CWE-90

Base Abstraction Level
Pillar — Highest-level weakness category
Class — Abstract, language-independent
Base — Specific enough to detect
Variant — Tied to specific technology
Compound — Requires multiple weaknesses
Draft MITRE CWE Status
Stable — Fully reviewed and complete
Draft — Under development, may change
Incomplete — Partially defined by MITRE
Deprecated — No longer recommended
Obsolete — Replaced by another CWE
Improper Neutralization of Special Elements used in an LDAP Query ('LDAP Injection')

Description

The product constructs all or part of an LDAP query using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended LDAP query when it is sent to a downstream component.

Consequences

Confidentiality, Integrity, Availability — Execute Unauthorized Code or Commands, Read Application Data, Modify Application Data

An attacker could include input that changes the LDAP query which allows unintended commands or code to be executed, allows sensitive data to be read or modified or causes other unintended behavior.

Mitigations

Phase: Implementation

Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.

Detection

Automated Static Analysis

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.)