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CVE-2023-46120 Siemens CVE debrief

CVE-2023-46120 is a medium-severity vulnerability in the RabbitMQ Java client library affecting Siemens SINEC NMS. The vulnerability stems from improper enforcement of the `maxBodyLength` parameter when receiving Message objects, allowing attackers to send oversized messages that trigger memory exhaustion and Out-of-Memory (OOM) errors on consumer systems. This creates a denial-of-service condition through memory exhaustion. The vulnerability was patched in RabbitMQ Java client version 5.18.0. Siemens has addressed this in SINEC NMS through updates to version 3.0 or later. The CVSS 3.1 vector (AV:N/AC:L/PR:H/UI:N/S:U/C:N/I:N/A:H/E:P/RL:O/RC:C) indicates network attack vector with low complexity, requiring high privileges, with high availability impact. The vulnerability was published on August 13, 2024, and is not listed in CISA's Known Exploited Vulnerabilities catalog.

Vendor
Siemens
Product
SINEC NMS
CVSS
MEDIUM 4.9
CISA KEV
Not listed in stored evidence
Original CVE published
2024-02-13
Original CVE updated
2024-03-12
Advisory published
2024-02-13
Advisory updated
2024-03-12

Who should care

Organizations operating Siemens SINEC NMS for industrial network management, developers using RabbitMQ Java client libraries in JVM-based applications, security teams managing message broker infrastructure, and OT/ICS security practitioners responsible for availability of critical industrial systems.

Technical summary

The RabbitMQ Java client library fails to apply the `maxBodyLength` configuration parameter when receiving Message objects. This allows malicious actors to transmit arbitrarily large messages that consume excessive memory on consumer systems, resulting in Out-of-Memory errors and denial-of-service conditions. The vulnerability is exploitable over the network with low complexity but requires high privileges. The fix was implemented in RabbitMQ Java client version 5.18.0, which has been integrated into SINEC NMS version 3.0 and later.

Defensive priority

medium

Recommended defensive actions

  • Update Siemens SINEC NMS to version 3.0 or later to incorporate the patched RabbitMQ Java client library (version 5.18.0)
  • Review and validate message size limits in RabbitMQ Java client configurations
  • Monitor consumer systems for abnormal memory consumption patterns
  • Apply defense-in-depth practices for industrial control systems per CISA guidance
  • Verify RabbitMQ Java client library versions in dependent applications and upgrade to 5.18.0 or later

Evidence notes

Vulnerability description and remediation details sourced from CISA CSAF advisory ICSA-24-228-06 and Siemens security advisory SSA-784301. CVSS score and vector from source material. Patch version 5.18.0 explicitly stated in source description.

Sources and references

Verified primary and authoritative sources

  • CVE-2023-46120 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2023-46120

    CVE Program - Official CVE Program record with source-provided CVE metadata.

  • CVE-2023-46120 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2023-46120

    NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.

Supplemental references

  • Source item URL

    Unverified legacy reference

    URL: https://raw.githubusercontent.com/cisagov/CSAF/develop/csaf_files/OT/white/2024/icsa-24-228-06.json

    cisa_csaf

  • Source reference

    Unverified legacy reference

    URL: https://cert-portal.siemens.com/productcert/csaf/ssa-784301.json

    Reference

  • Source reference

    Unverified legacy reference

    URL: https://cert-portal.siemens.com/productcert/html/ssa-784301.html

    Reference

  • Source reference

    Unverified legacy reference

    URL: https://www.cisa.gov/news-events/ics-advisories/icsa-24-228-06

    Reference

  • Source reference

    Unverified legacy reference

    URL: https://www.cisa.gov/uscert/ics/alerts/ICS-ALERT-10-301-01

    Reference

  • Source reference

    Unverified legacy reference

    URL: https://www.cisa.gov/resources-tools/resources/ics-recommended-practices

    Reference

  • Source reference

    Unverified legacy reference

    URL: https://www.cisa.gov/topics/industrial-control-systems

    Reference

  • Source reference

    Unverified legacy reference

    URL: https://us-cert.cisa.gov/sites/default/files/recommended_practices/NCCIC_ICS-CERT_Defense_in_Depth_2016_S508C.pdf

    Reference

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.