CVE-2022-3059: CWE-89 Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection') in Schoolbox Pty Ltd Schoolbox
The application was vulnerable to multiple instances of SQL injection (authenticated and unauthenticated) through a vulnerable parameter. Due to the stacked query support, complex SQL commands could be crafted and injected into the vulnerable parameter and using a sleep based inferential SQL injection it was possible to extract data from the database.
AI Analysis
Technical Summary
CVE-2022-3059 is a high-severity SQL injection vulnerability affecting Schoolbox, a learning management system developed by Schoolbox Pty Ltd, specifically version 21.0.2. The vulnerability arises from improper neutralization of special elements used in SQL commands (CWE-89), allowing attackers to inject malicious SQL statements through a vulnerable parameter. Both authenticated and unauthenticated users can exploit this flaw, which significantly increases the attack surface. The vulnerability supports stacked queries, enabling attackers to execute multiple SQL commands in a single injection, thereby increasing the complexity and potential damage of the attack. Additionally, the vulnerability allows for sleep-based inferential SQL injection techniques, which can be used to extract sensitive data from the backend database by measuring response delays. The CVSS v3.1 base score is 8.6, reflecting a high severity due to network attack vector, low attack complexity, no privileges or user interaction required, and a significant impact on confidentiality, with partial impacts on integrity and availability. No known exploits in the wild have been reported yet, and no official patches have been linked, indicating that organizations using the affected version remain at risk until mitigations or updates are applied.
Potential Impact
For European organizations, the impact of this vulnerability can be substantial, especially for educational institutions and organizations relying on the Schoolbox platform for managing learning content, student data, and administrative functions. Exploitation could lead to unauthorized disclosure of sensitive personal data, including student records, grades, and potentially financial information, violating GDPR and other data protection regulations. The ability to execute stacked queries and inferential SQL injection increases the risk of data exfiltration and unauthorized data manipulation, which could disrupt educational services and damage institutional reputation. Furthermore, partial impacts on system integrity and availability could lead to service interruptions, affecting teaching and administrative operations. Given the critical nature of educational infrastructure and the sensitivity of the data involved, European organizations must treat this vulnerability with high priority to avoid regulatory penalties and operational disruptions.
Mitigation Recommendations
Since no official patches are currently linked, organizations should implement immediate compensating controls. These include: 1) Conducting a thorough code review and input validation to sanitize and parameterize all SQL queries, eliminating direct concatenation of user inputs. 2) Employing prepared statements or stored procedures to prevent injection. 3) Restricting database user permissions to the minimum necessary to limit the impact of a successful injection. 4) Implementing Web Application Firewalls (WAFs) with rules specifically designed to detect and block SQL injection attempts, including those using stacked queries and time-based inference techniques. 5) Monitoring application logs and database query patterns for anomalies indicative of injection attempts. 6) Segregating the database environment and encrypting sensitive data at rest to reduce exposure. 7) Planning and testing an upgrade path to a patched version once available. Additionally, educating developers and administrators about secure coding practices and regular security assessments will help prevent similar vulnerabilities.
Affected Countries
United Kingdom, Germany, France, Netherlands, Sweden, Finland, Ireland, Belgium, Denmark, Austria
CVE-2022-3059: CWE-89 Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection') in Schoolbox Pty Ltd Schoolbox
Description
The application was vulnerable to multiple instances of SQL injection (authenticated and unauthenticated) through a vulnerable parameter. Due to the stacked query support, complex SQL commands could be crafted and injected into the vulnerable parameter and using a sleep based inferential SQL injection it was possible to extract data from the database.
AI-Powered Analysis
Technical Analysis
CVE-2022-3059 is a high-severity SQL injection vulnerability affecting Schoolbox, a learning management system developed by Schoolbox Pty Ltd, specifically version 21.0.2. The vulnerability arises from improper neutralization of special elements used in SQL commands (CWE-89), allowing attackers to inject malicious SQL statements through a vulnerable parameter. Both authenticated and unauthenticated users can exploit this flaw, which significantly increases the attack surface. The vulnerability supports stacked queries, enabling attackers to execute multiple SQL commands in a single injection, thereby increasing the complexity and potential damage of the attack. Additionally, the vulnerability allows for sleep-based inferential SQL injection techniques, which can be used to extract sensitive data from the backend database by measuring response delays. The CVSS v3.1 base score is 8.6, reflecting a high severity due to network attack vector, low attack complexity, no privileges or user interaction required, and a significant impact on confidentiality, with partial impacts on integrity and availability. No known exploits in the wild have been reported yet, and no official patches have been linked, indicating that organizations using the affected version remain at risk until mitigations or updates are applied.
Potential Impact
For European organizations, the impact of this vulnerability can be substantial, especially for educational institutions and organizations relying on the Schoolbox platform for managing learning content, student data, and administrative functions. Exploitation could lead to unauthorized disclosure of sensitive personal data, including student records, grades, and potentially financial information, violating GDPR and other data protection regulations. The ability to execute stacked queries and inferential SQL injection increases the risk of data exfiltration and unauthorized data manipulation, which could disrupt educational services and damage institutional reputation. Furthermore, partial impacts on system integrity and availability could lead to service interruptions, affecting teaching and administrative operations. Given the critical nature of educational infrastructure and the sensitivity of the data involved, European organizations must treat this vulnerability with high priority to avoid regulatory penalties and operational disruptions.
Mitigation Recommendations
Since no official patches are currently linked, organizations should implement immediate compensating controls. These include: 1) Conducting a thorough code review and input validation to sanitize and parameterize all SQL queries, eliminating direct concatenation of user inputs. 2) Employing prepared statements or stored procedures to prevent injection. 3) Restricting database user permissions to the minimum necessary to limit the impact of a successful injection. 4) Implementing Web Application Firewalls (WAFs) with rules specifically designed to detect and block SQL injection attempts, including those using stacked queries and time-based inference techniques. 5) Monitoring application logs and database query patterns for anomalies indicative of injection attempts. 6) Segregating the database environment and encrypting sensitive data at rest to reduce exposure. 7) Planning and testing an upgrade path to a patched version once available. Additionally, educating developers and administrators about secure coding practices and regular security assessments will help prevent similar vulnerabilities.
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Technical Details
- Data Version
- 5.1
- Assigner Short Name
- TML
- Date Reserved
- 2022-08-30T00:00:00.000Z
- Cisa Enriched
- true
- Cvss Version
- 3.1
- State
- PUBLISHED
Threat ID: 682d981dc4522896dcbdaec5
Added to database: 5/21/2025, 9:08:45 AM
Last enriched: 7/5/2025, 7:39:48 PM
Last updated: 7/31/2025, 1:59:03 PM
Views: 9
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