CVE-2017-5493 in WordPress
Summary
by MITRE
wp-includes/ms-functions.php in the Multisite WordPress API in WordPress before 4.7.1 does not properly choose random numbers for keys, which makes it easier for remote attackers to bypass intended access restrictions via a crafted (1) site signup or (2) user signup.
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Analysis
by VulDB Data Team • 05/13/2026
The vulnerability identified as CVE-2017-5493 resides within the WordPress multisite functionality, specifically in the wp-includes/ms-functions.php file which governs the Multisite API. This flaw represents a critical weakness in the random number generation process used for cryptographic key creation during site and user signup operations. The vulnerability affects WordPress versions prior to 4.7.1 and exposes systems to potential unauthorized access attempts through predictable key generation patterns. Attackers can exploit this weakness to bypass intended access restrictions by crafting malicious signup requests that leverage the predictable random number sequences.
The technical implementation of this vulnerability stems from insufficient randomness in the cryptographic key generation algorithms used by WordPress during multisite operations. When users attempt to sign up for new sites or accounts within a multisite WordPress installation, the system generates random keys to secure these operations and prevent unauthorized access. However, the flawed random number generator produces predictable sequences that can be reverse-engineered by attackers. This weakness directly violates the principles of secure random number generation as outlined in industry standards such as CWE-330, which addresses the use of insecure random number generators in security-sensitive contexts. The vulnerability specifically impacts the cryptographic strength of the generated keys, making them susceptible to brute force attacks and prediction attempts that would normally be computationally infeasible with properly random sequences.
The operational impact of this vulnerability extends beyond simple access bypass scenarios and represents a significant threat to WordPress multisite installations. Attackers can potentially exploit this weakness to register unauthorized sites, gain administrative access to existing installations, or manipulate the signup process to create malicious entries within the multisite network. This vulnerability particularly affects organizations that rely heavily on WordPress multisite functionality for managing multiple domains or user groups, as it undermines the fundamental security assumptions of the signup process. The attack surface is broadened because the vulnerability affects both site signup and user signup operations, providing multiple vectors for exploitation. According to ATT&CK framework category T1190, this vulnerability enables initial access through exploitation of software vulnerabilities, while also supporting privilege escalation techniques that could allow attackers to establish persistent access within the multisite environment.
Mitigation strategies for CVE-2017-5493 focus primarily on upgrading to WordPress version 4.7.1 or later, where the random number generation has been properly addressed. Organizations should also implement additional security measures including monitoring for unusual signup patterns, implementing rate limiting on signup requests, and ensuring proper network segmentation around WordPress installations. Security teams should conduct thorough vulnerability assessments to identify any systems running vulnerable versions and establish patch management procedures to prevent similar issues in the future. The fix implemented in WordPress 4.7.1 addressed the underlying random number generation algorithm to ensure proper cryptographic strength for key creation, aligning with security best practices for cryptographic implementations. Additionally, organizations should consider implementing web application firewalls and intrusion detection systems to monitor for exploitation attempts targeting this specific vulnerability, as the predictable nature of the random number sequences makes detection possible through pattern analysis and anomaly detection techniques.