CVE-2020-35568 in mymbCONNECT24
Summary
by MITRE • 02/16/2021
An issue was discovered in MB CONNECT LINE mymbCONNECT24 and mbCONNECT24 through 2.6.2. An incomplete filter applied to a database response allows an authenticated attacker to gain non-public information about other users and devices in the account.
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Analysis
by VulDB Data Team • 03/02/2021
This vulnerability exists in MB CONNECT LINE mymbCONNECT24 and mbCONNECT24 versions up to 2.6.2, representing a critical authorization flaw that undermines the system's data protection mechanisms. The issue stems from an incomplete input validation filter applied to database responses, which fails to properly sanitize or restrict access to sensitive information. This flaw allows authenticated attackers who have gained initial access to the system to exploit the incomplete filtering mechanism and extract non-public data about other users and devices within their account. The vulnerability specifically targets the application's data access controls, creating a path for privilege escalation through data exposure rather than direct system compromise.
The technical implementation of this vulnerability demonstrates a classic case of insufficient access control enforcement within the application's backend data handling processes. When the system processes database queries and responses, the filter mechanism that should restrict data visibility to authorized users fails to properly validate or sanitize the output before it is transmitted to the requesting user. This incomplete filtering creates a data leakage scenario where authenticated users can manipulate the system to retrieve information about other users and their associated devices without proper authorization. The vulnerability operates at the application layer and requires authentication to exploit, making it particularly concerning as it can be leveraged by insiders or compromised legitimate users.
The operational impact of CVE-2020-35568 extends beyond simple data exposure, as it enables attackers to gather comprehensive information about system users and their device configurations. This intelligence gathering capability can facilitate more sophisticated attacks including social engineering, targeted phishing campaigns, and advanced persistent threat operations. Attackers can exploit the leaked information to identify high-value targets, understand user behavior patterns, and map out device inventories that may contain additional vulnerabilities. The exposure of device information particularly undermines the security posture of IoT and connected device ecosystems where such information could reveal network topology, device types, firmware versions, and potential attack vectors. This vulnerability directly violates the principle of least privilege and data confidentiality as outlined in cybersecurity frameworks such as the NIST Cybersecurity Framework and ISO/IEC 27001 standards.
Mitigation strategies for this vulnerability should focus on implementing robust input validation and output filtering mechanisms throughout the application's data access pathways. The primary remediation involves strengthening the database response filtering to ensure that all user queries are properly validated and that responses are strictly limited to the authenticated user's authorized scope. Security patches should include comprehensive access control enforcement that validates user permissions at multiple layers of the application architecture. Organizations should implement proper logging and monitoring of data access patterns to detect anomalous behavior that might indicate exploitation attempts. The fix should align with CWE-20: Improper Input Validation and CWE-284: Improper Access Control, both of which are fundamental security weaknesses that directly relate to this vulnerability's root cause. Additionally, implementing principle of least privilege access controls and regular security testing including penetration testing and code reviews should be part of the remediation process to prevent similar issues from emerging in future releases.