Static Analysis for CSRF Vulnerability Detection in Software
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Solution Overview
Problem
Current server-based anti-CSRF mechanisms rely on proper implementation and testing by website developers to protect against cross-site request forgery (CSRF) attacks, lacking a systematic method to determine the vulnerability of computer software applications to such attacks.
Innovation Solution
A system that includes a static analyzer to identify defense operations, variables, and security-sensitive operations within a software application, determining if control-flow predicates use data-flow dependent variables to make branching decisions and if these decisions are based on values from external sources, thereby assessing the application's safety from CSRF attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If server-based anti-CSRF mechanisms are implemented, then protection against CSRF attacks is improved, but the complexity of implementation and testing increases
Solution Approach 1:
The system performs automatic static analysis of the software application to determine CSRF vulnerability without requiring developer intervention for testing. The analyzer independently identifies defense operations, tracks data-flow dependent variables, and evaluates control-flow predicates to assess security, enabling the system to self-verify its own security posture.
Solution Approach 2:
The system performs security analysis in advance of deployment by statically analyzing the software application's source code or bytecode. It identifies defense operations against CSRF attacks, tracks variable dependencies, and determines vulnerability status before the application is deployed, allowing developers to fix issues beforehand.
2Reliability
If developer testing is performed to verify CSRF protection, then security reliability is improved, but time consumption and resource usage increase
Solution Approach 1:
The system replaces manual developer testing with automated static analysis. Instead of developers manually reviewing code and testing CSRF protection, the system uses computer-based analysis to automatically identify defense operations, track data-flow dependencies, and determine vulnerability status, significantly reducing time and resource consumption.
Solution Approach 2:
The system introduces an intermediary static analysis tool between the developer and the security verification process. This intermediary automatically performs the complex analysis of defense operations and data-flow dependencies, bridging the gap between code implementation and security assessment without requiring direct developer involvement in the testing process.
3Measurement precision
If comprehensive security analysis is performed on all operations, then detection precision is improved, but the complexity of analysis increases
Solution Approach 1:
The system segments the security analysis into distinct components: identifying defense operations, tracking data-flow dependent variables, analyzing control-flow predicates, and evaluating security-sensitive operations. Each component handles a specific aspect of the analysis, making the overall complex task manageable and systematic while maintaining high detection precision.
Solution Approach 2:
The system applies different analysis techniques to different parts of the code based on their security relevance. It specifically focuses on defense operations and their data-flow dependent variables, applying rigorous analysis only where needed rather than uniformly to all code, thus maintaining precision while managing complexity.
Data Source
AI summary
Determining the vulnerability of computer software applications to attacks by identifying a defense-related variable within a computer software application that is assigned results of a defense operation defending against a predefined type of attack, identifying a control-flow predicate dominating a security-sensitive operation within the application, identifying a data-flow dependent variable in the application that is data-flow dependent on the defense-related variable, determining whether the control-flow predicate uses the data-flow dependent variable to make a branching decision and whether a control-flow path leading to the security-sensitive operation is taken only if the data-flow dependent variable is compared against a value of a predefined type, determining that the security-sensitive operation is safe from the attack if both control-flow conditions are true, and determining that the application is safe from the attack if all security-sensitive operations in the application are determined to be safe from the attack.