\u67e5\u8be2\u6027\u80fd\u3002\r\n\r\nUSU Oracle Optimization 5.17.5\u4e4b\u524d\u7248\u672c\u5b58\u5728\u547d\u4ee4\u6ce8\u5165\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u4e00\u4e9b\u5e38\u89c1\u7684OS\u547d\u4ee4\u88ab\u963b\u6b62\uff0c\u4f46\u7528\u4e8ebase64\u89e3\u7801\u7684OS\u547d\u4ee4\u672a\u88ab\u963b\u6b62\uff0c\u7ecf\u8fc7\u8eab\u4efd\u9a8c\u8bc1\u7684DataCollection\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5728\u4ee3\u7406\u4e0a\u4ee5root\u8eab\u4efd\u4ece\u670d\u52a1\u5668\u542f\u52a8\u4efb\u4f55shell\u547d\u4ee4\u3002\u76ee\u524d\uff0c\u4f9b\u5e94\u5546\u53d1\u5e03\u4e86\u5b89\u5168\u516c\u544a\u53ca\u76f8\u5173\u8865\u4e01\u4fe1\u606f\uff0c\u4fee\u590d\u4e86\u6b64\u6f0f\u6d1e\u3002",
  "patchName": "USU Oracle Optimization\u547d\u4ee4\u6ce8\u5165\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "USU Oracle Optimization USU Oracle Optimization \u003c5.17.5"
  },
  "referenceLink": "https://github.com/orangecertcc/security-research/security/advisories/GHSA-xw3r-mq8p-fjv5",
  "serverity": "\u9ad8",
  "submitTime": "2022-05-06",
  "title": "USU Oracle Optimization\u547d\u4ee4\u6ce8\u5165\u6f0f\u6d1e"
}

CVE-2022-29937 (GCVE-0-2022-29937)

Vulnerability from cvelistv5 – Published: 2022-04-29 16:34 – Updated: 2024-08-03 06:33

Summary

USU Oracle Optimization before 5.17.5 allows authenticated DataCollection users to achieve agent root access because some common OS commands are blocked but (for example) an OS command for base64 decoding is not blocked. NOTE: this is not an Oracle Corporation product.

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

1 reference

URL	Tags
https://github.com/orangecertcc/security-research…	x_refsource_MISC

Show details on NVD website

JSON

To clipboard

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          "dateUpdated": "2024-08-03T06:33:43.072Z",
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              "x_transferred"
            ],
            "url": "https://github.com/orangecertcc/security-research/security/advisories/GHSA-xw3r-mq8p-fjv5"
          }
        ],
        "title": "CVE Program Container"
      }
    ],
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          "product": "n/a",
          "vendor": "n/a",
          "versions": [
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              "status": "affected",
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      ],
      "descriptions": [
        {
          "lang": "en",
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        }
      ],
      "problemTypes": [
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      },
      "references": [
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        }
      ],
      "x_legacyV4Record": {
        "CVE_data_meta": {
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          "ID": "CVE-2022-29937",
          "STATE": "PUBLIC"
        },
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  "cveMetadata": {
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    "datePublished": "2022-04-29T16:34:36.000Z",
    "dateReserved": "2022-04-29T00:00:00.000Z",
    "dateUpdated": "2024-08-03T06:33:43.072Z",
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  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

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.