Divide By Zero

Draft Base

Structure: Simple

Description

A divide-by-zero error occurs when software attempts to perform a division operation where the denominator is zero.

Extended Description

This flaw typically happens when user input, external data, or an unexpected program state introduces a zero value into a calculation where it wasn't anticipated. It's especially common in functions handling physical dimensions—like size, length, or coordinates—or in mathematical routines that don't validate their inputs. Without proper checks, the division triggers a runtime error that can crash the application or create an unstable state. Proactively preventing this requires validating all inputs and implementing safeguards before any division operation. While SAST tools can flag the dangerous pattern, Plexicus uses AI to analyze the context and suggest the specific guard clauses or error-handling code needed to fix it, turning a generic warning into an actionable fix. Managing these validation points across a large codebase is challenging; an ASPM platform like Plexicus helps track and prioritize these flaws for consistent remediation.

Common Consequences 1

Scope: Availability

Impact: DoS: Crash, Exit, or Restart

A Divide by Zero results in a crash.

Detection Methods 2

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.)

FuzzingHigh

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.

Demonstrative Examples 3

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.

Code Example:Bad
Java
java

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.

Code Example:Good
Java
java

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.

Code Example:Bad
C
c

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.

Code Example:Good
C
c

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.