Adaptive Security Scan Selection for Software Deployment Changes
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Solution Overview
Problem
Current security scanning in software deployments is inefficient due to indiscriminate scanning that triggers numerous false positives and excessive resource consumption, with multiple scanning engines identifying the same vulnerabilities without contextual awareness of software alterations.
Innovation Solution
An adaptive security scanning system that intelligently selects scanning techniques based on code-level changes, design deviations, and deployment configurations, using AI/ML to optimize resource utilization and reduce noise by dynamically forming a scan chain based on previous scan results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If indiscriminate security scanning is performed across all software changes, then comprehensive vulnerability detection is achieved, but false positives increase and computational resources are excessively consumed
Solution Approach 1:
The patent segments the security scanning process by dividing vulnerabilities into different categories (critical, high, medium, low risk) and applying different scanning intensities and methodologies to each segment. Critical vulnerabilities receive comprehensive scanning while low-risk areas use lighter scanning approaches, thereby maintaining detection completeness while reducing overall computational resource consumption.
Solution Approach 2:
The patent applies local quality by tailoring the scanning approach to specific code regions and vulnerability types. Different scanning techniques and thresholds are applied locally based on the nature of the code being scanned, the type of vulnerability detected, and the associated risk level, rather than using a uniform scanning approach across all code.
2Reliability
If multiple scanning engines are deployed to identify vulnerabilities, then detection coverage is improved, but redundant vulnerability identification increases and assessment efficiency decreases
Solution Approach 1:
The patent merges results from multiple scanning engines through a centralized correlation system that consolidates vulnerability findings. The system combines data from SAST, DAST, SCA, and other scanning tools, eliminating duplicate vulnerability reports and presenting a unified view of security issues, thereby maintaining comprehensive detection coverage while improving assessment efficiency.
Solution Approach 2:
The patent implements feedback mechanisms where results from one scanning engine inform and adjust the operation of other scanning engines. For example, if SAST identifies a potential vulnerability, DAST may adjust its scanning focus accordingly, and SCA results may feedback to refine dependency analysis in subsequent scans, reducing redundant identification while maintaining coverage.
3Ease of operation
If security scanning is performed without contextual awareness of software alterations, then scanning simplicity is maintained, but false positives increase and developer alert volume becomes excessive
Solution Approach 1:
The patent performs preliminary actions by analyzing code changes, commit messages, and software alteration contexts before executing security scans. The system pre-processes information about what has changed in the software, enabling it to contextualize vulnerability findings and reduce false positives while maintaining scanning simplicity through automated contextual analysis.
Data Source
AI summary
Systems and methods for adaptive selection of security scanning in software deployments are disclosed. An embodiment of the present invention is directed to dynamically modifying scope based on specific code changes, third party risks and/or architectural changes. By selectively prioritizing and sequencing the scans, an embodiment of the present invention integrates language framework, third-party risks and design changes into a unified security scan workflow that optimizes efficiency while maintaining strong robust coverage.