CVE-2025-1796 in dify
Summary
by MITRE • 03/20/2025
A vulnerability in langgenius/dify v0.10.1 allows an attacker to take over any account, including administrator accounts, by exploiting a weak pseudo-random number generator (PRNG) used for generating password reset codes. The application uses `random.randint` for this purpose, which is not suitable for cryptographic use and can be cracked. An attacker with access to workflow tools can extract the PRNG output and predict future password reset codes, leading to a complete compromise of the application.
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Analysis
by VulDB Data Team • 07/17/2025
This vulnerability resides in the langgenius/dify application version 0.10.1 where a critical security flaw exists in the password reset functionality. The system employs a weak pseudo-random number generator through the use of random.randint function for generating password reset codes, which fundamentally undermines the security of the authentication mechanism. This weakness allows attackers to predict future reset codes by analyzing the PRNG output, effectively enabling account takeover attacks across all user accounts including administrative ones.
The technical implementation flaw stems from the improper use of cryptographic functions within the application's security infrastructure. According to CWE-330, the use of weak random number generators for cryptographic purposes represents a significant weakness that directly enables predictable outcomes. The random.randint function lacks the cryptographic security properties necessary for generating secure tokens, making it vulnerable to reverse engineering and prediction attacks. This vulnerability directly maps to ATT&CK technique T1566.001 which involves credential access through social engineering and manipulation of authentication systems.
The operational impact of this vulnerability extends far beyond simple privilege escalation as it provides attackers with complete control over user accounts and potentially the entire system administration. When an attacker gains access to workflow tools within the application environment, they can extract the PRNG output and systematically predict future password reset codes, enabling them to bypass the entire authentication mechanism. This creates a persistent backdoor that can be exploited repeatedly without detection, allowing for long-term unauthorized access to sensitive data and system resources.
Mitigation strategies must address both immediate remediation and long-term architectural improvements. The primary fix involves replacing the weak random.randint implementation with a cryptographically secure random number generator such as Python's secrets module or equivalent cryptographic libraries. Organizations should implement proper entropy sources and ensure all security tokens are generated using approved cryptographic methods that meet NIST SP 800-90A standards for random number generation. Additionally, implementing rate limiting and monitoring for password reset requests can help detect anomalous patterns that might indicate exploitation attempts. The system should also enforce multi-factor authentication for administrative accounts and implement time-based token validation to further reduce the window of opportunity for attackers to exploit predictable reset codes.