CVE-2026-33879: FLIP Auth Bypass Vulnerability

CVE-2026-33879 Overview

CVE-2026-33879 is a Missing Rate Limiting vulnerability affecting the Federated Learning and Interoperability Platform (FLIP), an open-source platform designed for federated training and evaluation of medical imaging AI models across healthcare institutions. The FLIP login page in versions 0.1.1 and prior lacks rate limiting or CAPTCHA protection, enabling brute-force and credential-stuffing attacks against the authentication system.

Critical Impact

Healthcare institutions using FLIP are vulnerable to credential-based attacks. Since FLIP users are external to the organization, there is an elevated risk of credential reuse from previous data breaches being exploited to gain unauthorized access to sensitive medical AI training systems.

Affected Products

• Federated Learning and Interoperability Platform (FLIP) version 0.1.1 and prior
• FLIP login authentication endpoint
• Healthcare institutions using FLIP for federated medical imaging AI

Discovery Timeline

• 2026-03-27 - CVE CVE-2026-33879 published to NVD
• 2026-03-30 - Last updated in NVD database

Technical Details for CVE-2026-33879

Vulnerability Analysis

This vulnerability is classified under CWE-307 (Improper Restriction of Excessive Authentication Attempts). The FLIP login page does not implement any mechanism to restrict the number of authentication attempts a user can make, nor does it employ CAPTCHA or similar challenge-response tests to distinguish between human users and automated attack tools.

The absence of rate limiting on authentication endpoints is particularly concerning in the context of healthcare applications. FLIP is designed to facilitate federated learning across multiple healthcare institutions, meaning that external users from various organizations interact with the platform. This external user base significantly increases the risk of credential reuse attacks, where attackers leverage credentials exposed in previous data breaches to attempt access to FLIP instances.

Root Cause

The root cause of this vulnerability is the lack of defensive mechanisms on the authentication endpoint. The FLIP login functionality was implemented without:

• Request rate limiting to throttle repeated authentication attempts
• Account lockout policies after failed login attempts
• CAPTCHA or other challenge-response mechanisms
• Adaptive authentication controls that respond to suspicious activity patterns

This design oversight allows attackers to submit unlimited authentication requests without triggering any protective measures.

Attack Vector

The attack vector is network-based, requiring no authentication or user interaction. An attacker can target FLIP instances exposed to the network by:

1. Brute-force attacks: Systematically attempting common passwords against known usernames until valid credentials are discovered
2. Credential stuffing: Using automated tools to test username/password combinations obtained from previous data breaches against FLIP login endpoints
3. Password spraying: Attempting a small number of commonly used passwords against many accounts to avoid detection

The vulnerability is exploitable through standard HTTP requests to the login endpoint. Attackers can leverage readily available tools such as Hydra, Burp Suite Intruder, or custom scripts to automate the attack process. The lack of rate limiting means thousands of authentication attempts can be made in rapid succession without being blocked.

For technical details regarding the vulnerability mechanism, see the GitHub Security Advisory.

Detection Methods for CVE-2026-33879

Indicators of Compromise

• High volume of failed authentication attempts from single IP addresses or IP ranges
• Unusual login patterns outside normal business hours or from unexpected geographic locations
• Multiple accounts experiencing failed login attempts in rapid succession
• Authentication logs showing sequential or patterned password attempts against user accounts
• Successful logins following numerous failed attempts from the same source

Detection Strategies

• Implement log aggregation and analysis for authentication events on FLIP instances
• Configure SIEM alerts for threshold-based detection of failed login attempts
• Monitor for distributed attack patterns where multiple source IPs target the same accounts
• Deploy web application firewalls (WAF) with anomaly detection capabilities
• Utilize threat intelligence feeds to identify known malicious IP addresses attempting authentication

Monitoring Recommendations

• Enable detailed authentication logging including source IP, timestamp, username, and attempt status
• Establish baseline metrics for normal authentication activity to identify anomalies
• Configure real-time alerting for authentication attempt thresholds exceeding normal patterns
• Implement geographic and time-based anomaly detection for login attempts

How to Mitigate CVE-2026-33879

Immediate Actions Required

• Audit authentication logs for signs of ongoing or previous brute-force or credential-stuffing attacks
• Implement network-level rate limiting using reverse proxy or WAF configurations as an interim measure
• Enforce strong password policies and multi-factor authentication (MFA) for all FLIP users
• Consider IP allowlisting to restrict access to known healthcare institution networks
• Monitor the FLIP project repository for security updates and patches

Patch Information

As of the publication date, it is unclear if an official patch is available from the FLIP project maintainers. Organizations should monitor the GitHub Security Advisory for updates on remediation guidance.

SentinelOne customers benefit from proactive threat detection capabilities that can identify credential-based attack patterns. The SentinelOne Singularity platform provides behavioral analysis that can detect anomalous authentication activity indicative of brute-force or credential-stuffing attacks, offering an additional layer of protection while awaiting an official patch.

Workarounds

• Deploy a reverse proxy (such as nginx or HAProxy) in front of FLIP with rate limiting configured for the login endpoint
• Implement fail2ban or similar tools to automatically block IP addresses after repeated failed authentication attempts
• Add CAPTCHA protection at the network perimeter using a WAF or application gateway
• Require VPN access for all FLIP authentication to reduce the attack surface
• Implement multi-factor authentication as an additional layer regardless of rate limiting status

# Example nginx rate limiting configuration for FLIP login endpoint
# Add to nginx server configuration block

limit_req_zone $binary_remote_addr zone=flip_login:10m rate=5r/m;

location /login {
    limit_req zone=flip_login burst=3 nodelay;
    limit_req_status 429;
    # proxy_pass to FLIP backend
}