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CVE-2024-22025 NodeJS CVE debrief

CVE-2024-22025 is a denial-of-service vulnerability in Node.js affecting Siemens SINEC INS, published 2024-11-12. The vulnerability stems from resource exhaustion during fetch() brotli decoding, where a remote attacker can send a specially crafted request to trigger a DoS condition. The CVSS 3.1 score of 5.3 (MEDIUM) reflects network accessibility with low attack complexity, no required privileges or user interaction, and low availability impact. Siemens has released a vendor fix: update to V1.0 SP2 Update 3 or later. CISA published this advisory as ICSA-24-319-08, cross-referencing Siemens' security advisory SSA-915275.

Vendor
NodeJS
Product
SINEC INS
CVSS
MEDIUM 5.3
CISA KEV
Not listed in stored evidence
Original CVE published
2024-11-12
Original CVE updated
2024-11-12
Advisory published
2024-11-12
Advisory updated
2024-11-12

Who should care

Organizations operating Siemens SINEC INS in industrial environments, OT security teams managing Node.js-based applications, and infrastructure operators relying on fetch() for HTTP communications should prioritize this update.

Technical summary

The vulnerability exists in Node.js's implementation of the fetch() API when handling Brotli-compressed responses. Insufficient resource limits during decompression allow an attacker to exhaust system resources through crafted compressed data, resulting in denial of service. The attack vector is network-based with no authentication required.

Defensive priority

medium

Recommended defensive actions

  • Update Siemens SINEC INS to V1.0 SP2 Update 3 or later version per vendor guidance.
  • Review network segmentation for SINEC INS deployments to limit exposure of affected systems.
  • Monitor for anomalous request patterns that may indicate attempted exploitation of fetch() brotli decoding.
  • Apply CISA ICS recommended practices for defense-in-depth strategies in industrial control environments.

Evidence notes

The vulnerability description and remediation details are sourced from CISA CSAF advisory ICSA-24-319-08, which references Siemens security advisory SSA-915275. The affected product is confirmed as SINEC INS with a specific vendor fix version available.

Sources and references

Verified primary and authoritative sources

  • CVE-2024-22025 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2024-22025

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

  • CVE-2024-22025 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2024-22025

    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-24-319-08.json

    cisa_csaf

  • Source reference

    Unverified legacy reference

    URL: https://cert-portal.siemens.com/productcert/csaf/ssa-915275.json

    Reference

  • Source reference

    Unverified legacy reference

    URL: https://cert-portal.siemens.com/productcert/html/ssa-915275.html

    Reference

  • Source reference

    Unverified legacy reference

    URL: https://www.cisa.gov/news-events/ics-advisories/icsa-24-319-08

    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.