CWE-206: Observable Internal Behavioral Discrepancy

What is Observable Internal Behavioral Discrepancy?

• Overview: CWE-206, Observable Internal Behavioral Discrepancy, occurs when a product reveals its internal state or decision points through observable behaviors, allowing attackers to gain insights that can be used to their advantage.

• Exploitation Methods:

• Attackers can exploit discrepancies in behavior to infer internal logic or state information, such as the presence or absence of a username in a login process.
• Common attack patterns include analyzing response times, error messages, or other subtle differences in behavior to deduce sensitive information.

• Security Impact:

• Direct consequences include unauthorized access or information disclosure, as attackers can deduce valid usernames or other sensitive information.
• Potential cascading effects may involve further exploitation of the system using the gathered information, leading to broader security breaches.
• Business impact includes potential data breaches, loss of customer trust, and compliance violations.

• Prevention Guidelines:

• Specific code-level fixes include ensuring that all error messages and response behaviors are consistent and do not reveal unnecessary information.
• Security best practices involve implementing uniform responses for all similar actions and decisions within the application.
• Recommended tools and frameworks include using security testing tools that can identify behavioral discrepancies and applying consistent coding standards to minimize observable differences.

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Technical Details

Likelihood of Exploit: Not specified

Affected Languages: Not Language-Specific

Affected Technologies: Not specified

Vulnerable Code Example

import time

def authenticate_user(username, password):
    # This function checks credentials and returns True if they are correct
    if username == "admin" and password == "securepassword":
        return True
    # Introduces a time delay for incorrect credentials
    time.sleep(2)
    return False

Explanation of Vulnerability

In this vulnerable code example, the function authenticate_user introduces a time delay when credentials are incorrect. An attacker can measure the response time to differentiate between valid and invalid credentials. This discrepancy allows attackers to enumerate valid usernames or deduce password correctness based on timing differences. This is a classic case of CWE-206, where internal behavior discrepancies are observable through timing.

How to fix Observable Internal Behavioral Discrepancy?

To mitigate this vulnerability, responses should be made consistent in terms of their timing regardless of whether the credentials are valid or not. This can be achieved by ensuring that every authentication attempt takes the same amount of time to process, regardless of its outcome. This approach prevents attackers from using timing attacks to infer the correctness of the credentials.

Fixed Code Example

import time

def authenticate_user(username, password):
    # Standardize processing time for both valid and invalid credentials
    start_time = time.time()
    
    # Check credentials
    is_authenticated = (username == "admin" and password == "securepassword")
    
    # Calculate the time taken and add delay to standardize response time
    time.sleep(max(0, 2 - (time.time() - start_time)))
    return is_authenticated

Explanation of Fix

In the fixed code example, the function authenticate_user captures the start time before any credential checks. After performing the credential verification, it calculates the elapsed time and introduces an additional delay to ensure that the total response time is consistent for both correct and incorrect credentials. This approach prevents attackers from leveraging timing discrepancies to infer sensitive information. The use of max(0, 2 - (time.time() - start_time)) ensures that at least 2 seconds have passed for every authentication attempt, aligning the response time uniformly.