CVE-2026-84993 Vulnerability Analysis & Exploit Details

CVE-2026-84993
Vulnerability Scoring

6.5
/10
High Risk

If left unpatched, CVE-2026-84993 could lead to major system disruptions or data loss.

Attack Complexity Details

  • Attack Complexity: Low
    Exploits can be performed without significant complexity or special conditions.
  • Attack Vector: Network
    Vulnerability is exploitable over a network without physical access.
  • Privileges Required: Low
    Some privileges are necessary to exploit the vulnerability.
  • Scope: Unchanged
    Exploit remains within the originally vulnerable component.
  • User Interaction: None
    No user interaction is necessary for exploitation.

CVE-2026-84993 Details

Status: Received on 16 Sep 2026, 17:18 UTC

Published on: 16 Sep 2026, 17:18 UTC

CVSS Release: version 3

CVSS3 Source

security-advisories@github.com

CVSS3 Type

Secondary

CVSS3 Vector

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N

CVE-2026-84993 Vulnerability Summary

CVE-2026-84993: MikroORM is a TypeScript ORM for Node.js based on Data Mapper, Unit of Work and Identity Map patterns. Prior to 6.6.16 and 7.1.7, the shared SQL layer validates the field key of an orderBy clause but does not validate its direction value before AbstractSqlPlatform.getOrderByExpression concatenates it into an ORDER BY clause. Applications that bind attacker-controlled request data to the direction in em.find(), em.findOne(), em.findAndCount(), QueryBuilder.orderBy(), or QueryBuilderHelper.getQueryOrderFromObject() can permit a raw SQL fragment that performs blind or boolean extraction of data available to the database account. The BaseMySqlPlatform and MsSqlPlatform fallthrough paths have the same behavior, affecting SQLite, PostgreSQL, MySQL, MariaDB, MSSQL, libSQL, and Oracle drivers, while MongoDB is not affected. This issue is fixed in versions 6.6.16 and 7.1.7.

Assessing the Risk of CVE-2026-84993

Access Complexity Graph

The exploitability of CVE-2026-84993 depends on two key factors: attack complexity (the level of effort required to execute an exploit) and privileges required (the access level an attacker needs).

Exploitability Analysis for CVE-2026-84993

CVE-2026-84993 presents an accessible attack vector with minimal effort required. Restricting access controls and implementing security updates are critical to reducing exploitation risks.

Understanding AC and PR

A lower complexity and fewer privilege requirements make exploitation easier. Security teams should evaluate these aspects to determine the urgency of mitigation strategies, such as patch management and access control policies.

Attack Complexity (AC) measures the difficulty in executing an exploit. A high AC means that specific conditions must be met, making an attack more challenging, while a low AC means the vulnerability can be exploited with minimal effort.

Privileges Required (PR) determine the level of system access necessary for an attack. Vulnerabilities requiring no privileges are more accessible to attackers, whereas high privilege requirements limit exploitation to authorized users with elevated access.

CVSS Score Breakdown Chart

Above is the CVSS Sub-score Breakdown for CVE-2026-84993, illustrating how Base, Impact, and Exploitability factors combine to form the overall severity rating. A higher sub-score typically indicates a more severe or easier-to-exploit vulnerability.

CIA Impact Analysis

Below is the Impact Analysis for CVE-2026-84993, showing how Confidentiality, Integrity, and Availability might be affected if the vulnerability is exploited. Higher values usually signal greater potential damage.

  • Confidentiality: High
    Exploiting CVE-2026-84993 can result in unauthorized access to sensitive data, severely compromising data privacy.
  • Integrity: None
    CVE-2026-84993 poses no threat to data integrity.
  • Availability: None
    CVE-2026-84993 does not impact system availability.

CVE-2026-84993 References

External References

CWE Common Weakness Enumeration

CWE-89

CAPEC Common Attack Pattern Enumeration and Classification

  • Command Line Execution through SQL Injection CAPEC-108 An attacker uses standard SQL injection methods to inject data into the command line for execution. This could be done directly through misuse of directives such as MSSQL_xp_cmdshell or indirectly through injection of data into the database that would be interpreted as shell commands. Sometime later, an unscrupulous backend application (or could be part of the functionality of the same application) fetches the injected data stored in the database and uses this data as command line arguments without performing proper validation. The malicious data escapes that data plane by spawning new commands to be executed on the host.
  • Object Relational Mapping Injection CAPEC-109 An attacker leverages a weakness present in the database access layer code generated with an Object Relational Mapping (ORM) tool or a weakness in the way that a developer used a persistence framework to inject their own SQL commands to be executed against the underlying database. The attack here is similar to plain SQL injection, except that the application does not use JDBC to directly talk to the database, but instead it uses a data access layer generated by an ORM tool or framework (e.g. Hibernate). While most of the time code generated by an ORM tool contains safe access methods that are immune to SQL injection, sometimes either due to some weakness in the generated code or due to the fact that the developer failed to use the generated access methods properly, SQL injection is still possible.
  • SQL Injection through SOAP Parameter Tampering CAPEC-110 An attacker modifies the parameters of the SOAP message that is sent from the service consumer to the service provider to initiate a SQL injection attack. On the service provider side, the SOAP message is parsed and parameters are not properly validated before being used to access a database in a way that does not use parameter binding, thus enabling the attacker to control the structure of the executed SQL query. This pattern describes a SQL injection attack with the delivery mechanism being a SOAP message.
  • Expanding Control over the Operating System from the Database CAPEC-470 An attacker is able to leverage access gained to the database to read / write data to the file system, compromise the operating system, create a tunnel for accessing the host machine, and use this access to potentially attack other machines on the same network as the database machine. Traditionally SQL injections attacks are viewed as a way to gain unauthorized read access to the data stored in the database, modify the data in the database, delete the data, etc. However, almost every data base management system (DBMS) system includes facilities that if compromised allow an attacker complete access to the file system, operating system, and full access to the host running the database. The attacker can then use this privileged access to launch subsequent attacks. These facilities include dropping into a command shell, creating user defined functions that can call system level libraries present on the host machine, stored procedures, etc.
  • SQL Injection CAPEC-66 This attack exploits target software that constructs SQL statements based on user input. An attacker crafts input strings so that when the target software constructs SQL statements based on the input, the resulting SQL statement performs actions other than those the application intended. SQL Injection results from failure of the application to appropriately validate input.
  • Blind SQL Injection CAPEC-7 Blind SQL Injection results from an insufficient mitigation for SQL Injection. Although suppressing database error messages are considered best practice, the suppression alone is not sufficient to prevent SQL Injection. Blind SQL Injection is a form of SQL Injection that overcomes the lack of error messages. Without the error messages that facilitate SQL Injection, the adversary constructs input strings that probe the target through simple Boolean SQL expressions. The adversary can determine if the syntax and structure of the injection was successful based on whether the query was executed or not. Applied iteratively, the adversary determines how and where the target is vulnerable to SQL Injection.

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