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PatchSiren cyber security CVE debrief

CVE-2026-52759 Ghidra CVE debrief

CVE-2026-52759 is a MEDIUM severity vulnerability in Ghidra before 12.1.1. The vulnerability is caused by an uncontrolled memory allocation in the Mach-O binary parser, which allows attackers to cause a denial of service. An attacker can supply a crafted Mach-O binary with an arbitrarily large ncmds load command count value, forcing the parser to allocate excessive heap memory without validating file size, crashing the Ghidra JVM.

Vendor
Ghidra
Product
Unknown
CVSS
MEDIUM 6.7
CISA KEV
Not listed in stored evidence
Original CVE published
2026-06-10
Original CVE updated
2026-06-11
Advisory published
2026-06-10
Advisory updated
2026-06-11

Who should care

Users of Ghidra before version 12.1.1 should apply the patch to prevent denial of service attacks.

Technical summary

The vulnerability is caused by an uncontrolled memory allocation in the Mach-O binary parser. An attacker can supply a crafted Mach-O binary with an arbitrarily large ncmds load command count value, forcing the parser to allocate excessive heap memory without validating file size, crashing the Ghidra JVM.

Defensive priority

MEDIUM

Recommended defensive actions

  • Apply the patch by upgrading to Ghidra version 12.1.1 or later.
  • Restrict access to the Ghidra application to trusted users only.
  • Monitor the Ghidra application for unusual activity.

Evidence notes

The vulnerability was reported by [redacted] and is tracked by CVE-2026-52759.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-52759 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-52759

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

  • CVE-2026-52759 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-52759

    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.