CWE-807: Reliance on Untrusted Inputs in a Security Decision

What is Reliance on Untrusted Inputs in a Security Decision?

• Overview: Reliance on Untrusted Inputs in a Security Decision occurs when a software system bases its security decisions on inputs that can be altered by an untrusted source, potentially allowing attackers to bypass security measures.

• Exploitation Methods:

• Attackers can exploit this vulnerability by manipulating inputs such as cookies, URL parameters, or form fields that the system trusts for making security decisions.
• Common attack patterns include using custom clients to alter HTTP requests, intercepting and modifying data in transit, or using browser extensions to change hidden form fields.

• Security Impact:

• Direct consequences of successful exploitation include unauthorized access to sensitive data or functionalities, privilege escalation, and bypassing authentication or authorization controls.
• Potential cascading effects involve further compromises within the system, leading to data breaches or system integrity issues.
• Business impact can include loss of customer trust, legal liabilities, financial losses, and damage to brand reputation.

• Prevention Guidelines:

• Specific code-level fixes include validating and sanitizing all inputs, implementing strict access controls, and avoiding reliance on client-side data for security decisions.
• Security best practices involve using server-side checks for sensitive operations, employing secure coding standards, and maintaining an up-to-date threat model.
• Recommended tools and frameworks include using libraries that handle cryptographic operations securely, employing web application firewalls (WAFs), and utilizing security testing tools to identify and mitigate potential vulnerabilities.

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Technical Details

Likelihood of Exploit: High

Affected Languages: Not Language-Specific

Affected Technologies: Not specified

Vulnerable Code Example

Python Example

def authenticate_user(data):
    # Untrusted input (data['role']) is being used to make a security decision
    if data['role'] == 'admin':
        return "Access Granted"
    else:
        return "Access Denied"

# Example of how an attacker could exploit this:
user_data = {'role': 'admin'}  # Untrusted input from potentially malicious source
print(authenticate_user(user_data))

Explanation:

• The security decision to grant access is based solely on the 'role' key from data, which is assumed to be trustworthy. An attacker could manipulate this input to gain unauthorized access as an admin.

How to fix Reliance on Untrusted Inputs in a Security Decision?

To fix this vulnerability, follow these best practices:

1. Validate Inputs: Always validate and sanitize inputs from untrusted sources.
2. Use Secure Authentication: Instead of relying on input values like roles, use secure authentication methods such as token-based authentication.
3. Role Verification: Ensure that roles and permissions are verified against a trusted source (e.g., a secure database) rather than the input itself.

Fixed Code Example

Python Example

def is_admin(username):
    # Check the role from a trusted source such as a database
    # Simulate a secure database lookup
    trusted_roles = {'user1': 'admin', 'user2': 'user'}
    return trusted_roles.get(username) == 'admin'

def authenticate_user(data):
    # Validate input by checking against a trusted source
    if 'username' in data and is_admin(data['username']):
        return "Access Granted"
    else:
        return "Access Denied"

# Secure example with username validation
user_data = {'username': 'user1'}  # Only username is trusted
print(authenticate_user(user_data))

Explanation:

• The is_admin function checks the user's role against a trusted source (e.g., a secure database) rather than relying on potentially manipulated input.
• The input is now validated by checking for the presence of a username and verifying it with a trusted source, which mitigates the risk of the security decision being bypassed by an attacker.

Improvements Made:

1. Added proper syntax highlighting for Python code blocks.
2. Removed unnecessary line number comments and ensured code is clear and focused on demonstrating the vulnerability and its fix.
3. Improved comments to better explain the security issues and how they are addressed in the fixed example.
4. Ensured the examples are realistic and follow Python best practices.