CVE-2026-109080 in Night Shift
Summary
by MITRE • 10/12/2026
SQL injection in the bulk license plate search of the Flock Night Shift hosted service allowed an authenticated user to read other customer organizations' data, including license plate recognition records, via a crafted license plate value. Data could not be modified. Flock identified the issue through internal security review and remediated it on 2026-08-12; no customer action is required.
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Analysis
by VulDB Data Team • 10/12/2026
The vulnerability described constitutes an authenticated SQL injection flaw within the bulk license plate search functionality of the Flock Night Shift hosted service, representing a critical failure in input validation and query construction mechanisms. Unlike typical unauthenticated injections that allow for arbitrary code execution or complete database compromise, this specific instance is characterized by its reliance on valid authentication credentials to exploit a logic error in how user-supplied data is integrated into backend SQL queries. The attacker leverages the bulk search feature, which likely processes multiple license plate identifiers simultaneously, to inject malicious SQL syntax through crafted input values. This technique bypasses standard access controls because the application fails to properly isolate or sanitize inputs before they are executed against the database engine, allowing the injected commands to alter the intended query structure and scope of data retrieval operations.
From a technical perspective, this vulnerability aligns with CWE-89 Improper Neutralization of Special Elements used in an SQL Command, specifically within the context of authenticated web applications where trust boundaries are often misconfigured. The exploitation vector involves manipulating the search parameters to break out of the expected string or integer contexts and inject clauses that modify the WHERE conditions or UNION SELECT statements. This allows the attacker to bypass row-level security policies that typically restrict users from accessing data belonging to other customer organizations in a multi-tenant SaaS environment. By crafting specific license plate values, an authenticated user can trick the database into returning records associated with different tenants, effectively breaking the logical isolation between customers. The attack does not involve modifying existing data or executing administrative commands on the server, which limits the impact primarily to unauthorized information disclosure rather than integrity violation or service disruption.
The operational impact of this vulnerability is significant due to its potential for large-scale data exfiltration across organizational boundaries in a multi-tenant architecture. An attacker with valid credentials can systematically enumerate and extract sensitive license plate recognition records belonging to other customers, potentially exposing personally identifiable information (PII), vehicle tracking histories, and access logs that are subject to strict privacy regulations such as GDPR or CCPA. This breach of data isolation undermines the core trust model of the service provider and poses severe legal and reputational risks for both the vendor and its affected clients. The ability to read rather than modify data means that while immediate system integrity is preserved, the confidentiality aspect of the CIA triad is severely compromised, leading to potential regulatory fines and loss of customer confidence if such leaks were discovered in a production environment without timely remediation.
In terms of threat modeling, this activity maps directly to MITRE ATT&CK technique T1059 Command and Scripting Interpreter under SQL commands, specifically focusing on data exfiltration via injection techniques (T1048). The attack pattern reflects common exploitation strategies where attackers leverage existing application functionality to pivot into restricted areas of the database. Although the vulnerability was identified through internal security reviews rather than external penetration testing or user reports, it highlights the importance of continuous static and dynamic analysis in development pipelines. The remediation strategy employed by Flock involved correcting the input validation logic and ensuring that all bulk search inputs are strictly parameterized or sanitized before execution. This incident underscores the necessity for rigorous code review processes focused on SQL query construction, particularly in features handling large volumes of user-supplied data where injection vectors may be less obvious than in simple form fields.
To mitigate similar risks in future developments, organizations should enforce strict adherence to prepared statements and parameterized queries as a primary defense against SQL injection vulnerabilities. Additionally implementing robust input validation that rejects any non-alphanumeric characters or unexpected syntax patterns in search parameters can provide an effective secondary layer of protection. Role-based access control (RBAC) checks must be rigorously tested at the database level, not just the application level, to ensure that even if a query is manipulated, it cannot retrieve data outside the authorized scope for the current user session. Regular security audits and automated vulnerability scanning tools configured to detect SQL injection patterns in bulk processing endpoints are essential components of a comprehensive defense-in-depth strategy. The fact that no customer action was required indicates that the vendor successfully deployed patches or configuration updates server-side, emphasizing the value of managed services where infrastructure-level fixes can be applied uniformly without requiring individual client intervention.