CVE-2026-33879: CWE-307: Improper Restriction of Excessive Authentication Attempts in londonaicentre FLIP
Federated Learning and Interoperability Platform (FLIP) is an open-source platform for federated training and evaluation of medical imaging AI models across healthcare institutions. The FLIP login page in versions 0.1.1 and prior has no rate limiting or CAPTCHA, enabling brute-force and credential-stuffing attacks. FLIP users are external to the organization, increasing credential reuse risk. As of time of publication, it is unclear if a patch is available.
AI Analysis
Technical Summary
CVE-2026-33879 identifies a vulnerability in the FLIP platform (versions 0.1.1 and prior) where the login interface does not implement any controls such as rate limiting or CAPTCHA to prevent excessive authentication attempts. This weakness (CWE-307) enables attackers to attempt brute-force or credential-stuffing attacks against user accounts. Since FLIP users are external to the organization, the risk of credential reuse exploitation is heightened. No official patch or fix has been confirmed as of the publication date.
Potential Impact
The vulnerability allows attackers to perform unlimited authentication attempts without restriction, potentially leading to unauthorized access if weak or reused credentials are present. However, the overall severity is rated low (CVSS 2.7) due to the lack of additional privileges or direct system compromise indicated. No known exploits are reported in the wild at this time.
Mitigation Recommendations
Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Until a patch or official fix is available, organizations should consider implementing external mitigations such as web application firewalls with rate limiting rules or deploying CAPTCHA mechanisms on the login page if possible. Monitoring for unusual login activity may also help detect attempted abuse, but no vendor-provided mitigation is currently documented.
CVE-2026-33879: CWE-307: Improper Restriction of Excessive Authentication Attempts in londonaicentre FLIP
Description
Federated Learning and Interoperability Platform (FLIP) is an open-source platform for federated training and evaluation of medical imaging AI models across healthcare institutions. The FLIP login page in versions 0.1.1 and prior has no rate limiting or CAPTCHA, enabling brute-force and credential-stuffing attacks. FLIP users are external to the organization, increasing credential reuse risk. As of time of publication, it is unclear if a patch is available.
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2026-33879 identifies a vulnerability in the FLIP platform (versions 0.1.1 and prior) where the login interface does not implement any controls such as rate limiting or CAPTCHA to prevent excessive authentication attempts. This weakness (CWE-307) enables attackers to attempt brute-force or credential-stuffing attacks against user accounts. Since FLIP users are external to the organization, the risk of credential reuse exploitation is heightened. No official patch or fix has been confirmed as of the publication date.
Potential Impact
The vulnerability allows attackers to perform unlimited authentication attempts without restriction, potentially leading to unauthorized access if weak or reused credentials are present. However, the overall severity is rated low (CVSS 2.7) due to the lack of additional privileges or direct system compromise indicated. No known exploits are reported in the wild at this time.
Mitigation Recommendations
Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Until a patch or official fix is available, organizations should consider implementing external mitigations such as web application firewalls with rate limiting rules or deploying CAPTCHA mechanisms on the login page if possible. Monitoring for unusual login activity may also help detect attempted abuse, but no vendor-provided mitigation is currently documented.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- GitHub_M
- Date Reserved
- 2026-03-24T15:10:05.680Z
- Cvss Version
- 4.0
- State
- PUBLISHED
Threat ID: 69c6ec5f3c064ed76ff25045
Added to database: 3/27/2026, 8:45:19 PM
Last enriched: 4/4/2026, 11:01:59 AM
Last updated: 5/11/2026, 6:17:26 AM
Views: 64
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