← Back to search

CVE-2026-92190

9.8 CRITICAL

Published 2026-11-04 · Updated 2026-11-04

AI risk analysis

Summary
The vulnerability stems from unsafe deserialization of untrusted data in the baseRmiServiceExporter bean of Quest Foglight for Databases, allowing remote attackers to execute arbitrary code without authentication by crafting malicious serialized objects.
Exploitability
Exploitation is straightforward for remote attackers due to the lack of authentication and weak input validation; no user interaction or privileged access is required.
Blast radius
Successful exploitation grants SYSTEM-level code execution on the affected server, enabling full compromise of confidentiality, integrity, and availability of the host and potentially connected database environments.
Detection
No reliable host or network indicator is derivable from the published description.
Prioritized remediation
Upgrade to Quest Foglight for Databases version 2.590 or later, where this deserialization flaw has been patched.
rcedeserializationuntrusted-inputno-authsystem-access

Analysis generated locally by garnet-coder (no data left the box). AI-assisted — verify against primary sources before acting.

NVD description

Quest Foglight for Databases baseRmiServiceExporter Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Quest Foglight for Databases. Authentication is not required to exploit this vulnerability. The specific flaw exists within the configuration of the baseRmiServiceExporter bean. The issue results from the lack of proper validation of user-supplied data prior to deserializing it. An attacker can leverage this vulnerability to execute code in the context of SYSTEM. Was ZDI-CAN-29170.

CVSS vector

CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Weaknesses

CWE-502

All references

Source data: NVD (nvd.nist.gov), public domain. Exploit-DB.ai adds local AI analysis for defensive use only.

Related CVEs

Related by shared AI tags and CWE weakness class. Browse the full archive.