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GeoVision GV-VMS EUVDEUVD-2026-38645

| CVE-2026-12488 MEDIUM
Stack-based Buffer Overflow (CWE-121)
2026-06-24 GV GHSA-7j74-f2vx-3rfg
6.2
CVSS 3.1 · Vendor: GV
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Severity by source

Vendor (GV) PRIMARY
6.2 MEDIUM
AV:N/AC:H/PR:H/UI:R/S:C/C:L/I:N/A:H
vuln.today AI
6.1 MEDIUM

Server impersonation requires MitM network positioning (AC:H) but no privileges on the target (PR:N); impact is confirmed DoS only, with no confidentiality or integrity effect described.

3.1 AV:N/AC:H/PR:N/UI:R/S:C/C:N/I:N/A:H
4.0 AV:N/AC:H/AT:P/PR:N/UI:A/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

Primary rating from Vendor (GV).

CVSS VectorVendor: GV

Attack Vector
Network
Attack Complexity
High
Privileges Required
High
User Interaction
Required
Scope
Changed
Confidentiality
Low
Integrity
None
Availability
High

Lifecycle Timeline

1
Analysis Generated
Jun 24, 2026 - 05:34 vuln.today

DescriptionCVE.org

A memory corruption vulnerability exists in the GV-Cloud functionality of GeoVision GV-VMS V20 20.0.2.

A specially crafted network request can lead to a denial of service. An attacker can impersonate the legitimate server to trigger this vulnerability.

AnalysisAI

Stack-based buffer overflow (CWE-121) in the GV-Cloud component of GeoVision GV-VMS V20 20.0.2 enables a remote attacker with a network-intercept position to crash the video management system, causing high-impact denial of service against physical security infrastructure. Exploitation requires impersonating the legitimate GV-Cloud server - achieved via MitM techniques - and delivering a specially crafted network payload that corrupts stack memory in the GV-Cloud client handler. Reported by Cisco Talos (TALOS-2026-2411); no public exploit has been identified at time of analysis and no CISA KEV listing exists.

Technical ContextAI

GeoVision GV-VMS (Video Management System) V20 is a physical-security platform for managing IP cameras, recordings, and alarms; its GV-Cloud feature provides remote cloud connectivity for management, remote viewing, and telemetry. The GV-Cloud client component initiates outbound connections to a cloud endpoint and processes server responses. The root cause is CWE-121 (Stack-based Buffer Overflow): the client fails to enforce appropriate size bounds on incoming server response data, allowing an adversary-controlled response to overwrite adjacent stack frames and corrupt execution state. The affected product is identified by CPE cpe:2.3:a:geovision_inc.:geovision:*:*:*:*:*:*:*:*, where the wildcard version field indicates the precise patched boundary is not bounded by the available CPE data alone. Because the vulnerable code path is exercised only when the GV-VMS host connects to a cloud server, the attack surface is limited to the client-to-cloud communication channel.

RemediationAI

Consult the GeoVision security advisory at https://www.geovision.com.tw/cyber_security.php for the specific patched GV-VMS release - no exact fixed version number is independently confirmed in the available intelligence, so the advisory page must be checked directly. Upgrading to the vendor-released patched version is the primary recommended action. As a high-priority compensating control, disable the GV-Cloud feature entirely on any GV-VMS deployment where remote cloud connectivity is not operationally required; this eliminates the attack surface completely at the cost of losing cloud management and remote-viewing capabilities. Where GV-Cloud must remain enabled, implement firewall ACL rules restricting the GV-VMS host's outbound TCP connections to only the documented GeoVision cloud server IP ranges, preventing arbitrary server impersonation via rogue endpoints. Enforcing TLS certificate validation and pinning for cloud server connections - if configurable in GV-VMS - would neutralize the impersonation vector, but configuration availability should be confirmed with the vendor. Segment the GV-VMS host on a dedicated VLAN with strict ingress filtering to reduce MitM exposure.

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EUVD-2026-38645 vulnerability details – vuln.today

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