CVE-2026-19636 in Security Center
Summary
by MITRE • 08/14/2026
An issue was identified in which CSRF tokens were generated using a predictable method, potentially reducing their effectiveness as a security control. This has been addressed by improving the randomness and entropy of token generation.
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Analysis
by VulDB Data Team • 08/14/2026
Cross-site request forgery csrf vulnerabilities represent one of the most persistent threats in web application security where attackers exploit the trust relationship between browsers and web applications to execute unauthorized commands. The specific weakness identified involves the predictable generation of csrf tokens which fundamentally undermines their cryptographic integrity and security effectiveness. When tokens are generated using predictable methods such as sequential numbering, time-based values, or insufficient entropy sources, they become vulnerable to exploitation by malicious actors who can anticipate or reproduce valid token values. This vulnerability directly maps to cwe-352 which categorizes cross-site request forgery vulnerabilities and specifically addresses the weakness of inadequate token generation mechanisms that fail to provide sufficient randomness. The operational impact of such a flaw extends beyond simple privilege escalation as it enables attackers to craft malicious requests that appear legitimate to the target application, potentially compromising user accounts, modifying sensitive data, or executing unauthorized transactions. Attackers leveraging this vulnerability can employ techniques described in the attack pattern taxonomy under attack-0172 which details how predictable token generation enables csrf attacks through automated exploitation tools and manual crafting of malicious payloads.
The technical implementation flaw stems from insufficient entropy sources during token creation processes where developers rely on deterministic algorithms or weak random number generators instead of cryptographically secure methods. This weakness manifests when applications use system time, counter values, or other predictable elements as components in their token generation algorithm rather than employing robust cryptographic randomization techniques. The reduced entropy means that an attacker can potentially reverse engineer the token generation algorithm or simply guess valid tokens through pattern recognition and statistical analysis. Modern web security frameworks and standards such as owasp top ten 2021 specifically identify csrf as a critical control failure when applications fail to implement proper token generation mechanisms with sufficient randomness. The mitigation strategy requires implementing cryptographically secure random number generators that provide adequate entropy for token creation, typically requiring at least 128 bits of entropy to ensure resistance against brute force and prediction attacks.
Security practitioners must address this vulnerability by upgrading token generation libraries to utilize established cryptographic standards such as those defined in nist sp 800-90a for random number generation or openssl rand functions that provide cryptographically secure randomness. The implementation should incorporate multiple entropy sources including hardware random number generators, system-level randomness pools, and time-based components that are properly mixed to prevent predictability. Additional defensive measures include implementing token expiration mechanisms, binding tokens to user sessions, and employing additional layers of authentication such as hmac signatures that further strengthen the overall security posture against csrf attacks. Organizations should conduct regular security assessments to verify that token generation processes meet current cryptographic standards and maintain compliance with industry frameworks like iso 27001 and soc 2 that require robust authentication mechanisms including proper csrf protection measures. The remediation process must also include comprehensive testing of token generation under various conditions to ensure that the improved implementation provides sufficient entropy and resistance against both automated and manual exploitation attempts.