CWE-369 Base Draft Medium likelihood

Divide By Zero

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

Definition

What is CWE-369?

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

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.

Real-world impact

Real-world CVEs caused by CWE-369

CVE-2007-3268

Invalid size value leads to divide by zero.
CVE-2007-2723

"Empty" content triggers divide by zero.
CVE-2007-2237

Height value of 0 triggers divide by zero.

How attackers exploit it

Step-by-step attacker path

1
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.
2
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.
3
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.
4
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.
5
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.

Vulnerable code example

Vulnerable Java

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.

Vulnerable Java

public int computeAverageResponseTime (int totalTime, int numRequests) {
  	return totalTime / numRequests;
  }

Secure code example

Secure 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.

Secure Java

public int computeAverageResponseTime (int totalTime, int numRequests) throws ArithmeticException {
  	if (numRequests == 0) {
  		System.out.println("Division by zero attempted!");
  		throw ArithmeticException;
  	}
  	return totalTime / numRequests;
  }

What changed: the unsafe sink is replaced (or the input is validated/escaped) so the same payload no longer triggers the weakness.

Prevention checklist

How to prevent CWE-369

Architecture Use safe-by-default frameworks and APIs that prevent the unsafe pattern from being expressible.
Implementation Validate input at trust boundaries; use allowlists, not denylists.
Implementation Apply the principle of least privilege to credentials, file paths, and runtime permissions.
Testing Cover this weakness in CI: SAST rules + targeted unit tests for the data flow.
Operation Monitor logs for the runtime signals listed in the next section.

Detection signals

How to detect CWE-369

Automated Static Analysis High

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 High

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.

CWE-369

Don't catalog this weakness. Prove it's reachable.

Plexicus turns CWE catalogs into evidence: every CWE-pattern is matched against your real code graph, reach is proven on a sandbox clone, and verified findings ship as reviewed PRs.

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Frequently asked questions

What is CWE-369?

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

How serious is CWE-369?

MITRE rates the likelihood of exploit as Medium — exploitation is realistic but typically requires specific conditions.

What languages or platforms are affected by CWE-369?

MITRE has not specified affected platforms for this CWE — it can apply across most application stacks.

How can I prevent CWE-369?

Use safe-by-default frameworks, validate untrusted input at trust boundaries, and apply the principle of least privilege. Cover the data-flow signature in CI with SAST.

How does Plexicus detect and fix CWE-369?

Plexicus's SAST engine matches the data-flow signature for CWE-369 on every commit. When a match is found, our Codex Remedium agent opens a fix PR with the corrected code, tests, and a one-line summary for the reviewer.

Where can I learn more about CWE-369?

MITRE publishes the canonical definition at https://cwe.mitre.org/data/definitions/369.html. You can also reference OWASP and NIST documentation for adjacent guidance.

Related weaknesses

Weaknesses related to CWE-369

CWE-682 Parent

Divide By Zero

What is CWE-369?

Real-world CVEs caused by CWE-369

Step-by-step attacker path

Vulnerable Java

Secure Java

How to prevent CWE-369

How to detect CWE-369

Don't catalog this weakness. Prove it's reachable.

Frequently asked questions

Weaknesses related to CWE-369

Incorrect Calculation

Wrap-around Error

Incorrect Calculation of Buffer Size

Incorrect Bitwise Shift of Integer

Insufficient Precision or Accuracy of a Real Number

Incorrect Calculation of Multi-Byte String Length

Integer Overflow or Wraparound

Integer Underflow (Wrap or Wraparound)

Off-by-one Error

Further reading

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Sample evidence handover

Server-Side Request Forgery in `webhooks/receiver`