Code Vulnerability Remediation Using Historical Revision Tokens
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Solution Overview
Problem
Current software vulnerability remediation processes rely heavily on manual corrections and repetitive scanning, which are time-consuming and do not scale effectively for automated vulnerability remediation.
Innovation Solution
A system and method for tokenizing software code security vulnerabilities, generating generalized remediation tokens based on historical code revisions, and automatically remediating similar issues in new code submissions using these tokens.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual remediation is performed to correct code vulnerabilities, then vulnerability correction effectiveness is improved, but time consumption and processing duration increase significantly
Solution Approach 1:
The system performs preliminary action by pre-processing code packages through security analysis tools to generate vulnerability listings and remediation updates before actual deployment. Historical code revisions are analyzed in advance to create a knowledge base of vulnerability patterns and their corrections, enabling faster automated remediation when similar vulnerabilities are detected in new code.
Solution Approach 2:
The system uses copying by generating generalized remediation tokens that capture the essence of vulnerability patterns from historical code revisions. These tokens are copied and applied to new code packages with similar vulnerability patterns, eliminating the need to manually analyze and correct each vulnerability from scratch, thus reducing time consumption while maintaining correction effectiveness.
2Measurement precision
If manual code review and revision processes are used to detect and correct vulnerabilities, then detection accuracy is improved, but productivity and scalability deteriorate
Solution Approach 1:
The system implements self-service by enabling automated remediation that operates independently without requiring manual intervention for each vulnerability. The generalized remediation tokens automatically identify and correct vulnerabilities in new code packages by matching patterns from historical data, allowing the system to scale productivity while maintaining detection accuracy through consistent application of proven remediation strategies.
Solution Approach 2:
The system uses feedback by continuously analyzing the results of vulnerability detection and remediation processes. Historical code revisions and their outcomes are fed back into the system to refine and update the generalized remediation tokens, improving detection accuracy over time while the automated nature maintains high productivity and scalability.
3Reliability
If repetitive vulnerability scanning is performed manually, then vulnerability detection capability is maintained, but time efficiency and automation level decrease
Solution Approach 1:
The system performs preliminary action by pre-generating vulnerability listings and remediation updates from historical code revisions before they are needed for actual remediation. This advance preparation creates a ready-to-use knowledge base that enables automated scanning and correction of new code packages, maintaining detection capability while significantly increasing automation level and time efficiency.
Solution Approach 2:
The system uses copying by creating generalized remediation tokens that encapsulate vulnerability patterns and their corrections from historical scans. These tokens are copied and applied automatically to new code packages during scanning, maintaining reliable vulnerability detection capability while eliminating the need for manual scanning and correction, thus achieving high automation level.
Data Source
AI summary
Systems and methods automating the process of application code vulnerability remediation. Implementations include building a repository of code revisions as software is checked for security vulnerabilities using or more software analysis tools. In certain implementations, historical code revisions are cataloged and stored in the repository. The revisions may be tokenized and utilized to detect and automatically remediate similar issues when new software packages are submitted to the system.