CVE-2023-54347: 
OpenEMR vulnerability analysis and mitigation

CVE-2023-54347 is an authentication brute force vulnerability in OpenEMR 7.0.1 that allows unauthenticated attackers to bypass rate limiting protections on the main login endpoint. By submitting repeated POST requests with authUser and clearPass parameters, attackers can systematically enumerate username and password combinations without triggering account lockout restrictions. The vulnerability was published to the NVD and GitHub Advisory Database on May 5, 2026, and is assigned a CVSS v3.1 score of 7.5 (High) and a CVSS v4.0 score of 8.7 (High) (Github Advisory).

The root cause is classified as CWE-307 (Improper Restriction of Excessive Authentication Attempts), meaning OpenEMR 7.0.1 fails to implement sufficient controls — such as account lockout, CAPTCHA, or effective rate limiting — to prevent repeated failed login attempts (Github Advisory). An attacker exploits this by sending automated HTTP POST requests to the OpenEMR login endpoint, supplying different authUser and clearPass values in each request to perform dictionary attacks, password spraying, or credential stuffing. No authentication or special privileges are required, and the attack can be conducted entirely over the network with no user interaction. A public exploit entry exists on Exploit-DB (EDB-51413), referenced by VulnCheck's advisory (VulnCheck Advisory).

Successful exploitation allows an unauthenticated remote attacker to discover valid credentials for OpenEMR accounts, resulting in a high confidentiality impact. OpenEMR is an electronic medical records and practice management system, so compromised credentials could expose sensitive protected health information (PHI), patient records, billing data, and clinical notes. There is no direct integrity or availability impact from the brute force itself, but account takeover could enable further unauthorized actions within the application, including data exfiltration or modification of medical records (Github Advisory).

1. Reconnaissance: Identify internet-facing OpenEMR 7.0.1 instances using search engines like Shodan or Censys, or by scanning for the OpenEMR login page (typically at /openemr/interface/login/login.php or similar paths).
2. Enumerate valid usernames: Optionally attempt to identify valid usernames by observing differences in application responses to login attempts with known versus unknown usernames.
3. Craft brute force requests: Prepare a list of candidate passwords (wordlist or credential dump) and construct HTTP POST requests targeting the login endpoint with authUser and clearPass parameters.
4. Submit automated login attempts: Use tools such as hydra, burp suite intruder, or a custom script to send repeated POST requests without triggering account lockout, exploiting the absence of effective rate limiting.
5. Identify valid credentials: Monitor HTTP responses for indicators of successful authentication (e.g., session cookies, redirect to dashboard) to identify valid username/password combinations.
6. Access the application: Use the discovered credentials to log in to OpenEMR and access patient records, administrative functions, or other sensitive data (Github Advisory, VulnCheck Advisory).

• Network: High volume of HTTP POST requests to the OpenEMR login endpoint (e.g., /openemr/interface/login/login.php) from a single or small set of IP addresses in a short time window; requests with varying authUser and clearPass parameter values.
• Logs: Web server access logs showing hundreds or thousands of POST requests to the login endpoint with HTTP 200 or 302 responses; repeated failed authentication entries in OpenEMR application logs from the same source IP.
• Application: Sudden successful login from an IP address that previously generated many failed attempts; login activity at unusual hours or from unexpected geographic locations.

Organizations should update OpenEMR to a patched version that implements proper rate limiting and account lockout on the login endpoint; the GitHub advisory references the v7.0.1 source but does not specify a fixed version number, so administrators should monitor the OpenEMR project for patch releases (Github Advisory). As interim mitigations, implement IP-based rate limiting or CAPTCHA challenges at the web server or WAF level to throttle repeated login attempts. Additionally, restrict access to the OpenEMR login page to trusted IP ranges where operationally feasible, and enable multi-factor authentication if supported by the deployment.

VulnCheck published an advisory documenting the vulnerability and its impact on OpenEMR's authentication mechanism (VulnCheck Advisory). The GitHub Advisory Database classified the issue as High severity but marked it as "Unreviewed" with no confirmed patched version listed. No significant broader media coverage or notable researcher commentary beyond the initial disclosure has been identified.