CWE-1333: Inefficient Regular Expression Complexity

What is Inefficient Regular Expression Complexity?

• Overview: Inefficient Regular Expression Complexity occurs when a regular expression is constructed in a way that causes excessive computational complexity, leading to high CPU usage due to exponential backtracking.

• Exploitation Methods:

• Attackers can exploit this vulnerability by crafting inputs that trigger excessive backtracking.
• Common attack patterns include creating inputs that intentionally cause the regular expression engine to exhaust CPU resources.

• Security Impact:

• Direct consequences include significant CPU consumption leading to performance degradation.
• Potential cascading effects include denial of service as resources are consumed, impacting other operations.
• Business impact includes service downtime, increased operational costs, and potential loss of customer trust.

• Prevention Guidelines:

• Specific code-level fixes include optimizing regular expressions to avoid patterns that cause excessive backtracking.
• Security best practices involve thoroughly testing regular expressions with various inputs to ensure efficiency.
• Recommended tools and frameworks include static analysis tools that can detect inefficient regular expressions and suggest optimizations.

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Technical Details

Likelihood of Exploit: High

Affected Languages: Not Language-Specific

Affected Technologies: Not specified

Vulnerable Code Example

Python Example

import re

def find_pattern(input_string):
    # Vulnerable regex pattern that can cause excessive backtracking
    pattern = re.compile(r'(a+)+b')  # Nested quantifiers can cause exponential backtracking
    return pattern.search(input_string)

# This input can cause backtracking and high CPU usage
input_string = 'aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa!'  # No 'b' to terminate
print(find_pattern(input_string))

Explanation:

• The regular expression (a+)+b is vulnerable because it contains nested quantifiers (+ inside another +). This structure can lead to exponential backtracking when the input string does not contain a terminating 'b', causing high CPU usage and degrading performance.

How to fix Inefficient Regular Expression Complexity?

To fix the inefficient regular expression complexity, you should:

1. Refactor the Regular Expression: Avoid using nested quantifiers that lead to exponential backtracking. Simplify the pattern to remove ambiguity.
2. Use Atomic Groups (if supported): In languages that support it, atomic groups ((?>...)) can prevent backtracking by making the match attempt once and not revisit.
3. Avoid Greedy Patterns: Use more specific patterns to minimize the chance of excessive backtracking.

By simplifying the pattern and removing nested quantifiers, you can prevent inefficient complexity.

Fixed Code Example

Python Example

import re

def find_pattern(input_string):
    # Fixed regex pattern that avoids nested quantifiers
    pattern = re.compile(r'a+b')  # Simplified pattern to eliminate nested quantifiers
    return pattern.search(input_string)

# This input is handled efficiently without risk of high CPU usage
input_string = 'aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab'
print(find_pattern(input_string))

Explanation:

• The fixed regular expression a+b eliminates the nested quantifiers, which prevents backtracking issues.
• This pattern is more efficient and reduces the risk of excessive CPU consumption when processing strings, even if the input string does not contain the terminating 'b'. By simplifying the pattern, the potential for exponential backtracking is removed, ensuring efficient execution.