CVE-2022-43958 is a security vulnerability identified in Siemens QMS Automotive software versions prior to V12.39. The core issue is the plaintext storage of user credentials within the product's database, without any form of hashing or encryption. This vulnerability falls under CWE-256, which concerns the improper storage of sensitive information such as passwords. Because the credentials are stored in plaintext, an attacker who gains access to the database can directly retrieve user passwords. This exposure enables the attacker to impersonate legitimate users, potentially escalating privileges or accessing sensitive automotive quality management data. The vulnerability does not require exploitation of a software bug beyond database access, meaning that if an attacker can breach the database or obtain a backup, they can easily extract credentials. No authentication or user interaction is needed to exploit this vulnerability once database access is achieved. Siemens has addressed this issue in version 12.39 and later, but versions prior to this remain vulnerable. There are no known exploits in the wild at the time of this report, and no official patches or mitigation links have been published by Siemens yet. The vulnerability affects all versions of QMS Automotive before V12.39, which is a specialized software product used primarily in the automotive industry for quality management processes.

For European organizations, particularly those in the automotive sector, this vulnerability poses a significant risk to confidentiality and integrity of sensitive operational data. Compromise of user credentials can lead to unauthorized access to quality management systems, potentially allowing attackers to alter or sabotage quality control data, disrupt manufacturing workflows, or exfiltrate proprietary information. Given the critical role of quality management in automotive production, such disruptions could have downstream effects on product safety, regulatory compliance, and supply chain integrity. Additionally, unauthorized access could facilitate lateral movement within corporate networks, increasing the risk of broader compromise. The impact on availability is less direct but could occur if attackers modify or delete critical data. Since Siemens QMS Automotive is widely used by automotive manufacturers and suppliers across Europe, the vulnerability could affect multiple tiers of the automotive supply chain. The lack of encryption for stored passwords also raises compliance concerns under GDPR and other data protection regulations, as it reflects inadequate protection of personal data. Although no active exploitation has been reported, the vulnerability's simplicity and the value of the targeted systems make it a potential target for threat actors focusing on industrial espionage or sabotage.

Organizations using Siemens QMS Automotive should prioritize upgrading to version 12.39 or later, where the vulnerability has been addressed. Until upgrades can be performed, the following specific mitigations are recommended: 1) Restrict and monitor access to the QMS Automotive database with strict network segmentation and access controls to minimize the risk of unauthorized database access. 2) Implement enhanced logging and alerting on database access events to detect suspicious activity early. 3) Conduct regular audits of stored credentials and consider manual encryption or migration of credentials if feasible. 4) Employ multi-factor authentication (MFA) for accessing the QMS Automotive system to reduce the impact of credential compromise. 5) Review and tighten internal policies on credential management and database backups, ensuring backups are encrypted and access-controlled. 6) Educate IT and security teams about the vulnerability and the importance of safeguarding the QMS Automotive environment. 7) Coordinate with Siemens support for any interim patches or recommended configuration changes. These measures go beyond generic advice by focusing on protecting the database layer, enhancing detection capabilities, and compensating for the lack of credential hashing until a full upgrade is possible.