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PatchSiren cyber security CVE debrief

CVE-2026-120252 cgohlke CVE debrief

A stack-based buffer overflow vulnerability exists in the imagecodecs library, specifically in the lossless JPEG Define Huffman Table parser. This vulnerability can cause a crash when processing a crafted lossless JPEG image. The imagecodecs library is used in various applications, and defenders should verify library versions and implement input validation to prevent potential crashes. The vulnerability was discovered in imagecodecs 2023.1.23 through 2026.10.10, and further verification is needed to determine the full scope of affected versions and potential impact.

Vendor
cgohlke
Product
imagecodecs
CVSS
MEDIUM 6.8
CISA KEV
Not listed in stored evidence
Original CVE published
2026-11-01
Original CVE updated
2026-11-01
Advisory published
2026-11-01
Advisory updated
2026-11-01

Who should care

Defenders responsible for imagecodecs library maintenance and deployment, as well as developers and users of applications that utilize this library, should be aware of this vulnerability and take steps to verify and update the library to prevent potential crashes.

Why it matters

CVE-2026-120252 is a stack-based buffer overflow vulnerability in the imagecodecs library that can cause crashes from crafted JPEG images. Defenders should verify library versions, implement input validation, and update to fixed versions to prevent potential impact.

  • Potential crashes from crafted JPEG images require verification and updates to the imagecodecs library
  • Defenders should verify library versions and implement input validation and error handling for JPEG image processing

Technical summary

The imagecodecs library contains a stack-based buffer overflow vulnerability in the lossless JPEG Define Huffman Table parser. This vulnerability can be triggered by a crafted lossless JPEG image, causing a crash in the calling process. The vulnerability is caused by the DHT symbol counts wrapping an 8-bit sum, overflowing the 32-entry HufVal and HufSz stack arrays. Defenders should prioritize verifying and updating the imagecodecs library to prevent potential crashes from crafted JPEG images. The CVE record and NVD entry provide details on the vulnerability, but further verification is needed to determine the full scope of affected versions and potential impact.

Defensive priority

Defenders should prioritize verifying and updating the imagecodecs library to prevent potential crashes from crafted JPEG images.

Recommended defensive actions

  • Verify the imagecodecs library version and update to a fixed version if necessary
  • Review and monitor imagecodecs library usage in the environment
  • Implement input validation and error handling for JPEG image processing
  • Check relevant monitoring, detection, and logs for exposed assets that need extra review
  • Track exceptions, retest remediated assets, and close the item only after evidence is documented
  • 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

Evidence notes

The vulnerability was discovered in imagecodecs 2023.1.23 through 2026.10.10. The CVE record and NVD entry provide details on the vulnerability, but further verification is needed to determine the full scope of affected versions and potential impact.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-120252 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-120252

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

  • CVE-2026-120252 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-120252

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

Supplemental references

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.