Summary
A SQL injection vulnerability in the Insurance Management System allows remote attackers to influence database queries through the Policy_no or Name parameters in the policy-holder editing function. It becomes risky when user-controlled values are incorporated into mysqli_query statements without adequate parameterization or validation.
A SQL injection vulnerability in the Insurance Management System allows remote attackers to influence database queries through the Policy_no or Name parameters in the policy-holder editing function. It becomes risky when user-controlled values are incorporated into mysqli_query statements without adequate parameterization or validation.
Affected context
The vulnerability occurs in /Agent/ManagePolicy/EditPolicyHolder.php, where the mysqli_query function processes the Policy_no or Name inputs. Deployments are exposed when these values can be supplied remotely and are used to construct database queries without a strong separation between SQL code and input data.
The vulnerability occurs in /Agent/ManagePolicy/EditPolicyHolder.php, where the mysqli_query function processes the Policy_no or Name inputs. Deployments are exposed when these values can be supplied remotely and are used to construct database queries without a strong separation between SQL code and input data.
Exploit preconditions
- Attack surface: The remotely accessible policy-holder editing functionality
- Required access: Access to the application endpoint that accepts Policy_no or Name values; authentication requirements depend on deployment controls
- Trigger point: Processing of attacker-influenced values by mysqli_query
- Why exploitation is possible: Input is incorporated into a database query without sufficient parameterization or equivalent query-boundary protection
- Attack surface: The remotely accessible policy-holder editing functionality
- Required access: Access to the application endpoint that accepts Policy_no or Name values; authentication requirements depend on deployment controls
- Trigger point: Processing of attacker-influenced values by mysqli_query
- Why exploitation is possible: Input is incorporated into a database query without sufficient parameterization or equivalent query-boundary protection
Why this happens
The underlying bug is improper neutralization of special elements used in an SQL command. Application input reaches mysqli_query as part of a dynamically constructed statement rather than being handled strictly as data. This maps primarily to CWE-89, SQL Injection; CWE-74 is a broader related category covering improper neutralization in an interpreter.
The underlying bug is improper neutralization of special elements used in an SQL command. Application input reaches mysqli_query as part of a dynamically constructed statement rather than being handled strictly as data. This maps primarily to CWE-89, SQL Injection; CWE-74 is a broader related category covering improper neutralization in an interpreter.
Potential impact
- An attacker may read unauthorized database records.
- An attacker could modify or delete stored insurance and policy-holder data.
- Database credentials or sensitive application information could be exposed.
- The application may experience unauthorized actions, data integrity loss, or service disruption.
- An attacker may read unauthorized database records.
- An attacker could modify or delete stored insurance and policy-holder data.
- Database credentials or sensitive application information could be exposed.
- The application may experience unauthorized actions, data integrity loss, or service disruption.
General mitigation guidance
Mitigation generally focuses on preserving a strict boundary between SQL
statements and externally supplied values.
Common defensive patterns include:
- Use parameterized queries or prepared statements for all user-influenced database operations.
- Prefer narrowly scoped data-access methods and typed query parameters over string-built SQL.
- Apply allowlist validation for identifiers and business fields, while treating validation as a supplement rather than a replacement for parameterization.
- Reduce database-account privileges to only the operations required by the application.
- Avoid exposing detailed database errors and maintain secure handling of connection credentials.
- Add automated tests and policy checks that reject dynamic SQL construction involving request data.
Mitigation generally focuses on preserving a strict boundary between SQL
statements and externally supplied values.
Common defensive patterns include:
- Use parameterized queries or prepared statements for all user-influenced database operations.
- Prefer narrowly scoped data-access methods and typed query parameters over string-built SQL.
- Apply allowlist validation for identifiers and business fields, while treating validation as a supplement rather than a replacement for parameterization.
- Reduce database-account privileges to only the operations required by the application.
- Avoid exposing detailed database errors and maintain secure handling of connection credentials.
- Add automated tests and policy checks that reject dynamic SQL construction involving request data.
How teams detect issues like this
Organizations can look for this vulnerability through:
- Static analysis patterns that identify mysqli_query calls receiving concatenated, interpolated, or otherwise request-derived values.
- Code review checks for SQL strings assembled from controller parameters such as Policy_no or Name.
- Dynamic testing that uses benign special-character and boundary inputs to identify unexpected query behavior without relying on destructive actions.
- Database and application monitoring for anomalous query errors, unusual access patterns, and unexpected data changes.
- Secure coding policies requiring prepared statements and automated review rules for database APIs.
Organizations can look for this vulnerability through:
- Static analysis patterns that identify mysqli_query calls receiving concatenated, interpolated, or otherwise request-derived values.
- Code review checks for SQL strings assembled from controller parameters such as Policy_no or Name.
- Dynamic testing that uses benign special-character and boundary inputs to identify unexpected query behavior without relying on destructive actions.
- Database and application monitoring for anomalous query errors, unusual access patterns, and unexpected data changes.
- Secure coding policies requiring prepared statements and automated review rules for database APIs.
Sources
| Source | Link |
|---|---|
| github. | github.com/ |
| github. | github.com/ |
| vuldb. | vuldb.com/ |
| vuldb. | vuldb.com/ |
| vuldb. | vuldb.com/ |
| vuldb. | vuldb.com/ |
