CVE-2026-8029 in Smart Life
Summary
by MITRE • 08/05/2026
The ZTE Smart Life app contains an SQL injection vulnerability that allows attackers to execute UNION SELECT statements to query sensitive data in the feedback.db database across tables, including user accounts, phone numbers, feedback content, and local debug log paths, thereby enabling the theft of local privacy data.
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Analysis
by VulDB Data Team • 08/05/2026
The ZTE Smart Life application presents a critical sql injection vulnerability that fundamentally compromises the security posture of connected IoT devices and their associated user data. This vulnerability exists within the mobile application's database interaction mechanisms, specifically allowing malicious actors to construct and execute UNION SELECT statements against the feedback.db database file. The flaw represents a classic sql injection attack vector where insufficient input validation permits attackers to manipulate database queries through crafted payloads that bypass normal authentication and authorization controls.
The technical exploitation of this vulnerability enables unauthorized access to sensitive data stored within the application's local database structure. Attackers can leverage union-based sql injection techniques to extract information from multiple tables within the feedback.db database including user account credentials, personal phone numbers, detailed feedback content submitted by users, and local debug log file paths that may contain additional system information or configuration details. This comprehensive data exposure occurs because the application fails to properly sanitize user inputs before incorporating them into database queries, creating an attack surface where malicious payloads can manipulate the intended query execution flow.
The operational impact of this vulnerability extends beyond simple data theft to encompass potential identity theft, privacy violations, and escalation of attacks against connected IoT devices. The inclusion of debug log paths in the exposed data creates additional security risks as these paths may reveal internal application architecture, file locations, or system configurations that could aid in further exploitation attempts. From a cybersecurity perspective, this vulnerability aligns with cwe-89 sql injection weakness classification and represents a significant risk to user privacy and device security, particularly when considering that smart home devices often contain sensitive personal information and may serve as entry points for broader network infiltration.
The implications of this vulnerability within the context of the mitre att&ck framework demonstrate clear capabilities for initial access and credential access phases where adversaries can harvest user credentials and personal information for subsequent malicious activities. Organizations implementing zte smart life applications should consider this vulnerability as part of their risk assessment for connected home devices, particularly given that many IoT ecosystems lack proper input validation and database security controls. Effective mitigations include implementing proper parameterized queries, input sanitization mechanisms, and comprehensive database access controls to prevent unauthorized data extraction through sql injection vectors.
Security teams should prioritize patching this vulnerability across all affected zte smart life application versions while implementing network monitoring to detect potential exploitation attempts targeting the feedback.db database. The vulnerability represents a fundamental failure in secure coding practices and highlights the importance of proper database security measures within mobile applications that handle user data, particularly in IoT ecosystems where device security directly impacts overall network security posture. Regular security assessments and code reviews focusing on sql injection prevention techniques should be mandatory for all application development cycles to prevent similar vulnerabilities from emerging in future releases.
This vulnerability classification aligns with common industry practices for assessing database security risks and demonstrates the critical need for robust input validation, proper database access controls, and comprehensive security testing throughout the software development lifecycle. The exposed data types indicate a complete breakdown in data protection mechanisms that should be addressed through immediate remediation efforts and enhanced security monitoring protocols to prevent unauthorized access to user information stored within local application databases.