CVE-2022-41210 in Customer Data Cloud
Summary
by MITRE • 10/12/2022
SAP Customer Data Cloud (Gigya mobile app for Android) - version 7.4, uses insecure random number generator program which makes it easy for the attacker to predict future random numbers. This can lead to information disclosure and modification of certain user settings.
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Analysis
by VulDB Data Team • 05/20/2025
The vulnerability identified as CVE-2022-41210 affects SAP Customer Data Cloud's Gigya mobile app for Android version 7.4, presenting a critical security risk through the use of an insecure random number generator. This flaw resides in the cryptographic implementation of the mobile application, specifically within the random number generation algorithms that are fundamental to secure communications and user authentication processes. The insecure random number generator represents a significant weakness in the application's security architecture, as it undermines the cryptographic foundations that protect sensitive user data and system integrity. The vulnerability directly impacts the app's ability to generate unpredictable values required for secure session management, authentication tokens, and other cryptographic operations that rely on true randomness.
The technical flaw manifests through the utilization of pseudo-random number generators that lack sufficient entropy and cryptographic strength. This weakness allows attackers to analyze patterns in the generated sequences and predict future values with considerable accuracy. The implications extend beyond simple prediction capabilities, as this vulnerability creates opportunities for attackers to compromise user sessions, manipulate authentication processes, and potentially gain unauthorized access to sensitive user information. The insecure random number generation creates a pathway for attackers to forge tokens, bypass authentication mechanisms, and establish persistent access to user accounts within the SAP Customer Data Cloud ecosystem.
The operational impact of this vulnerability is severe and multifaceted, affecting both individual user privacy and organizational security posture. Attackers can exploit this weakness to perform session hijacking attacks, where they predict session identifiers and take control of user sessions. The vulnerability also enables credential stuffing and other automated attack vectors that leverage predictable random values to compromise user accounts. Additionally, the insecure random number generator can affect the integrity of user settings modifications, allowing attackers to manipulate application configurations and potentially gain elevated privileges within the system. This vulnerability directly violates security principles outlined in the OWASP Top Ten, particularly the weakness related to insecure cryptographic storage and weak cryptography.
From a threat modeling perspective, this vulnerability aligns with several ATT&CK techniques including T1552.001 (Unsecured Credentials) and T1078.004 (Valid Accounts) as attackers can exploit predictable random values to compromise authentication mechanisms. The vulnerability also maps to CWE-330 (Use of Insufficiently Random Values) and CWE-331 (Insufficient Entropy) which specifically address weaknesses in random number generation and entropy sources. Organizations using SAP Customer Data Cloud should prioritize immediate remediation through patch updates provided by SAP, as the vulnerability creates an attack surface that can lead to full account compromise and data exfiltration. The security implications extend beyond individual user accounts to potentially affect enterprise data integration systems that rely on the SAP Customer Data Cloud for customer management and analytics.
Mitigation strategies should include immediate deployment of SAP-provided security patches and updates to address the insecure random number generator implementation. Organizations should also implement additional monitoring and detection capabilities to identify potential exploitation attempts targeting this vulnerability. Security teams should conduct comprehensive assessments of all SAP applications and mobile solutions to identify similar cryptographic weaknesses in the broader technology stack. The remediation process should include thorough code reviews of cryptographic implementations and verification that proper entropy sources and secure random number generators are utilized throughout the application architecture. Regular security testing and penetration testing should be conducted to ensure that cryptographic implementations meet industry standards and maintain adequate security postures against evolving threat landscapes.