Description

An SQL Injection vulnerability affecting Tuleap Enterprise Edition 17.5 could allow an attacker to have read access the Tuleap database.

Executive Summary

Technical Details

Mitigations

References

Additional Metadata

{
  "score": "7.1",
  "pubDate": "2026-10-12T11:17:10.317Z",
  "pubdate": "2026-10-12T11:17:10.317Z",
  "executiveSummary": "An SQL injection (SQLi) vulnerability has been identified in Tuleap Enterprise Edition version 17.5. This flaw allows an unauthorized or authenticated attacker to inject malicious SQL queries into database inputs that are improperly sanitized.\nThe primary impact of this vulnerability is unauthorized read access to the underlying Tuleap database. By exploiting this flaw, an attacker could potentially extract sensitive information stored within the system, including project data, user credentials, or system configurations.\nThe vulnerability resides in the application's data processing layer, where user-supplied input is concatenated directly into SQL queries without adequate parameterization. This constitutes a significant security risk, as it bypasses the application's intended data access controls.\nThe exploitability of this vulnerability depends on the attacker's ability to reach the vulnerable endpoint and inject crafted payloads. While the specific entry point is not detailed, the nature of SQLi in web applications typically requires network connectivity to the Tuleap instance. Organizations utilizing Tuleap Enterprise Edition 17.5 are advised to restrict access to the application interface and monitor for suspicious database query patterns until formal security patches are provided by the vendor.",
  "technicalDetails": "The vulnerability is characterized as an improper neutralization of special elements used in an SQL command (CWE-89). In Tuleap Enterprise Edition 17.5, the issue stems from the failure to enforce strict input validation or use parameterized queries (prepared statements) within a specific database-interactive component.\nWhen the application processes a request, it fails to sanitize user-controlled input before including it in the database query string. An attacker can leverage this by supplying crafted SQL syntax, such as UNION-based or Boolean-based payloads, to manipulate the logical structure of the query executed against the backend database.\nThe attack flow generally involves the following stages: 1) Identification of an input vector that communicates with the Tuleap backend database. 2) Injection of a specifically crafted payload containing SQL control characters, such as single quotes, comments, or logical operators (e.g., OR 1=1). 3) Execution of the modified query by the database engine, which causes the application to return unintended dataset results to the attacker. 4) Data exfiltration, where the attacker iteratively extracts sensitive information by observing the application's responses to varying payload structures.\nThis vulnerability is particularly critical due to the potential for data breach and unauthorized information disclosure. Because the application processes requests on behalf of the user, the database engine executes the injected commands with the privilege level of the application's database service account. If the application service account is not sufficiently restricted, an attacker may be able to query internal system tables, meta-data, or sensitive credentials of other users within the Tuleap platform.\nAffected versions are strictly limited to Tuleap Enterprise Edition 17.5. The vulnerability occurs within the application tier; however, the impact is felt directly by the data persistence layer. Successful exploitation typically requires network exposure to the vulnerable Tuleap instance. The lack of parameterized queries prevents the database driver from distinguishing between legitimate data inputs and executable SQL code, allowing for the subversion of the intended application logic. Post-exploitation, an attacker can maintain persistent access to the information retrieval capabilities of the database, leading to long-term data leakage scenarios."
}