What is Collapse of Data into Unsafe Value (CWE-182)?

TL;DR: Collapse of Data into Unsafe Value (CWE-182) occurs when data is filtered in a way that causes it to be reduced or "collapsed" into an unsafe value, violating expected security properties. This can be prevented by using input validation strategies.

What is Collapse of Data into Unsafe Value?

Collapse of Data into Unsafe Value (CWE-182) is a type of vulnerability that occurs when data is filtered in a way that causes it to be reduced or "collapsed" into an unsafe value, violating expected security properties. As defined by the MITRE Corporation under CWE-182, this vulnerability can lead to Bypass Protection Mechanism due to Access Control violations.

Quick Summary

Collapse of Data into Unsafe Value (CWE-182) is a critical security vulnerability that occurs when data is filtered in a way that causes it to be reduced or "collapsed" into an unsafe value. This can lead to Bypass Protection Mechanism due to Access Control violations, resulting in potential security breaches and data compromise.

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

Collapse of Data into Unsafe Value Overview

What: Collapse of Data into Unsafe Value (CWE-182) occurs when data is filtered in a way that causes it to be reduced or "collapsed" into an unsafe value.

Why it matters: This can lead to Bypass Protection Mechanism due to Access Control violations, resulting in potential security breaches and data compromise.

Where it occurs: Collapse of Data into Unsafe Value (CWE-182) can occur in any application that filters data, including web applications, APIs, and databases.

Who is affected: Any user who interacts with the affected application may be at risk of experiencing a security breach due to Collapse of Data into Unsafe Value (CWE-182).

Who is NOT affected: Applications that do not filter data or use secure input validation strategies are not affected by this vulnerability.

How Collapse of Data into Unsafe Value Works

Root Cause

Collapse of Data into Unsafe Value (CWE-182) occurs when an application filters data in a way that causes it to be reduced or "collapsed" into an unsafe value. This can happen due to various reasons, including:

• Inadequate input validation
• Insufficient error handling
• Incorrect use of data filtering mechanisms

Attack Flow

1. An attacker sends malicious input to the affected application.
2. The application filters the input in a way that causes it to be reduced or "collapsed" into an unsafe value.
3. The unsafe value is used by the application, leading to potential security breaches and data compromise.

Prerequisites to Exploit

• The attacker must send malicious input to the affected application.
• The application must filter the input in a way that causes it to be reduced or "collapsed" into an unsafe value.

Vulnerable Code

# Vulnerable code: Input is not validated before being used
input_value = request.form['input']
if input_value == 'malicious_input':
    # Perform malicious action

Secure Code

# Secure code: Input is validated before being used
input_value = request.form['input']
if input_value in ['valid_input1', 'valid_input2']:
    # Perform safe action
else:
    raise ValueError('Invalid input')

The vulnerable code does not validate the input before using it, while the secure code validates the input and raises an error if it is invalid.

Business Impact of Collapse of Data into Unsafe Value

Collapse of Data into Unsafe Value (CWE-182) can have significant business impacts, including:

• Confidentiality: Unauthorized access to sensitive data.
• Integrity: Tampering with data or modifying it without authorization.
• Availability: Denial of service or disruption of application functionality.

Collapse of Data into Unsafe Value Attack Scenario

1. An attacker sends malicious input to the affected application.
2. The application filters the input in a way that causes it to be reduced or "collapsed" into an unsafe value.
3. The unsafe value is used by the application, leading to potential security breaches and data compromise.

How to Detect Collapse of Data into Unsafe Value

Manual Testing

• Review the application’s code for inadequate input validation and insufficient error handling.
• Test the application with malicious input to see if it filters the input in a way that causes it to be reduced or "collapsed" into an unsafe value.

Automated Scanners (SAST / DAST)

• Use static analysis tools to identify potential security vulnerabilities, including Collapse of Data into Unsafe Value (CWE-182).
• Use dynamic testing tools to simulate malicious input and detect potential security breaches.

PenScan Detection

PenScan’s scanner engines actively test for this issue and can help you identify vulnerabilities.

False Positive Guidance

When reviewing the results of automated scanners or manual testing, consider the following:

• If a pattern looks risky but is actually safe due to context that a scanner cannot see, it may be a false positive.
• Always review the code manually to confirm the presence of Collapse of Data into Unsafe Value (CWE-182).

How to Fix Collapse of Data into Unsafe Value

Input Validation

• Use input validation strategies that strictly conform to specifications, rejecting any input that does not meet these requirements.

Error Handling

• Implement robust error handling mechanisms to detect and prevent potential security breaches.

Framework-Specific Fixes for Collapse of Data into Unsafe Value

Note: This section will be specific to the framework being used. For example, if the application is built using Java EE, the fix may involve using an EJB-specific annotation or configuration setting.

Java EE

// Vulnerable code: Input is not validated before being used
@Stateless
public class MyBean {
    @Inject
    private EntityManager em;

    public void doSomething() {
        String input = request.getParameter('input');
        // Perform malicious action
    }
}

// Secure code: Input is validated before being used
@Stateless
public class MyBean {
    @Inject
    private EntityManager em;

    public void doSomething() {
        String input = request.getParameter('input');
        if (input.equals('valid_input')) {
            // Perform safe action
        } else {
            throw new IllegalArgumentException('Invalid input');
        }
    }
}

How to Ask AI to Check Your Code for Collapse of Data into Unsafe Value

You can ask AI to review your code block for potential CWE-182 Collapse of Data into Unsafe Value vulnerabilities and rewrite it using input validation.

Collapse of Data into Unsafe Value Best Practices Checklist

✅ Use input validation strategies that strictly conform to specifications, rejecting any input that does not meet these requirements.

✅ Implement robust error handling mechanisms to detect and prevent potential security breaches.

Collapse of Data into Unsafe Value FAQ

How does Collapse of Data into Unsafe Value occur?

It occurs when data is filtered in a way that causes it to be reduced or "collapsed" into an unsafe value, violating expected security properties.

What are the common consequences of Collapse of Data into Unsafe Value?

The common consequences include Bypass Protection Mechanism due to Access Control violations.

How can I prevent Collapse of Data into Unsafe Value?

You can prevent it by assuming all input is malicious and using 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.

What are the potential mitigations for Collapse of Data into Unsafe Value?

The potential mitigations include avoiding making decisions based on names of resources (e.g., files) if those resources can have alternate names, and assuming all input is malicious and using an "accept known good" input validation strategy.

How can I detect Collapse of Data into Unsafe Value?

You can detect it by manually testing for the presence of unsafe values in your application’s data filtering mechanisms.

What are some best practices to follow when dealing with Collapse of Data into Unsafe Value?

Some best practices include assuming all input is malicious and using an "accept known good" input validation strategy, and canonicalizing the name to match that of the file system’s representation of the name.

How can I ask AI to check my code for Collapse of Data into Unsafe Value?

You can ask AI to review your code block for potential CWE-182 Collapse of Data into Unsafe Value vulnerabilities and rewrite it using input validation.

Vulnerabilities Related to Collapse of Data into Unsafe Value

References

• MITRE CWE-182
• 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 Collapse of Data into Unsafe Value and other risks before an attacker does.