
    Write a function to analyze a customer's authentication pattern and find the time window with the highest security risk by calculating the maximum difference between failed and successful biometric verifications in any continuous sequence of authentication attempts. The authentication pattern is represented as a sequence where '1' indicates a successful verification and '0' indicates a failed attempt. This analysis helps identify periods of potentially compromised account access or suspicious login behavior.
    

    
def find_length(string):
    """
    Write a function to analyze a customer's authentication pattern and find the time window with the highest security risk by calculating the maximum difference between failed and successful biometric verifications in any continuous sequence of authentication attempts. The authentication pattern is represented as a sequence where '1' indicates a successful verification and '0' indicates a failed attempt. This analysis helps identify periods of potentially compromised account access or suspicious login behavior.
    

    """
def find_length(string):
    """
    Write a function to analyze a customer's authentication pattern and find the time window with the highest security risk by calculating the maximum difference between failed and successful biometric verifications in any continuous sequence of authentication attempts. The authentication pattern is represented as a sequence where '1' indicates a successful verification and '0' indicates a failed attempt. This analysis helps identify periods of potentially compromised account access or suspicious login behavior.
    

    """
    n = len(string)
    current_sum = 0
    max_sum = 0
    for i in range(n):
        current_sum += 1 if string[i] == '0' else -1
        if current_sum < 0:
            current_sum = 0
        max_sum = max(current_sum, max_sum)
    return max_sum if max_sum else 0