CVE-2025-40916 identifies a cryptographic weakness in the GRYPHON Mojolicious::Plugin::CaptchaPNG version 1.05, a Perl plugin used to generate CAPTCHA images. The vulnerability arises from the use of Perl's built-in rand() function as the source of randomness for both the CAPTCHA text and the image noise. The rand() function is a pseudo-random number generator (PRNG) that is not designed for cryptographic purposes and is considered weak because it produces predictable sequences if the internal state or seed can be inferred. This weakness falls under CWE-338, which concerns the use of cryptographically weak PRNGs. The insecure randomness undermines the security of the CAPTCHA mechanism, potentially allowing attackers to predict or reproduce CAPTCHA challenges, thereby bypassing the CAPTCHA protection. This can facilitate automated attacks such as credential stuffing, brute force login attempts, or spam submissions on web applications relying on this plugin. No known exploits have been reported in the wild as of the publication date (June 16, 2025), and no official patch or mitigation has been released yet. The vulnerability is specific to version 1.05 of the plugin and does not affect other versions unless they use the same weak random source. Since CAPTCHA is a common defense mechanism against automated abuse, the weakness in randomness directly impacts the integrity and effectiveness of this security control.

For European organizations, the impact of this vulnerability can be significant, especially for those relying on Mojolicious::Plugin::CaptchaPNG 1.05 to protect web forms, login pages, or other user interaction points from automated abuse. Successful exploitation could allow attackers to bypass CAPTCHA challenges, increasing the risk of automated credential stuffing, spam, fraudulent registrations, and denial of service through automated requests. This can lead to unauthorized access, data leakage, service disruption, and reputational damage. Organizations in sectors with high web interaction such as e-commerce, financial services, government portals, and online service providers are particularly at risk. The compromised CAPTCHA mechanism reduces the effectiveness of bot mitigation strategies, potentially increasing the attack surface. Additionally, since the weakness affects the integrity of the CAPTCHA challenge, it undermines trust in the affected applications’ security controls. However, the vulnerability does not directly compromise confidentiality or availability unless combined with other attack vectors. The absence of known exploits suggests that exploitation may require some technical effort or targeted knowledge, but the predictable nature of the weak PRNG makes automated attacks feasible once the weakness is understood.

Immediate mitigation should focus on replacing the insecure rand() function with a cryptographically secure pseudo-random number generator (CSPRNG). In Perl, this can be achieved by using modules such as Crypt::PRNG or leveraging system sources of entropy like /dev/urandom or the Crypt::Random module. Developers should update the CAPTCHA generation logic to use these secure sources for both the CAPTCHA text and image noise. Until an official patch is released, organizations should consider disabling the Mojolicious::Plugin::CaptchaPNG 1.05 or replacing it with alternative CAPTCHA solutions that use secure randomness. Additionally, implementing multi-layered bot mitigation strategies such as rate limiting, IP reputation checks, and behavioral analysis can reduce the risk of automated abuse. Monitoring web application logs for unusual patterns of CAPTCHA failures or repeated automated requests can help detect exploitation attempts. Organizations should also review their dependency management processes to quickly identify and update vulnerable components. Finally, educating developers about the importance of cryptographically secure randomness in security controls is essential to prevent similar issues.