Vulnerability-Lookup

CNVD-2023-16470

Vulnerability from cnvd - Published: 2023-03-13

Title

Advantech R-SeeNet堆栈缓冲区溢出漏洞

Description

Advantech R-SeeNet是中国研华（Advantech）公司的一个工业监控软件。该软件基于snmp协议进行监控平台，并且适用于Linux、Windows平台。 Advantech R-SeeNet 2.4.17及以前版本存在堆栈缓冲区溢出漏洞，未经授权的攻击者可利用该漏洞通过过长的文件名实现栈缓冲区溢出导致远程代码执行。

Severity

高

Patch Name

Advantech R-SeeNet堆栈缓冲区溢出漏洞的补丁

Patch Description

Formal description

用户可参考如下厂商提供的安全补丁以修复该漏洞： https://www.cisa.gov/uscert/ics/advisories/icsa-22-291-01

Reference

https://nvd.nist.gov/vuln/detail/CVE-2022-3386

Impacted products

Name
Advantech R-SeeNet <=2.4.17

Show details on source website

JSON

To clipboard

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2022-3386",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2022-3386"
    }
  },
  "description": "Advantech R-SeeNet\u662f\u4e2d\u56fd\u7814\u534e\uff08Advantech\uff09\u516c\u53f8\u7684\u4e00\u4e2a\u5de5\u4e1a\u76d1\u63a7\u8f6f\u4ef6\u3002\u8be5\u8f6f\u4ef6\u57fa\u4e8esnmp\u534f\u8bae\u8fdb\u884c\u76d1\u63a7\u5e73\u53f0\uff0c\u5e76\u4e14\u9002\u7528\u4e8eLinux\u3001Windows\u5e73\u53f0\u3002\n\nAdvantech R-SeeNet 2.4.17\u53ca\u4ee5\u524d\u7248\u672c\u5b58\u5728\u5806\u6808\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff0c\u672a\u7ecf\u6388\u6743\u7684\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u901a\u8fc7\u8fc7\u957f\u7684\u6587\u4ef6\u540d\u5b9e\u73b0\u6808\u7f13\u51b2\u533a\u6ea2\u51fa\u5bfc\u81f4\u8fdc\u7a0b\u4ee3\u7801\u6267\u884c\u3002",
  "formalWay": "\u7528\u6237\u53ef\u53c2\u8003\u5982\u4e0b\u5382\u5546\u63d0\u4f9b\u7684\u5b89\u5168\u8865\u4e01\u4ee5\u4fee\u590d\u8be5\u6f0f\u6d1e\uff1a\r\nhttps://www.cisa.gov/uscert/ics/advisories/icsa-22-291-01",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2023-16470",
  "openTime": "2023-03-13",
  "patchDescription": "Advantech R-SeeNet\u662f\u4e2d\u56fd\u7814\u534e\uff08Advantech\uff09\u516c\u53f8\u7684\u4e00\u4e2a\u5de5\u4e1a\u76d1\u63a7\u8f6f\u4ef6\u3002\u8be5\u8f6f\u4ef6\u57fa\u4e8esnmp\u534f\u8bae\u8fdb\u884c\u76d1\u63a7\u5e73\u53f0\uff0c\u5e76\u4e14\u9002\u7528\u4e8eLinux\u3001Windows\u5e73\u53f0\u3002\r\n\r\nAdvantech R-SeeNet 2.4.17\u53ca\u4ee5\u524d\u7248\u672c\u5b58\u5728\u5806\u6808\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff0c\u672a\u7ecf\u6388\u6743\u7684\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u901a\u8fc7\u8fc7\u957f\u7684\u6587\u4ef6\u540d\u5b9e\u73b0\u6808\u7f13\u51b2\u533a\u6ea2\u51fa\u5bfc\u81f4\u8fdc\u7a0b\u4ee3\u7801\u6267\u884c\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": "Advantech R-SeeNet\u5806\u6808\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "Advantech R-SeeNet \u003c=2.4.17"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2022-3386",
  "serverity": "\u9ad8",
  "submitTime": "2022-10-24",
  "title": "Advantech R-SeeNet\u5806\u6808\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e"
}

CVE-2022-3386 (GCVE-0-2022-3386)

Vulnerability from cvelistv5 – Published: 2022-10-27 20:34 – Updated: 2025-04-16 16:08

Summary

Advantech R-SeeNet Versions 2.4.17 and prior are vulnerable to a stack-based buffer overflow. An unauthorized attacker can use an outsized filename to overflow the stack buffer and enable remote code execution.

Severity

9.8 (Critical)


                        
                          CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

SSVC

Exploitation: none Automatable: yes Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2025-04-16 15:53 UTC

CWE

CWE-121 - Stack-based Buffer Overflow

Assigner

icscert icscert root

References

1 reference

URL	Tags
https://www.cisa.gov/uscert/ics/advisories/icsa-2…	government-resource

Impacted products

1 product

Vendor	Product	Version
Advantech	R-SeeNet	Affected: 0 , ≤ 2.4.17 (custom)

Credits

rgod Trend Micro Zero Day Initiative

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
      {
        "providerMetadata": {
          "dateUpdated": "2024-08-03T01:07:06.514Z",
          "orgId": "af854a3a-2127-422b-91ae-364da2661108",
          "shortName": "CVE"
        },
        "references": [
          {
            "tags": [
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              "x_transferred"
            ],
            "url": "https://www.cisa.gov/uscert/ics/advisories/icsa-22-291-01"
          }
        ],
        "title": "CVE Program Container"
      },
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2022-3386",
                "options": [
                  {
                    "Exploitation": "none"
                  },
                  {
                    "Automatable": "yes"
                  },
                  {
                    "Technical Impact": "total"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-04-16T15:53:19.360549Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2025-04-16T16:08:15.899Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "defaultStatus": "unaffected",
          "product": "R-SeeNet",
          "vendor": "Advantech",
          "versions": [
            {
              "lessThanOrEqual": "2.4.17",
              "status": "affected",
              "version": "0",
              "versionType": "custom"
            }
          ]
        }
      ],
      "credits": [
        {
          "lang": "en",
          "type": "finder",
          "user": "00000000-0000-4000-9000-000000000000",
          "value": "rgod"
        },
        {
          "lang": "en",
          "type": "reporter",
          "user": "00000000-0000-4000-9000-000000000000",
          "value": "Trend Micro Zero Day Initiative"
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "supportingMedia": [
            {
              "base64": false,
              "type": "text/html",
              "value": "\n\n\u003cspan style=\"background-color: rgb(255, 255, 255);\"\u003eAdvantech R-SeeNet Versions 2.4.17 and prior are vulnerable to a stack-based buffer overflow. An unauthorized attacker can use an outsized filename to overflow the stack buffer and enable remote code execution. \u003c/span\u003e\n\n"
            }
          ],
          "value": "\nAdvantech R-SeeNet Versions 2.4.17 and prior are vulnerable to a stack-based buffer overflow. An unauthorized attacker can use an outsized filename to overflow the stack buffer and enable remote code execution. \n\n"
        }
      ],
      "metrics": [
        {
          "cvssV3_1": {
            "attackComplexity": "LOW",
            "attackVector": "NETWORK",
            "availabilityImpact": "HIGH",
            "baseScore": 9.8,
            "baseSeverity": "CRITICAL",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "HIGH",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
            "version": "3.1"
          },
          "format": "CVSS",
          "scenarios": [
            {
              "lang": "en",
              "value": "GENERAL"
            }
          ]
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-121",
              "description": "CWE-121 Stack-based Buffer Overflow",
              "lang": "en",
              "type": "CWE"
            }
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      ],
      "providerMetadata": {
        "dateUpdated": "2022-10-27T20:34:44.584Z",
        "orgId": "7d14cffa-0d7d-4270-9dc0-52cabd5a23a6",
        "shortName": "icscert"
      },
      "references": [
        {
          "tags": [
            "government-resource"
          ],
          "url": "https://www.cisa.gov/uscert/ics/advisories/icsa-22-291-01"
        }
      ],
      "source": {
        "discovery": "EXTERNAL"
      },
      "x_generator": {
        "engine": "Vulnogram 0.1.0-dev"
      }
    }
  },
  "cveMetadata": {
    "assignerOrgId": "7d14cffa-0d7d-4270-9dc0-52cabd5a23a6",
    "assignerShortName": "icscert",
    "cveId": "CVE-2022-3386",
    "datePublished": "2022-10-27T20:34:44.584Z",
    "dateReserved": "2022-09-30T19:46:23.175Z",
    "dateUpdated": "2025-04-16T16:08:15.899Z",
    "requesterUserId": "bc31a57b-b1a5-40e2-9263-67c0ae8a3b8a",
    "state": "PUBLISHED"
  },
  "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.