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CVE-2026-40917 Red Hat CVE debrief

A flaw was found in GIMP, a heap buffer over-read in the `icns_slurp()` function when processing specially crafted ICNS image files. This could lead to application crashes or information disclosure. The vulnerability is triggered by a specially crafted ICNS file, which can cause the `icns_slurp()` function to read beyond the bounds of the heap buffer. This can result in the application crashing or potentially disclosing information from the heap memory. Defenders should be aware of the potential for application instability and information disclosure, particularly in systems that process ICNS files using GIMP.

Vendor
Red Hat
Product
Red Hat Enterprise Linux 6
CVSS
MEDIUM 5
CISA KEV
Not listed in stored evidence
Original CVE published
2026-04-15
Original CVE updated
2026-10-26
Advisory published
2026-04-15
Advisory updated
2026-10-26

Who should care

Defenders responsible for systems that process ICNS files, particularly those using GIMP, should assess exposure and prioritize patching or mitigation. This includes operators of systems that use GIMP to process ICNS files, as well as security teams and vulnerability management teams that oversee the security of these systems. Additionally, platform administrators and security personnel should be aware of the potential for application instability and

Why it matters

Defenders should prioritize patching or mitigating this vulnerability in GIMP installations that process ICNS files, as it could lead to application instability or information disclosure.

  • Potential application crashes due to malicious ICNS file processing
  • Possible information disclosure from heap memory

Technical summary

The `icns_slurp()` function in GIMP is vulnerable to a heap buffer over-read when processing specially crafted ICNS image files, potentially leading to application crashes or information disclosure. The vulnerability is caused by a lack of proper bounds checking in the `icns_slurp()` function, which can result in the application reading beyond the bounds of the heap buffer. This can lead to application instability or potentially disclose information from the heap memory. Defenders should prioritize patching or mitigating this vulnerability in GIMP installations that process ICNS files.

Defensive priority

Medium priority for systems processing ICNS files

Recommended defensive actions

  • Assess exposure for systems processing ICNS files
  • Verify GIMP version and apply patches if available
  • Monitor for suspicious ICNS file processing activity
  • Review compensating controls for exposed systems while remediation is scheduled and verified
  • 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

Evidence notes

The CVE record and NVD entry provide details on the vulnerability, but specific version information and exploitation details are limited. The `icns_slurp()` function in GIMP is vulnerable to a heap buffer over-read when processing specially crafted ICNS image files. The CVE Program and NVD have documented this vulnerability, but additional information from other sources is needed to fully understand the impact and potential mitigations. Defenders should verify GIMP version and apply patches if available, and monitor for suspicious ICN

Sources and references

Verified primary and authoritative sources

  • CVE-2026-40917 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-40917

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

  • CVE-2026-40917 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-40917

    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.