PatchSiren cyber security CVE debrief
CVE-2026-74238 tier4 CVE debrief
CVE-2026-74238 is a high-severity vulnerability in TIER IV Nebula, a software used for autonomous driving. The vulnerability allows unauthenticated remote attackers to cause the decoder to read past the end of a received UDP buffer into adjacent heap memory by sending a short UDP datagram. This can lead to fabricated points derived from heap memory contents being silently published into downstream PointCloud2 messages consumed by Autoware nodes.
- Vendor
- tier4
- Product
- nebula
- CVSS
- HIGH 8.7
- CISA KEV
- Not listed in stored evidence
- Original CVE published
- 2026-08-17
- Original CVE updated
- 2026-09-24
- Advisory published
- 2026-08-17
- Advisory updated
- 2026-09-24
Who should care
Autonomous driving system operators and developers using TIER IV Nebula, as well as security teams responsible for monitoring and patching vulnerabilities in autonomous driving systems.
Why it matters
CVE-2026-74238 is a high-severity vulnerability in TIER IV Nebula that allows unauthenticated remote attackers to cause the decoder to read past the end of a received UDP buffer into adjacent heap memory. Autonomous driving system operators and developers should prioritize patching and monitoring to prevent potential disruptions and incorrect data publication.
- Potential for incorrect data to be published to downstream nodes
- Possible disruption of autonomous driving system operations
- Need for input validation and sanitization for UDP datagrams
- Requirement for monitoring system logs for suspicious activity
Technical summary
The vulnerability is caused by an out-of-bounds read in the Vlp32Decoder::unpack() function, which allows unauthenticated remote attackers to cause the decoder to read past the end of a received UDP buffer into adjacent heap memory. This can lead to fabricated points derived from heap memory contents being silently published into downstream PointCloud2 messages consumed by Autoware nodes. The CVE record and NVD entry provide details on the vulnerability. TIER IV Nebula software used for autonomous driving is affected. The vulnerability has a high severity score and requires immediate attention from autonomous driving system operators and developers.
Defensive priority
High priority for autonomous driving systems using TIER IV Nebula, as it can cause incorrect data to be published to downstream nodes.
Recommended defensive actions
- Review and update TIER IV Nebula to the latest version
- Implement input validation and sanitization for UDP datagrams
- Monitor system logs for suspicious activity
- Confirm whether affected product deployments exist in managed environments and assign an owner for follow-up.
- Review the supplied official advisory or CVE record to validate affected scope, severity, and vendor guidance.
- Plan vendor-supported updates or mitigations through normal change control where exposure is confirmed.
- Check relevant monitoring, detection, and logs for exposed assets that need extra review.
Evidence notes
The vulnerability is caused by an out-of-bounds read in the Vlp32Decoder::unpack() function. The CVE record and NVD entry provide details on the vulnerability, but the exact affected versions and remediation steps are not specified.
Sources and references
Verified primary and authoritative sources
-
CVE-2026-74238 CVE Program record
Publisher, destination, and source semantics verified
URL: https://www.cve.org/CVERecord?id=CVE-2026-74238
CVE Program - Official CVE Program record with source-provided CVE metadata.
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CVE-2026-74238 NVD vulnerability detail
Publisher, destination, and source semantics verified
URL: https://nvd.nist.gov/vuln/detail/CVE-2026-74238
NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.
Supplemental references
-
Source reference
Unverified legacy reference
URL: https://github.com/tier4/nebula/issues/488
-
Source reference
Unverified legacy reference
URL: https://www.vulncheck.com/advisories/tier-iv-nebula-heap-out-of-bounds-read-via-vlp32-udp-decoder
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.