Vulnerability-Lookup

CNVD-2017-04918

Vulnerability from cnvd - Published: 2017-04-10

Title

Schneider Electric Modicon PLC多重身份验证绕过漏洞（CNVD-2017-04918）

Description

Modicon PLC是用于水坝、能源、食品农业等等行业的可编程控制器产品。 Schneider Electric Modicon PLC存在多重身份验证绕过漏洞，访问OT网络的攻击者可以拦截到目标PLC的流量，包括向设备发送管理命令所需的会话标识符。

Severity

中

Patch Name

Schneider Electric Modicon PLC多重身份验证绕过漏洞（CNVD-2017-04918）的补丁

Patch Description

Modicon PLC是用于水坝、能源、食品农业等等行业的可编程控制器产品。 Schneider Electric Modicon PLC存在多重身份验证绕过漏洞，访问OT网络的攻击者可以拦截到目标PLC的流量，包括向设备发送管理命令所需的会话标识符。目前，供应商发布了安全公告及相关补丁信息，修复了此漏洞。

Formal description

目前厂商已经发布了升级补丁以修复此安全问题，详情请关注厂商主页: http://www.securityweek.com/plcs-several-vendors-vulnerable-replay-attacks

Reference

http://securityaffairs.co/wordpress/57731/malware/clearenergy-ransomware-scada.html http://www.securityfocus.com/bid/97562

Impacted products

Name
Schneider Electric Modicon PLC

Show details on source website

JSON

To clipboard

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  "referenceLink": "http://securityaffairs.co/wordpress/57731/malware/clearenergy-ransomware-scada.html\r\nhttp://www.securityfocus.com/bid/97562",
  "serverity": "\u4e2d",
  "submitTime": "2017-04-10",
  "title": "Schneider Electric Modicon PLC\u591a\u91cd\u8eab\u4efd\u9a8c\u8bc1\u7ed5\u8fc7\u6f0f\u6d1e\uff08CNVD-2017-04918\uff09"
}

CVE-2017-6034 (GCVE-0-2017-6034)

Vulnerability from cvelistv5 – Published: 2017-06-30 02:35 – Updated: 2026-06-04 21:07

Title

Schneider Electric Modicon Modbus Protocol Authentication Bypass by Capture-replay

Summary

An authentication bypass by capture-replay issue was discovered in Schneider Electric Modicon Modbus Protocol. Sensitive information is transmitted in cleartext in the Modicon Modbus protocol, which may allow an attacker to replay the following commands: run, stop, upload, and download.

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 2026-05-28 19:09 UTC

CWE

CWE-294

Assigner

icscert CNA under the icscert root

CNA scorecard B 75/100 over 342 records in the last 180 days details

References

4 references

URL	Tags
https://ics-cert.us-cert.gov/advisories/ICSA-17-101-01
http://www.securityfocus.com/bid/97562	vdb-entryx_refsource_BID
https://github.com/cisagov/CSAF/blob/develop/csaf…
https://www.se.com/us/en/download/document/SEVD-2…

Impacted products

1 product

Vendor	Product	Version
Schneider Electric	Modicon Modbus Protocol	Affected: all versions

Date Public

2017-06-29 00:00

Credits

Eran Goldstein of CRITIFENCE reported the identified vulnerabilities.

Show details on NVD website

JSON

To clipboard

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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.

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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.
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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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