API Security Testing via Live Traffic Duplication
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Solution Overview
Problem
Existing security solutions struggle to effectively test and identify vulnerabilities in web-based applications, particularly those targeting application program interfaces (APIs), as they often rely on known patterns of exploitation and lack understanding of API operation details.
Innovation Solution
The system uses live and legitimate user traffic with in-depth knowledge of API business logic to perform security testing. It intercepts and analyzes API traffic, identifies user session data, duplicates suitable traffic, modifies it with malicious code, and sends it to the API destination for analysis, determining if the malicious code resulted in a valid attack.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional security solutions use known patterns of exploitation to test APIs, then the testing process is simpler and faster, but the ability to identify vulnerabilities is limited and less accurate
Solution Approach 1:
The system copies legitimate user traffic patterns and duplicates them to create test requests that mimic real user behavior. By copying actual traffic patterns rather than using predefined attack patterns, the system achieves more accurate vulnerability detection while maintaining manageable complexity through automation of the copying process
Solution Approach 2:
The system modifies parameters of duplicated traffic by injecting malicious code and varying attack parameters to test different vulnerability scenarios. This allows comprehensive testing of API vulnerabilities by changing parameters such as data types, values, and request structures to uncover security flaws that fixed pattern testing would miss
2Reliability
If security testing uses live user traffic with deep API business logic knowledge, then vulnerability identification improves, but the testing process becomes more complex and time-consuming
Solution Approach 1:
The system performs self-service by automatically analyzing intercepted traffic, identifying user sessions, and selecting appropriate traffic patterns for duplication without requiring manual configuration. The automated analysis of business logic and traffic patterns reduces the complexity burden while maintaining high reliability through comprehensive coverage of API operations
Solution Approach 2:
The system performs preliminary actions by intercepting and analyzing legitimate user traffic before generating test requests. By pre-analyzing traffic patterns, user sessions, and API business logic, the system prepares duplicated traffic with embedded malicious code that accurately reflects real attack scenarios, improving reliability without requiring complex manual testing procedures
3Measurement precision
If the system intercepts and analyzes all API traffic to identify vulnerabilities, then comprehensive security testing is achieved, but processing time and computational resources increase
Solution Approach 1:
The system extracts only the necessary traffic patterns and user session data from the intercepted API traffic for duplication and testing. By extracting relevant information such as user sessions, traffic patterns, and business logic rather than processing every detail of all traffic, the system achieves comprehensive vulnerability detection while reducing processing time and computational resource consumption
Data Source
AI summary
Live and legitimate user traffic is used with in depth knowledge of the business logic for an API specification to perform security testing on a set of APIs. The present system intercepts and analyzes application program interface (API) traffic, identifies user session data, and identifies traffic suitable to duplicate. The identified traffic is duplicated and modified by addition of malicious code. The modified code is then sent to its intended API destination, where it is processed as normal. The resulting response and other traffic as well as the API system and optionally other systems, such as datastore systems, are analyzed to determine if the malicious code resulted in a valid attack. Results from the modified code attack attempts are reported to a user.