CVE-2025-65328
Unknown Unknown - Not Provided
BaseFortify

Publication date: 2026-01-05

Last updated on: 2026-01-08

Assigner: MITRE

Description
Mega-Fence (webgate-lib.*) 25.1.914 and prior trusts the first value of the X-Forwarded-For (XFF) header as the client IP without validating a trusted proxy chain. An attacker can supply an arbitrary XFF value in a remote request to spoof the client IP, which is then propagated to security-relevant state (e.g., WG_CLIENT_IP cookie). Deployments that rely on this value for IP allowlists may be bypassed.
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Meta Information
Published
2026-01-05
Last Modified
2026-01-08
Generated
2026-05-07
AI Q&A
2026-01-05
EPSS Evaluated
2026-05-05
NVD
EUVD
Affected Vendors & Products
Showing 1 associated CPE
Vendor Product Version / Range
webgate mega-fence to 25.1.914 (exc)
Helpful Resources
Exploitability
CWE
CWE Icon
KEV
KEV Icon
CWE ID Description
CWE-807 The product uses a protection mechanism that relies on the existence or values of an input, but the input can be modified by an untrusted actor in a way that bypasses the protection mechanism.
Attack-Flow Graph
AI Powered Q&A
Can you explain this vulnerability to me?

CVE-2025-65328 is a vulnerability in Mega-Fence (webgate-lib.*) versions 25.1.914 and earlier where the software trusts the first value of the X-Forwarded-For (XFF) HTTP header as the client IP address without validating if the request comes from a trusted proxy. This allows an attacker to send a crafted XFF header to spoof the client IP address. The spoofed IP is then used in security-relevant contexts such as the WG_CLIENT_IP cookie. This can lead to bypassing IP-based allowlists, evading audit trails, and circumventing rate limiting or abuse detection if the deployment relies on this IP for security decisions. [1]


How can this vulnerability impact me? :

This vulnerability can impact you by allowing attackers to spoof their client IP address, which can bypass IP-based allowlists or administrative restrictions. It can also undermine audit trails and log attribution, making it harder to track malicious activity. Additionally, attackers may evade rate limiting or abuse detection mechanisms that rely on the client IP address, potentially leading to increased abuse or unauthorized access. [1]


How can this vulnerability be detected on my network or system? Can you suggest some commands?

You can detect this vulnerability by monitoring HTTP requests for suspicious or arbitrary X-Forwarded-For headers that do not match your trusted proxy IP ranges. For example, you can capture and inspect HTTP traffic using tools like tcpdump or Wireshark to look for X-Forwarded-For headers with unexpected IP addresses. A sample tcpdump command to capture HTTP headers is: tcpdump -A -s 0 'tcp port 80 or tcp port 443' | grep -i 'X-Forwarded-For'. Additionally, check your web server or application logs for WG_CLIENT_IP cookie values that do not correspond to legitimate client IPs or trusted proxies. This can help identify spoofed client IPs being propagated. [1]


What immediate steps should I take to mitigate this vulnerability?

Immediate mitigation steps include: 1) Configure your system to only trust and parse X-Forwarded-For headers when the REMOTE_ADDR (the direct client IP) is within a configured trusted proxy CIDR range. 2) Implement a strict and documented precedence order for IP-related headers such as Forwarded, X-Forwarded-For, and X-Real-IP. 3) Default to ignoring client-supplied IP headers unless explicitly enabled and documented. 4) Clearly document how client IP addresses are determined and the trust assumptions involved. These steps help prevent attackers from spoofing client IP addresses via crafted X-Forwarded-For headers and reduce the risk of bypassing IP-based allowlists or security controls. [1]


How does this vulnerability affect compliance with common standards and regulations (like GDPR, HIPAA)?:

This vulnerability can undermine IP-based access controls, auditing, and abuse prevention mechanisms by allowing an attacker to spoof client IP addresses. Such spoofing can lead to inaccurate audit trails and potentially bypass security controls that are important for compliance with standards like GDPR and HIPAA, which require accurate logging and protection of access controls. Therefore, deployments relying on the vulnerable behavior may face challenges in maintaining compliance with these regulations unless mitigations are applied. [1]


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