Vulnerability-Lookup

CNVD-2022-68944

Vulnerability from cnvd - Published: 2022-10-14

Title

Sourcecodesterk Doctor Appointment System SQL注入漏洞

Description

Sourcecodesterk Doctor Appointment System是Sourcecodesterk开源的一个应用软件。提供了一个预约功能。 Sourcecodesterk Doctor Appointment System 1.0版本存在SQL注入漏洞，该漏洞源于程序未对search_result.php中的expertise参数进行充分过滤，攻击者可利用SQL注入攻击转储数据库凭证。

Severity

中

Formal description

厂商尚未提供漏洞修复方案，请关注厂商主页更新： https://www.sourcecodester.com/php/14182/doctor-appointment-system.html

Reference

http://packetstormsecurity.com/files/161342/Doctor-Appointment-System-1.0-SQL-Injection.html

Impacted products

Name
Sourcecodesterk Doctor Appointment System 1.0

Show details on source website

JSON

To clipboard

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2021-27124",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2021-27124"
    }
  },
  "description": "Sourcecodesterk Doctor Appointment System\u662fSourcecodesterk\u5f00\u6e90\u7684\u4e00\u4e2a\u5e94\u7528\u8f6f\u4ef6\u3002\u63d0\u4f9b\u4e86\u4e00\u4e2a\u9884\u7ea6\u529f\u80fd\u3002\n\nSourcecodesterk Doctor Appointment System 1.0\u7248\u672c\u5b58\u5728SQL\u6ce8\u5165\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u7a0b\u5e8f\u672a\u5bf9search_result.php\u4e2d\u7684expertise\u53c2\u6570\u8fdb\u884c\u5145\u5206\u8fc7\u6ee4\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528SQL\u6ce8\u5165\u653b\u51fb\u8f6c\u50a8\u6570\u636e\u5e93\u51ed\u8bc1\u3002",
  "formalWay": "\u5382\u5546\u5c1a\u672a\u63d0\u4f9b\u6f0f\u6d1e\u4fee\u590d\u65b9\u6848\uff0c\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\u66f4\u65b0\uff1a\r\nhttps://www.sourcecodester.com/php/14182/doctor-appointment-system.html",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2022-68944",
  "openTime": "2022-10-14",
  "products": {
    "product": "Sourcecodesterk Doctor Appointment System 1.0"
  },
  "referenceLink": "http://packetstormsecurity.com/files/161342/Doctor-Appointment-System-1.0-SQL-Injection.html",
  "serverity": "\u4e2d",
  "submitTime": "2022-05-30",
  "title": "Sourcecodesterk Doctor Appointment System SQL\u6ce8\u5165\u6f0f\u6d1e"
}

CVE-2021-27124 (GCVE-0-2021-27124)

Vulnerability from cvelistv5 – Published: 2021-02-18 03:06 – Updated: 2024-08-03 20:40

Summary

SQL injection in the expertise parameter in search_result.php in Doctor Appointment System v1.0 allows an authenticated patient user to dump the database credentials via a SQL injection attack.

Severity

No CVSS data available.

CWE

Assigner

mitre CNA under the mitre root

CNA scorecard E 29/100 over 2267 records in the last 180 days details

References

3 references

URL	Tags
http://packetstormsecurity.com/files/161342/Docto…	x_refsource_MISC
https://www.sourcecodester.com/php/14182/doctor-a…	x_refsource_MISC
https://naku-ratti.medium.com/doctor-appointment-…	x_refsource_MISC

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
      {
        "providerMetadata": {
          "dateUpdated": "2024-08-03T20:40:47.400Z",
          "orgId": "af854a3a-2127-422b-91ae-364da2661108",
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          },
          {
            "tags": [
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            ],
            "url": "https://www.sourcecodester.com/php/14182/doctor-appointment-system.html"
          },
          {
            "tags": [
              "x_refsource_MISC",
              "x_transferred"
            ],
            "url": "https://naku-ratti.medium.com/doctor-appointment-system-1-0-authenticated-sql-dios-7689b1d30f5f"
          }
        ],
        "title": "CVE Program Container"
      }
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          "vendor": "n/a",
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      "providerMetadata": {
        "dateUpdated": "2021-02-18T03:06:44.000Z",
        "orgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
        "shortName": "mitre"
      },
      "references": [
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        },
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          "url": "https://www.sourcecodester.com/php/14182/doctor-appointment-system.html"
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          ],
          "url": "https://naku-ratti.medium.com/doctor-appointment-system-1-0-authenticated-sql-dios-7689b1d30f5f"
        }
      ],
      "x_legacyV4Record": {
        "CVE_data_meta": {
          "ASSIGNER": "cve@mitre.org",
          "ID": "CVE-2021-27124",
          "STATE": "PUBLIC"
        },
        "affects": {
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              {
                "product": {
                  "product_data": [
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                      "version": {
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        "problemtype": {
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                  "lang": "eng",
                  "value": "n/a"
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          "reference_data": [
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            },
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            },
            {
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  "cveMetadata": {
    "assignerOrgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
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    "dateReserved": "2021-02-10T00:00:00.000Z",
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  },
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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.

Vulnerability timeline

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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.

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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