Attack Surface: 1. Resource Exhaustion (Lexer-Specific)
- Description: Attackers craft input designed to cause excessive resource consumption (memory or CPU) within the lexer itself.
- Lexer Contribution: The lexer's handling of specific input patterns (e.g., very long tokens, deeply nested structures) leads directly to the resource exhaustion. This is a direct vulnerability of the lexer's implementation.
- Example:
- Extremely Long String Literal: Input containing a string literal that is gigabytes in size, directly impacting the lexer's memory allocation.
- Deeply Nested Comments: Input with deeply nested comments (e.g.,
/* /* /* ... */ */ */) if the lexer supports nested comments, potentially causing stack overflow within the lexer.
- Impact: Denial of Service (DoS) – the application becomes unresponsive or crashes due to the lexer's resource consumption.
- Risk Severity: High
- Mitigation Strategies:
- Token Length Limits: Enforce strict limits on the maximum length of any individual token within the lexer's code. This is a direct mitigation within the lexer.
- Nesting Depth Limits: If the lexer handles nested structures, implement a limit on the maximum nesting depth within the lexer.
- Memory Allocation Monitoring: Monitor memory usage during lexing and terminate the process if it exceeds a predefined threshold. This is a proactive measure within the lexer's operation.
- Input size limit: Limit input that is passed to lexer.
Attack Surface: 2. Regular Expression Denial of Service (ReDoS)
- Description: If the lexer uses regular expressions internally, attackers can craft input that triggers catastrophic backtracking, causing the lexer to consume excessive CPU time.
- Lexer Contribution: The lexer's internal use of vulnerable regular expressions is the direct cause of the vulnerability. The attacker exploits the lexer's implementation.
- Example: A regex like
(a+)+$within the lexer's code, combined with input like "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa!", can cause exponential backtracking within the lexer. - Impact: Denial of Service (DoS) – the application becomes unresponsive due to the lexer's excessive CPU usage.
- Risk Severity: High
- Mitigation Strategies:
- Regex Auditing: Carefully audit all regular expressions used within the lexer for potential ReDoS vulnerabilities.
- Regex Timeout: Implement a timeout mechanism for regular expression evaluation within the lexer.
- Regex Simplification/Refactoring: Rewrite vulnerable regular expressions within the lexer's code to avoid backtracking issues.
- Alternative Lexing Techniques: Consider using alternative lexing techniques that don't rely on regular expressions within the lexer.