Description

Improper neutralization of special elements used in an SQL command ('SQL injection') vulnerability in TAC Information Services Internal and External Trade Inc. GOLDENHORN ONEIT allows Blind SQL Injection. This issue affects GOLDENHORN ONEIT: before Göbeklitepe.

Executive Summary

Technical Details

Mitigations

References

Additional Metadata

{
  "score": "8.8",
  "pubDate": "2026-09-04T13:18:15.023Z",
  "pubdate": "2026-09-04T13:18:15.023Z",
  "executiveSummary": "The vulnerability identified in TAC Information Services Internal and External Trade Inc. GOLDENHORN ONEIT is classified as a Blind SQL Injection, specifically stemming from the improper neutralization of special elements used in SQL commands. This flaw permits unauthorized actors to infer data from the backend database by observing the application's response patterns to manipulated queries.\nThe vulnerability affects all versions of GOLDENHORN ONEIT preceding the Göbeklitepe release. Successful exploitation allows an unauthenticated or authenticated attacker—depending on the specific entry point—to extract sensitive information, bypass authentication mechanisms, or potentially interact with the underlying database management system.\nThe risk implication is significant as Blind SQL Injection provides a stealthy mechanism for data exfiltration without requiring direct access to the database or verbose error messages. The attacker's capability is limited to inferential observation but can be automated to dump large volumes of data over time. No specific exploitation requirements beyond network reachability to the vulnerable application instance are noted, making this a critical concern for system integrity and data confidentiality.",
  "technicalDetails": "The vulnerability is rooted in the failure of the application to perform adequate input sanitization or parameterized querying on user-supplied data before incorporating it into dynamic SQL statements. By failing to neutralize special characters and SQL syntax elements, the application allows for the injection of malicious SQL sub-queries into legitimate request parameters.\nAs a Blind SQL Injection, the vulnerability does not manifest through direct data display or error messages returned to the interface. Instead, the attacker utilizes boolean-based or time-based inference techniques. In a boolean-based attack, the attacker injects conditional expressions (e.g., 'AND 1=1' vs 'AND 1=0') and observes changes in the HTTP response body or status code to confirm whether the injected logic evaluated to true or false. In a time-based attack, the attacker executes commands such as 'SLEEP()' or 'WAITFOR DELAY' to induce measurable latency in the application response, confirming the success of the injection if the server delay correlates with the injected command.\nThe attack flow typically follows a systematic discovery and exploitation pattern. First, the attacker identifies a parameter that influences a database query. Second, the attacker probes for injection points by submitting crafted payloads that alter the application's logical output. Once the vulnerability is confirmed, the attacker performs iterative character-by-character extraction of database metadata, schema information, table structures, and sensitive row data (such as credentials or PII) by constructing binary search queries. This process, while slow, is highly effective and can be fully automated using tools designed to interpret the server's boolean or temporal responses.\nThe affected component is the internal database interface layer of GOLDENHORN ONEIT, which processes unsanitized input across various web endpoints. Because the application processes these inputs directly, it is susceptible to any injection-capable parameter within the HTTP request headers, cookies, or body parameters. The post-exploitation impact includes full database compromise, unauthorized modification of data, and potentially administrative access to the underlying server if database permissions are not appropriately restricted. As versions prior to Göbeklitepe lack sufficient input validation controls, the entire product ecosystem within these versions remains at high risk of unauthorized data retrieval and potential manipulation."
}