Dynamic Content Security Policy Generation via Dependency Graph Analysis
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Solution Overview
Problem
Websites are vulnerable to digital skimming attacks, where malicious JavaScript code is injected to steal sensitive user information, and existing security measures like Content Security Policy (CSP) and Subresource Integrity (SRI) require manual labor to maintain, making them ineffective against dynamic threats from third-party providers.
Innovation Solution
A system that uses browser automation and crawlers to passively scan web applications, generate enriched dependency graph data by combining script and domain reputation, and dynamically create and deploy content security policies without modifying web pages or application servers, providing continuous protection against digital skimming attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual Content Security Policy (CSP) and Subresource Integrity (SRI) measures are implemented, then security protection is provided, but maintenance requires significant manual labor and cannot keep pace with dynamic threats from third-party providers
Solution Approach 1:
The system enables self-service by automatically monitoring third-party dependencies, detecting skimming attacks, and updating CSP/SRI policies without human intervention. The automated system continuously scans for malicious code, identifies compromised third-party resources, and regenerates security policies based on detected threats, eliminating the need for manual security maintenance while keeping pace with dynamic threats
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring web application behavior, detecting anomalies indicative of skimming attacks, and using this information to dynamically update security policies. The system observes third-party resource interactions, gathers intelligence on malicious patterns, and feeds this information back into policy generation to improve security protection adaptively
2Adaptability or versatility
If third-party providers are used to manage web service aspects, then service functionality is enhanced, but security vulnerabilities are introduced through compromised code from these providers
Solution Approach 1:
The system introduces an intermediary security layer between users and third-party providers. This intermediary automatically monitors and analyzes third-party code execution, detects skimming attacks, and blocks malicious activities while allowing legitimate third-party functionality to operate. The intermediary acts as a protective buffer that enables continued use of third-party services while neutralizing their security risks
Solution Approach 2:
The system performs preliminary actions by proactively scanning third-party dependencies for skimming code before attacks can occur. It continuously monitors third-party resources, identifies potential security threats in advance, and pre-generates updated CSP/SRI policies to prevent compromised code from executing. This preliminary detection and response capability blocks attacks before they can compromise user data
3Loss of information
If web resources are crawled and dependency data is collected, then visibility into third-party dependencies is achieved, but system complexity increases
Solution Approach 1:
The system achieves multi-functionality by combining multiple capabilities into a unified platform: automated web resource crawling, dependency graph generation, skimming attack detection, CSP/SRI policy generation, and continuous monitoring. This universal system handles the entire security workflow through integrated components, reducing operational complexity despite the comprehensive functionality provided
Data Source
AI summary
Techniques to facilitate prevention of malicious attacks on a web service are disclosed herein. In at least one implementation, web resources associated with the web service are crawled to obtain information about internal and external web assets associated with the web service. Responses from the internal and external web assets are intercepted and content security policy headers are dynamically injected into the responses to determine internal and external dependency data associated with the internal and external web assets. The internal and external dependency data is processed with script reputation and domain reputation data to generate enriched dependency graph data. The enriched dependency graph data is analyzed to dynamically generate content security policies for the web service, and the dynamically generated content security policies are deployed to protect the web service.