CVE-2025-41765 Overview
CVE-2025-41765 is a critical authorization bypass vulnerability affecting MBS Solutions Universal BACnet Router Firmware. Due to insufficient authorization enforcement, an unauthorized remote attacker can exploit the wwwupload.cgi endpoint to upload and apply arbitrary data. This includes, but is not limited to, contact images, HTTPS certificates, system backups for restoration, server peer configurations, and BACnet/SC server certificates and keys.
This vulnerability affects industrial control system (ICS) and building automation devices, making it particularly concerning for critical infrastructure environments that rely on BACnet protocol communications.
Critical Impact
Unauthenticated attackers can remotely upload malicious configurations, certificates, and system backups, potentially gaining complete control over building automation network infrastructure.
Affected Products
- MBS Solutions Universal BACnet Router Firmware (all versions)
- MBS Solutions UBR-01 MK II
- MBS Solutions UBR-02
- MBS Solutions UBR-LON
Discovery Timeline
- 2026-03-09 - CVE-2025-41765 published to NVD
- 2026-03-11 - Last updated in NVD database
Technical Details for CVE-2025-41765
Vulnerability Analysis
This vulnerability is classified under CWE-862 (Missing Authorization), indicating that the affected endpoint fails to verify that the requesting user has the necessary privileges to perform the requested action. The wwwupload.cgi endpoint processes file uploads without implementing proper authentication or authorization checks, allowing any network-accessible attacker to upload arbitrary content.
The impact of this vulnerability is severe because it allows attackers to manipulate critical system components including HTTPS certificates (enabling man-in-the-middle attacks), system backup files (allowing configuration manipulation), server peer configurations (disrupting network communications), and BACnet/SC certificates and keys (compromising building automation security).
Root Cause
The root cause of this vulnerability is the missing authorization check in the wwwupload.cgi CGI script handler. The firmware fails to validate whether incoming requests originate from authenticated administrative sessions before processing upload operations. This design flaw allows unauthenticated users to access functionality that should be restricted to authorized administrators only.
Attack Vector
The vulnerability is exploitable over the network without requiring any authentication or user interaction. An attacker with network access to the device's web interface can craft HTTP POST requests to the wwwupload.cgi endpoint to upload malicious files.
The attack flow involves:
- Identifying a vulnerable MBS Solutions BACnet router on the network
- Sending crafted HTTP POST requests to the wwwupload.cgi endpoint
- Uploading malicious content such as modified system backups, rogue certificates, or manipulated configurations
- The device processes and applies the uploaded content without authorization verification
Successful exploitation could allow an attacker to compromise HTTPS communications by uploading rogue certificates, restore malicious system configurations, modify BACnet/SC security settings, or disrupt building automation communications.
Detection Methods for CVE-2025-41765
Indicators of Compromise
- Unexpected HTTP POST requests to /wwwupload.cgi or similar upload endpoints on BACnet router devices
- Certificate changes on devices without corresponding administrative activity
- Unexpected system restoration or configuration modifications
- Anomalous network traffic patterns targeting BACnet router web interfaces
Detection Strategies
- Monitor network traffic for unauthenticated requests to the wwwupload.cgi endpoint
- Implement intrusion detection signatures for HTTP POST requests containing certificate or backup file content targeting BACnet routers
- Review web server access logs on affected devices for suspicious upload activity
- Deploy network segmentation monitoring to detect unauthorized access attempts to ICS/SCADA network segments
Monitoring Recommendations
- Establish baseline network behavior for BACnet router administrative interfaces
- Configure alerts for any certificate or configuration changes on affected devices
- Implement continuous monitoring of building automation network segments for unauthorized access
- Deploy SentinelOne Singularity platform for endpoint visibility and threat detection across OT environments
How to Mitigate CVE-2025-41765
Immediate Actions Required
- Restrict network access to affected devices using firewall rules and network segmentation
- Isolate MBS Solutions BACnet routers from untrusted networks immediately
- Monitor all access attempts to the wwwupload.cgi endpoint
- Review device configurations and certificates for unauthorized modifications
- Contact MBS Solutions for updated firmware containing security fixes
Patch Information
MBS Solutions has released a security advisory addressing this vulnerability. Refer to the MBS Solutions Security Advisory for detailed patch information and updated firmware versions. Organizations should prioritize applying the vendor-provided security updates to all affected devices.
Workarounds
- Implement strict network segmentation to prevent untrusted networks from accessing BACnet router management interfaces
- Deploy a web application firewall (WAF) or reverse proxy to filter and block requests to the vulnerable wwwupload.cgi endpoint
- Enable access control lists (ACLs) on network infrastructure to restrict management interface access to authorized IP addresses only
- Consider disabling the web management interface temporarily if not required for operations
# Example firewall rule to restrict access to BACnet router management
# Replace <MANAGEMENT_SUBNET> with your authorized management network
iptables -A INPUT -p tcp --dport 80 -s <MANAGEMENT_SUBNET> -j ACCEPT
iptables -A INPUT -p tcp --dport 443 -s <MANAGEMENT_SUBNET> -j ACCEPT
iptables -A INPUT -p tcp --dport 80 -j DROP
iptables -A INPUT -p tcp --dport 443 -j DROP
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.


