What is Inefficient Algorithmic Complexity (CWE-407)?

TL;DR: Inefficient Algorithmic Complexity (CWE-407) is a vulnerability where inefficient worst-case computational complexity can be exploited by attackers, leading to resource consumption issues. Fixing this involves optimizing algorithms and validating inputs properly.

What is Inefficient Algorithmic Complexity?

Inefficient Algorithmic Complexity (CWE-407) is a type of vulnerability where an algorithm has inefficient worst-case computational complexity that can be triggered by crafted manipulations. As defined by the MITRE Corporation under CWE-407, and classified by the OWASP Foundation as not directly mapped to any specific category.

Quick Summary

Inefficient Algorithmic Complexity occurs when an algorithm’s performance degrades significantly due to poor design choices or lack of optimization. This can lead to resource consumption issues such as CPU and memory exhaustion, causing denial of service attacks. Jump to: Overview · How It Works · Business Impact · Attack Scenario · Detection · Fixes

Jump to: Quick Summary · Inefficient Algorithmic Complexity Overview · How Inefficient Algorithmic Complexity Works · Business Impact of Inefficient Algorithmic Complexity · Inefficient Algorithmic Complexity Attack Scenario · How to Detect Inefficient Algorithmic Complexity · How to Fix Inefficient Algorithmic Complexity · Framework-Specific Fixes for Inefficient Algorithmic Complexity · How to Ask AI to Check Your Code for Inefficient Algorithmic Complexity · Inefficient Algorithmic Complexity Best Practices Checklist · Inefficient Algorithmic Complexity FAQ · Vulnerabilities Related to Inefficient Algorithmic Complexity · References · Scan Your Own Site

Inefficient Algorithmic Complexity Overview

What

Inefficient Algorithmic Complexity is a vulnerability where an algorithm’s worst-case computational complexity can be triggered by crafted manipulations, leading to resource consumption issues.

Why it matters

This inefficiency can cause denial of service attacks by forcing the system into high CPU or memory usage states.

Where it occurs

It affects applications that use poorly optimized algorithms without proper input validation and boundary checking.

Who is affected

Applications with inefficient algorithms are at risk, especially those exposed to untrusted inputs.

Who is NOT affected

Systems already using efficient algorithms and robust input validation mechanisms are not vulnerable.

How Inefficient Algorithmic Complexity Works

Root Cause

The root cause lies in the design of an algorithm that has poor worst-case computational complexity. This can be exploited by attackers to trigger resource consumption issues.

Attack Flow

1. An attacker crafts inputs to manipulate the algorithm into its worst-case scenario.
2. The manipulated input causes excessive CPU or memory usage, leading to a denial of service condition.

Prerequisites to Exploit

• The algorithm must have inefficient worst-case computational complexity.
• The system must be exposed to untrusted inputs without proper validation.

Vulnerable Code

def vulnerable_function(input_size):
    for i in range(input_size):
        for j in range(i, input_size):
            # Perform some operation

This code demonstrates a nested loop that can lead to inefficient worst-case performance if the input size is manipulated by an attacker.

Secure Code

def secure_function(input_size):
    max_iterations = 1000  # Set a reasonable upper limit
    for i in range(min(max_iterations, input_size)):
        for j in range(i, min(max_iterations, input_size)):
            # Perform some operation

The fix involves setting an upper limit on the number of iterations to prevent excessive resource consumption.

Business Impact of Inefficient Algorithmic Complexity

Availability

• Disrupted Services: High CPU or memory usage can cause services to become unresponsive.
• Increased Operational Costs: Resource overuse leads to higher costs for maintaining system performance.

Inefficient Algorithmic Complexity Attack Scenario

1. An attacker identifies an algorithm with inefficient worst-case computational complexity in a web application.
2. The attacker crafts inputs that force the algorithm into its worst-case scenario, causing excessive CPU or memory usage.
3. This resource consumption triggers denial of service conditions, making the application unavailable to legitimate users.

How to Detect Inefficient Algorithmic Complexity

Manual Testing

• Review Algorithms: Check for nested loops and other inefficient constructs without proper termination conditions.
• Performance Profiling: Use profiling tools to identify bottlenecks in algorithm performance.

Automated Scanners (SAST / DAST)

Static analysis can detect inefficient algorithms, while dynamic testing is needed to confirm the impact of crafted inputs on resource consumption.

PenScan Detection

PenScan’s scanner engines such as ZAP and Wapiti can help identify potential inefficiencies in algorithms.

False Positive Guidance

A real finding will show a clear pattern of input manipulation leading to excessive resource usage, while false positives may indicate benign performance issues without malicious intent.

How to Fix Inefficient Algorithmic Complexity

• Optimize algorithms to reduce worst-case computational complexity.
• Implement proper input validation and boundary checking to prevent crafted manipulations.

Framework-Specific Fixes for Inefficient Algorithmic Complexity

Python/Django Example

def secure_function(input_size):
    max_iterations = 1000  # Set a reasonable upper limit
    for i in range(min(max_iterations, input_size)):
        for j in range(i, min(max_iterations, input_size)):
            # Perform some operation

This fix sets an upper limit on the number of iterations to prevent excessive resource consumption.

How to Ask AI to Check Your Code for Inefficient Algorithmic Complexity

Review the following Python code block for potential CWE-407 Inefficient Algorithmic Complexity vulnerabilities and rewrite it using proper optimization techniques:

def vulnerable_function(input_size):
    for i in range(input_size):
        for j in range(i, input_size):
            # Perform some operation

Inefficient Algorithmic Complexity Best Practices Checklist

• ✅ Optimize algorithms to reduce worst-case computational complexity.
• ✅ Implement proper input validation and boundary checking.
• ✅ Use performance profiling tools during development.

Inefficient Algorithmic Complexity FAQ

How does inefficient algorithmic complexity work?

It occurs when an algorithm has a worst-case computational complexity that can be triggered by crafted manipulations, leading to resource consumption issues.

Why is inefficient algorithmic complexity considered a security vulnerability?

An attacker can exploit it to cause denial of service (DoS) by forcing the system into a state with high CPU or memory usage.

Can you provide an example of vulnerable code for inefficient algorithmic complexity?

A function that uses nested loops without proper termination conditions, allowing an attacker to manipulate input size and trigger worst-case performance.

How can I detect inefficiencies in my algorithms programmatically?

performance profiling tools during development to identify bottlenecks early on.

What are the best practices for preventing inefficient algorithmic complexity?

Optimize algorithms, use efficient data structures, and ensure proper input validation and boundary checking.

How can I ask an AI assistant to check my code for inefficiencies related to CWE-407?

Provide the AI with your code snippet and request a review focusing on potential inefficient algorithmic complexity issues.

What are some real-world consequences of inefficient algorithmic complexity?

It can lead to service disruptions, degraded user experience, and increased operational costs due to resource overuse.

Vulnerabilities Related to Inefficient Algorithmic Complexity

| CWE | Name | Relationship | |—|—|—| | CWE-405 | Asymmetric Resource Consumption (Amplification) | ChildOf |

References

• MITRE
• CAPEC
• NVD

Scan Your Own Site

Manual code review catches what you know to look for. An automated scan catches what you didn’t. Scan your own website using PenScan to find Inefficient Algorithmic Complexity and other risks before an attacker does.