CVE-2026-52751
Published: 10 June 2026
Summary
CVE-2026-52751 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Nsa Ghidra. Its CVSS base score is 8.6 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Client Execution (T1203); ranked at the 49.0th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-36009
Vulnerability details
Ghidra before 12.1 contains an unsafe deserialization vulnerability in client-side Shared-Project RMI connection code that allows unauthenticated remote code execution. Attackers can craft a malicious project file with a ghidra:// URL that, when opened via File → Open Project, deserializes…
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untrusted objects using a Jython 2.7.4 gadget chain to execute arbitrary commands.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Unsafe deserialization in Ghidra client directly enables client-side RCE (T1203) via opening a malicious project file/URL (T1204.002).
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Penetration testing supplies malicious serialized objects, detecting unsafe deserialization and supporting corrective actions.
Evaluation of untrusted data handling (deserialization testing) reveals unsafe processing, which the required remediation process addresses.
Untrusted serialized data can be deserialized and observed inside the chamber, blocking gadget-chain exploitation outside the sandbox.
Validates or rejects untrusted serialized data before deserialization occurs.
Identifies and blocks malicious code introduced through deserialization of untrusted data at system boundaries.
Integrity verification of serialized information can detect tampering before deserialization occurs.
Provenance of associated data allows detection of untrusted sources before deserialization or processing occurs.