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CVE Vulnerability Database
Vulnerability Database/CVE-2025-52487

CVE-2025-52487: DNN Platform Auth Bypass Vulnerability

CVE-2025-52487 is an authentication bypass vulnerability in DNN Platform that allows attackers to circumvent IP filter restrictions. This article covers the technical details, affected versions, and mitigation strategies.

Updated:

CVE-2025-52487 Overview

CVE-2025-52487 affects DNN Platform (formerly DotNetNuke), an open-source content management system (CMS) built on the Microsoft .NET stack. The vulnerability allows attackers to bypass the DNN Login IP Filter mechanism by submitting a specially crafted request or routing traffic through a proxy. Affected versions span 7.0.0 through any release prior to 10.0.1. Successful exploitation lets unauthorized IP addresses attempt logins despite explicit allow-list restrictions. The flaw is categorized under [CWE-863]: Incorrect Authorization. DNN maintainers fixed the issue in version 10.0.1.

Critical Impact

Remote unauthenticated attackers can bypass IP allow-list controls protecting DNN administrator login endpoints, enabling brute-force and credential-stuffing attacks against accounts that should be unreachable.

Affected Products

  • DNN Platform (DotNetNuke) versions 7.0.0 through 10.0.0
  • DNN.PLATFORM Login IP Filter component
  • All DNN deployments behind a reverse proxy or load balancer

Discovery Timeline

  • 2025-06-21 - CVE-2025-52487 published to NVD
  • 2025-09-15 - Last updated in NVD database

Technical Details for CVE-2025-52487

Vulnerability Analysis

The vulnerability resides in the DNN Login IP Filter authorization control. DNN administrators configure this filter to restrict login attempts to a defined allow list of source IP addresses. The filter logic determines the client IP from request headers but does not adequately validate the trust boundary of those headers. An attacker who controls request headers such as X-Forwarded-For can supply a spoofed source IP that matches the allow list. The filter accepts the attacker-controlled value and grants access to the login form. This is an authorization flaw mapped to [CWE-863], where the access decision relies on untrusted input. Because the bypass operates at the network filter layer, it precedes credential validation and exposes the underlying authentication endpoint to attacks that the IP filter was designed to prevent.

Root Cause

The root cause is improper handling of client IP determination when DNN runs behind a proxy or load balancer. The application trusts forwarded-IP headers without verifying that the request originated from an authorized upstream proxy. Any anonymous network client can therefore inject a header value to impersonate a permitted source.

Attack Vector

The attack vector is network-based and requires no authentication or user interaction. An attacker sends an HTTP request to the DNN login endpoint with a crafted proxy header containing an allow-listed IP address. The filter evaluates the spoofed header, approves the request, and forwards it to the login handler. The attacker then attempts credential brute force, password spraying, or credential stuffing against the exposed authentication endpoint. Refer to the DNN GitHub Security Advisory GHSA-fjhg-3mrh-mm7h for vendor-confirmed details.

Detection Methods for CVE-2025-52487

Indicators of Compromise

  • Login attempts in DNN event logs originating from IP addresses that match the allow list but correlate with unexpected geographic regions or user agents.
  • Inbound HTTP requests to /Login.aspx or /Default.aspx?tabid=* containing X-Forwarded-For, X-Real-IP, or Forwarded headers from untrusted upstream sources.
  • Repeated failed authentication events targeting administrator accounts following header anomalies.
  • Sudden increases in 401 or 403 responses on login endpoints from clients claiming allow-listed source IPs.

Detection Strategies

  • Inspect web server and IIS logs for requests containing forwarded-IP headers that did not transit a known reverse proxy.
  • Correlate the TCP source IP recorded by the load balancer with the IP value enforced by the DNN filter and alert on mismatches.
  • Baseline normal login source IPs and flag deviations even when filter checks succeed.

Monitoring Recommendations

  • Forward IIS, DNN application, and reverse proxy logs to a centralized analytics platform for correlation.
  • Enable DNN audit logging for authentication events and review administrator login activity daily.
  • Monitor for high-volume authentication attempts against /Login paths and alert on credential-stuffing patterns.

How to Mitigate CVE-2025-52487

Immediate Actions Required

  • Upgrade DNN Platform to version 10.0.1 or later, which contains the official fix.
  • Audit the DNN Login IP Filter configuration and confirm the allow list reflects current administrative source IPs only.
  • Restrict access to the DNN administrator login endpoint at the network or web application firewall (WAF) layer until patching completes.
  • Rotate administrator credentials and enable multi-factor authentication (MFA) on all privileged DNN accounts.

Patch Information

DNN Platform version 10.0.1 resolves the IP filter bypass. The vendor advisory is published as GHSA-fjhg-3mrh-mm7h. Administrators should review release notes and apply the upgrade following standard DNN upgrade procedures, including database backup and site verification post-deployment.

Workarounds

  • Configure the upstream reverse proxy or WAF to strip inbound X-Forwarded-For, X-Real-IP, and Forwarded headers and inject trusted values.
  • Enforce IP allow-list restrictions at the network firewall or WAF layer rather than relying solely on the DNN application filter.
  • Require MFA for all administrative accounts to limit the impact of any successful bypass.
bash
# Example: strip and replace forwarded headers at an nginx reverse proxy
location /Login.aspx {
    proxy_set_header X-Forwarded-For $remote_addr;
    proxy_set_header X-Real-IP $remote_addr;
    proxy_set_header Forwarded "";
    proxy_pass http://dnn_backend;
}

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

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