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CWE Reference

CWE-369: Divide By Zero | Glexia

CWE-369 (Divide By Zero) weakness overview with consequences, detection methods, mitigations, related CVEs and MITRE ATT&CK context.

Release 4.20weaknessDraft

Glexia's Take · Automated analysis

CWE-369: Divide By Zero

Divide By Zero represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.

Executive Impact

  • Availability: DoS: Crash, Exit, or Restart: A Divide by Zero results in a crash.

Developer Pattern

CWE-369 is the kind of defect developers can usually prevent with explicit validation, safer framework defaults, and tests that exercise hostile input or unsafe state transitions.

Automation confidence

high confidence from CWE-369, 4.20.

Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.

Official CWE Definition

CWE-369: Divide By Zero

The product divides a value by zero.

This weakness typically occurs when an unexpected value is provided to the product, or if an error occurs that is not properly detected. It frequently occurs in calculations involving physical dimensions such as size, length, width, and height.

Type
weakness
Abstraction
Base
Status
Draft
Source
MITRE CWE definition

Developer And Remediation Guidance

How teams prevent and detect this weakness

Causes

  • The following Java example contains a function to compute an average but does not validate that the input value used as the denominator is not zero. This will create an exception for attempting to divide by zero. If this error is not handled by Java exception handling, unexpected results can occur. By validating the input value used as the denominator the following code will ensure that a divide by zero error will not cause unexpected results. The following Java code example will validate the input value, output an error message, and throw an exception.
  • The following C/C++ example contains a function that divides two numeric values without verifying that the input value used as the denominator is not zero. This will create an error for attempting to divide by zero, if this error is not caught by the error handling capabilities of the language, unexpected results can occur. By validating the input value used as the denominator the following code will ensure that a divide by zero error will not cause unexpected results. If the method is called and a zero is passed as the second argument a DivideByZero error will be thrown and should be caught by the calling block with an output message indicating the error.
  • The following C# example contains a function that divides two numeric values without verifying that the input value used as the denominator is not zero. This will create an error for attempting to divide by zero, if this error is not caught by the error handling capabilities of the language, unexpected results can occur. The method can be modified to raise, catch and handle the DivideByZeroException if the input value used as the denominator is zero.

Remediation

  • Use safe APIs
  • Centralize the control
  • Add regression tests
  • Review logs and telemetry for attempted abuse

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.)
  • Fuzzing: Fuzz testing (fuzzing) is a powerful technique for generating large numbers of diverse inputs - either randomly or algorithmically - and dynamically invoking the code with those inputs. Even with random inputs, it is often capable of generating unexpected results such as crashes, memory corruption, or resource consumption. Fuzzing effectively produces repeatable test cases that clearly indicate bugs, which helps developers to diagnose the issues.

Mappings

Related CVEs, CWEs, and ATT&CK context

Related CWEs

Related CVEs

Related CVE mappings appear after CVE records are cross-indexed.

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ATT&CK Relevance

ATT&CK relevance is shown only when reviewed or responsibly inferred.