Vulnerability-Lookup

VAR-202307-0657

Vulnerability from variot - Updated: 2024-01-21 19:51

A vulnerability has been identified in SIMATIC MV540 H (All versions < V3.3.4), SIMATIC MV540 S (All versions < V3.3.4), SIMATIC MV550 H (All versions < V3.3.4), SIMATIC MV550 S (All versions < V3.3.4), SIMATIC MV560 U (All versions < V3.3.4), SIMATIC MV560 X (All versions < V3.3.4). Affected devices cannot properly process specially crafted IP packets sent to the devices. This could allow an unauthenticated remote attacker to cause a denial of service condition. The affected devices must be restarted manually. simatic mv540 h firmware, simatic mv540 s firmware, simatic mv550 h Multiple Siemens products such as firmware have unspecified vulnerabilities.Service operation interruption (DoS) It may be in a state. The SIMATIC MV500 products are fixed optical readers for capturing printed, laser, drilled, punched and dot-dash codes on a variety of different surfaces

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CVE-2023-35920 (GCVE-0-2023-35920)

Vulnerability from cvelistv5 – Published: 2023-07-11 09:07 – Updated: 2024-11-12 16:53

Summary

Severity

7.5 (High)


                        
                          CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H/E:P/RL:O/RC:C

SSVC

Exploitation: none Automatable: yes Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2024-11-12 16:50 UTC

CWE

CWE-400 - Uncontrolled Resource Consumption

Assigner

siemens icscert root

References

1 reference

URL	Tags
https://cert-portal.siemens.com/productcert/pdf/s…

Impacted products

12 products

Vendor	Product	Version
Siemens	SIMATIC MV540 H	Affected: All versions < V3.3.4
Siemens	SIMATIC MV540 S	Affected: All versions < V3.3.4
Siemens	SIMATIC MV550 H	Affected: All versions < V3.3.4
Siemens	SIMATIC MV550 S	Affected: All versions < V3.3.4
Siemens	SIMATIC MV560 U	Affected: All versions < V3.3.4
Siemens	SIMATIC MV560 X	Affected: All versions < V3.3.4
siemens	simatic_mv540_h	Affected: 0 , < V3.3.4 (custom) cpe:2.3:h:siemens:simatic_mv540_h:-:::::::*
siemens	simatic_mv540_s	Affected: 0 , < V3.3.4 (custom) cpe:2.3:h:siemens:simatic_mv540_s:-:::::::*
siemens	simatic_mv550_h	Affected: 0 , < V3.3.4 (custom) cpe:2.3:h:siemens:simatic_mv550_h:-:::::::*
siemens	simatic_mv550_s	Affected: 0 , < V3.3.4 (custom) cpe:2.3:h:siemens:simatic_mv550_s:-:::::::*
siemens	simatic_mv560_u	Affected: 0 , < V3.3.4 (custom) cpe:2.3:h:siemens:simatic_mv560_u:-:::::::*
siemens	simatic_mv560_x	Affected: 0 , < V3.3.4 (custom) cpe:2.3:h:siemens:simatic_mv560_x:-:::::::*

Show details on NVD website

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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.

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.