CVE-2026-57876: GeoVision Camera Out-of-Bounds Write Denial of Service

Technical summary

CVE-2026-57876 is an out-of-bounds write vulnerability (CWE-787) in the onvif.cgi endpoint of affected GeoVision devices. The root cause is insufficient input validation and bounds checking when processing HTTP request bodies. An unauthenticated remote attacker can exploit this by crafting an HTTP request with excessive payload data that exceeds the expected buffer size. The resulting heap or stack corruption causes memory access violations, leading to process termination and denial of service. The network-accessible nature of the endpoint and lack of authentication requirements make this trivial to trigger from any network position.

Business impact

Deployment of GeoVision GV-LPC2011 and GV-LPC2211 cameras in security surveillance systems creates a single-point-of-failure risk. An attacker with network visibility to the camera can disable video monitoring for critical areas without authentication, evading detection. In mission-critical environments—data centers, perimeter security, retail loss prevention—such outages can obstruct incident response and enable physical theft or intrusion during the downtime window. Attackers may exploit this as a distraction technique during coordinated physical theft or sabotage.

Affected systems

GeoVision GV-LPC2011 and GV-LPC2211 network cameras running firmware version V1.12 and earlier are vulnerable. Organizations must identify all instances of these models in their surveillance infrastructure and confirm firmware versions. GeoVision's product line targeting IP-based video surveillance suggests these are embedded devices deployed across enterprise and SMB networks, often accessible from administrative network segments or (in poorly segmented deployments) from untrusted networks.

Exploitability

This vulnerability presents high exploitability risk. No authentication is required, the attack surface is the standard HTTP port exposed by the camera, and the exploit is a single malformed request—well within the capability of automated scanning and exploitation tools. The vulnerability does not require user interaction or advanced techniques. Public disclosure and a straightforward proof-of-concept are likely to appear rapidly, enabling mass exploitation. Network-level visibility to the camera endpoint is the only technical barrier; cameras in DMZs or accessible from the internet face immediate risk.

Remediation

Organizations must prioritize upgrading affected GeoVision cameras to a patched firmware version released by GeoVision. Consult the GeoVision advisory for version numbers and upgrade procedures. Until patches are available or applied, implement compensating network controls: restrict HTTP access to the camera endpoints via firewall rules, disable or isolate the onvif.cgi endpoint if not required for integration, and deploy network segmentation to limit camera accessibility to authorized administrative subnets only. Consider temporarily disabling affected cameras if they are not critical and cannot be secured.

Patch guidance

Obtain the latest firmware release from GeoVision that addresses this vulnerability for the GV-LPC2011 and GV-LPC2211 models. Verify the patched version against the official GeoVision security advisory. Test patches in a non-production environment to ensure compatibility with existing integrations (e.g., video management systems, ONVIF clients) before rolling out enterprise-wide. Plan maintenance windows to minimize surveillance gaps during firmware updates. Document the firmware version across all instances to establish compliance baseline.

Detection guidance

Monitor network traffic to GeoVision cameras for HTTP POST requests to onvif.cgi with unusually large Content-Length headers or payload sizes significantly exceeding expected ONVIF message sizes (typically kilobytes, not megabytes). Correlate such traffic with camera availability or restart events. Enable verbose logging on video management system integrations to detect unexpected camera disconnections. Host-based detection: monitor syslog or device logs from affected cameras for memory-related errors, segmentation faults, or abnormal process restarts coinciding with suspicious traffic. Intrusion detection systems may fingerprint exploitation attempts by payload size anomalies targeting the onvif.cgi path.

Why prioritize this

HIGH severity (CVSS 7.5) with unauthenticated remote exploitability in a network-exposed endpoint. Although the impact is limited to denial of service (no data breach or unauthorized access), the trivial attack vector and lack of user interaction make this a high-priority remediation candidate. Cameras are often overlooked in patch management programs, increasing organizational dwell time. The threat of coordinated outages during physical security incidents elevates business risk beyond the base CVSS score.

Risk score, explained

CVSS 3.1 score of 7.5 (HIGH) reflects: network-adjacent attack vector (AV:N), low attack complexity (AC:L), no privileges required (PR:N), no user interaction (UI:N), unchanged scope (S:U), no confidentiality impact (C:N), no integrity impact (I:N), but complete availability impact (A:H). The score appropriately captures the ease of exploitation and guaranteed denial of service, but does not account for the widespread blind spot in IoT device patch management or the potential for coordinated multi-camera outages in distributed surveillance deployments.

Frequently asked questions