Description

Improper neutralization of special elements used in an SQL command ('SQL injection') vulnerability in HAVELSAN Inc. Sef - AI Chatbot Platform allows SQL Injection. This issue affects Sef - AI Chatbot Platform: before 2.1.

Executive Summary

Technical Details

Mitigations

References

Additional Metadata

{
  "score": "8.8",
  "pubDate": "2026-10-02T10:17:08.567Z",
  "pubdate": "2026-10-02T10:17:08.567Z",
  "executiveSummary": "The HAVELSAN Inc. Sef - AI Chatbot Platform contains an Improper Neutralization of Special Elements used in an SQL Command, commonly classified as SQL Injection (SQLi).\nThis vulnerability exists in versions of the Sef - AI Chatbot Platform prior to 2.1.\nThe flaw arises due to the insufficient sanitization of user-supplied data before it is integrated into database queries.\nAn unauthenticated or authenticated attacker can leverage this weakness to manipulate backend database queries, potentially leading to unauthorized data exfiltration, modification of application state, or complete compromise of the underlying database management system.\nThe risk is critical as successful exploitation allows for the circumvention of application-level security controls, potentially granting the attacker access to sensitive conversational logs, platform configurations, and stored user credentials.\nThere are no specific exploitation prerequisites listed other than reaching the vulnerable interface exposed by the application.",
  "technicalDetails": "The vulnerability is categorized under CWE-89: Improper Neutralization of Special Elements used in an SQL Command. The root cause is the platform's failure to properly parameterize queries or employ adequate input validation mechanisms for user-supplied data inputs that interact with the SQL backend.\nIn the Sef - AI Chatbot Platform, certain entry points—likely web-based request parameters or API inputs—do not adequately neutralize control characters such as single quotes ('), semicolons (;), or comment sequences (--, #). This allows an attacker to inject arbitrary SQL statements into the application's query logic.\nThe attack flow initiates when an attacker crafts a malicious payload containing SQL commands designed to alter the intended logic of the application query. For instance, an attacker could manipulate a WHERE clause to bypass authentication filters or use UNION-based techniques to retrieve metadata, user tables, or content from disparate tables within the database schema.\nGiven the nature of an AI chatbot platform, the application likely handles persistent storage of chat logs and user metadata. An attacker could exploit this vulnerability to perform 'blind' SQL injection, where the database's response is inferred based on time-based delays or boolean logical inference (true/false responses) in the application's output, eventually enabling the extraction of the entire database structure.\nThe vulnerability persists across all versions of the Sef - AI Chatbot Platform prior to 2.1. The lack of parameterized queries (prepared statements) in the application's data access layer means that any input field susceptible to this injection serves as a direct vector for database manipulation.\nPost-exploitation impact includes full database read/write/delete access. Depending on the database service account permissions configured for the platform, the attacker may be able to execute administrative functions, such as reading configuration files via database-specific features or potentially escalating privileges to the underlying server hosting the database if the database service is misconfigured or running with excessive system-level privileges."
}