Authorization Bypass Through User-Controlled SQL Primary Key

Incomplete Variant
Structure: Simple
Description

This vulnerability occurs when an application allows a user to directly control the primary key value used in a SQL query, enabling them to access database records they are not authorized to view.

Extended Description

This flaw typically unfolds in three steps: first, user-supplied data from an untrusted source (like a URL parameter or form field) is accepted without proper validation. Second, this data is directly used to specify a primary key in a SQL statement, such as in a `WHERE` clause. Finally, because the database query does not enforce additional row-level permissions, the user can manipulate the key to retrieve or modify records belonging to other users, effectively bypassing the application's intended authorization checks. Preventing this requires implementing proper access control at the data layer, such as adding checks to ensure the requested record belongs to the current user's session. Managing this at scale is difficult; an ASPM like Plexicus can help you track and remediate these authorization flaws across your entire stack by correlating user flows with data access patterns.

Common Consequences 1
Scope: ConfidentialityIntegrityAccess Control

Impact: Read Application DataModify Application DataBypass Protection Mechanism

Detection Methods 1
Automated Static AnalysisHigh
Automated static analysis, commonly referred to as Static Application Security Testing (SAST), can find some instances of this weakness by analyzing source code (or binary/compiled code) without having to execute it. Typically, this is done by building a model of data flow and control flow, then searching for potentially-vulnerable patterns that connect "sources" (origins of input) with "sinks" (destinations where the data interacts with external components, a lower layer such as the OS, etc.)
Potential Mitigations 2
Phase: Implementation
Assume all input is malicious. Use a standard input validation mechanism to validate all input for length, type, syntax, and business rules before accepting the data. Use an "accept known good" validation strategy.
Phase: Implementation
Use a parameterized query AND make sure that the accepted values conform to the business rules. Construct your SQL statement accordingly.
Demonstrative Examples 1

ID : DX-195

The following code uses a parameterized statement, which escapes metacharacters and prevents SQL injection vulnerabilities, to construct and execute a SQL query that searches for an invoice matching the specified identifier [1]. The identifier is selected from a list of all invoices associated with the current authenticated user.

Code Example:

Bad
C#
c#
The problem is that the developer has not considered all of the possible values of id. Although the interface generates a list of invoice identifiers that belong to the current user, an attacker can bypass this interface to request any desired invoice. Because the code in this example does not check to ensure that the user has permission to access the requested invoice, it will display any invoice, even if it does not belong to the current user.
Applicable Platforms
Languages:
SQL : Often
Technologies:
Database Server : Often
Modes of Introduction
Architecture and Design
Implementation
Taxonomy Mapping
  • Software Fault Patterns