Summary
Omnispace Agora Project contains a second-order SQL injection flaw in the _idCategoryFilter parameter, where attacker-controlled input is stored in a session and later incorporated into a SQL statement without parameterization. An authenticated attacker who can submit and persist a filter value may trigger unauthorized database access or manipulation when the stored filter is subsequently processed.
Omnispace Agora Project contains a second-order SQL injection flaw in the _idCategoryFilter parameter, where attacker-controlled input is stored in a session and later incorporated into a SQL statement without parameterization. An authenticated attacker who can submit and persist a filter value may trigger unauthorized database access or manipulation when the stored filter is subsequently processed.
Affected context
The vulnerability occurs in category filtering logic involving _idCategoryFilter and app/Common/MdlCategory.php. It becomes risky when authenticated users can influence a filter value, the value is persisted in session state, and later application processing concatenates that value into a SQL query rather than binding it as data.
The vulnerability occurs in category filtering logic involving _idCategoryFilter and app/Common/MdlCategory.php. It becomes risky when authenticated users can influence a filter value, the value is persisted in session state, and later application processing concatenates that value into a SQL query rather than binding it as data.
Exploit preconditions
- Attack surface: Authenticated application functionality that accepts category filter input
- Required access: Valid user authentication and permission to submit or persist the relevant filter value
- Trigger point: Later application processing that applies the stored session filter
- Why exploitation is possible: Persisted input is reused in a SQL statement through string concatenation without parameterized query binding
- Attack surface: Authenticated application functionality that accepts category filter input
- Required access: Valid user authentication and permission to submit or persist the relevant filter value
- Trigger point: Later application processing that applies the stored session filter
- Why exploitation is possible: Persisted input is reused in a SQL statement through string concatenation without parameterized query binding
Why this happens
The underlying bug is a second-order SQL injection pattern. Input is accepted and stored without being treated as permanently untrusted, then later reaches SQL construction where it is concatenated into a statement instead of passed through a parameterized interface. This maps to CWE-89: Improper Neutralization of Special Elements used in an SQL Command, because data supplied through an earlier application flow can alter the meaning of a later database query.
The underlying bug is a second-order SQL injection pattern. Input is accepted and stored without being treated as permanently untrusted, then later reaches SQL construction where it is concatenated into a statement instead of passed through a parameterized interface. This maps to CWE-89: Improper Neutralization of Special Elements used in an SQL Command, because data supplied through an earlier application flow can alter the meaning of a later database query.
Potential impact
- An attacker may read unauthorized database records
- An attacker could alter or delete data permitted by the database account
- Application data integrity may be compromised
- Sensitive information could be exposed through query results or error behavior
- Database availability may be affected by malicious query manipulation
- An attacker may read unauthorized database records
- An attacker could alter or delete data permitted by the database account
- Application data integrity may be compromised
- Sensitive information could be exposed through query results or error behavior
- Database availability may be affected by malicious query manipulation
General mitigation guidance
Mitigation generally focuses on making SQL data boundaries explicit throughout the full lifecycle of user-controlled values.
Common defensive patterns include:
- Use parameterized queries or prepared statements for every database operation
- Treat session-persisted values as untrusted input when they are read back
- Apply allowlist validation for category identifiers and filter formats
- Use typed query-building abstractions that separate data from SQL syntax
- Restrict database accounts to the minimum required read and write privileges
- Avoid exposing detailed database errors to users
- Enforce secure defaults for filters and reject unexpected values before query execution
Mitigation generally focuses on making SQL data boundaries explicit throughout the full lifecycle of user-controlled values.
Common defensive patterns include:
- Use parameterized queries or prepared statements for every database operation
- Treat session-persisted values as untrusted input when they are read back
- Apply allowlist validation for category identifiers and filter formats
- Use typed query-building abstractions that separate data from SQL syntax
- Restrict database accounts to the minimum required read and write privileges
- Avoid exposing detailed database errors to users
- Enforce secure defaults for filters and reject unexpected values before query execution
How teams detect issues like this
Detection can combine static analysis, code review, and runtime monitoring:
- Search for string concatenation, interpolation, or formatting used to construct SQL statements
- Trace request and session values through storage and later query execution
- Review category filtering code for missing parameter binding and weak allowlist validation
- Add policy checks that require approved database access APIs for application queries
- Monitor unusual filter activity, database errors, and access patterns involving authenticated accounts
- Use automated security analysis tools to identify data flows from request or session state into SQL construction
Detection can combine static analysis, code review, and runtime monitoring:
- Search for string concatenation, interpolation, or formatting used to construct SQL statements
- Trace request and session values through storage and later query execution
- Review category filtering code for missing parameter binding and weak allowlist validation
- Add policy checks that require approved database access APIs for application queries
- Monitor unusual filter activity, database errors, and access patterns involving authenticated accounts
- Use automated security analysis tools to identify data flows from request or session state into SQL construction
Sources
| Source | Link |
|---|---|
| github. | github.com/ |
| agora-project. | agora-project.net/ |
| vulncheck. | vulncheck.com/ |
