API Reputation Scoring for Real-Time Security Risk Assessment
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Solution Overview
Problem
Enterprise applications using APIs from internal or third-party services face security risks such as data leakage and penetration attacks, with existing technologies failing to effectively assess and mitigate these risks in real-time.
Innovation Solution
A system that employs API reputation scoring by collecting telemetry data from various sources, analyzing it to generate a reputation score, and using this score to define and enforce policies for the API service usage, integrating with CI/CD pipelines to determine deployment policies and mitigate risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If API services are used to enable application functionality, then productivity and service versatility are improved, but security risks such as data leakage and penetration attacks increase
Solution Approach 1:
The system performs preliminary security assessment by collecting telemetry data and generating reputation scores for API services before the application uses them. This advance evaluation identifies security risks in advance, allowing the system to block or monitor potentially harmful API calls before they can cause data leakage or penetration attacks, thus resolving the contradiction between enabling functionality and preventing harm.
Solution Approach 2:
The reputation scoring system acts as an intermediary between the application and the API services. It collects telemetry data from various sources, analyzes security characteristics, and generates reputation scores that mediate the interaction. This intermediary mechanism allows the application to use API services while filtering out harmful ones, thus maintaining productivity while reducing security risks.
2Reliability
If existing security technologies are used to protect API services, then security is improved, but real-time assessment capability is insufficient
Solution Approach 1:
The system continuously collects telemetry data from multiple sources and continuously updates reputation scores for API services. This continuous monitoring and assessment enables real-time detection of security issues, allowing the system to respond immediately to changing security conditions, thus achieving both reliable security protection and real-time assessment capability.
Solution Approach 2:
The system implements feedback mechanisms by analyzing telemetry data, generating reputation scores, and using these scores to dynamically adjust security policies. The feedback loop allows the system to learn from actual API usage patterns and security incidents, improving both the reliability of security protection and the speed of real-time assessment through iterative optimization.
3Measurement precision
If comprehensive telemetry collection is performed to assess API security, then measurement precision is improved, but system complexity increases
Solution Approach 1:
The system segments the telemetry collection process by organizing data from multiple sources into distinct categories (e.g., authentication telemetry, data transmission telemetry, error rate telemetry). This segmentation allows the system to maintain comprehensive measurement precision while managing complexity through structured organization and modular processing of different telemetry types.
Solution Approach 2:
The reputation scoring system serves multiple functions: it collects telemetry data, analyzes security characteristics, generates reputation scores, and informs security policies. This multi-functional approach consolidates what would otherwise be separate complex systems into a unified platform, maintaining measurement precision while reducing overall system complexity through functional integration.
Data Source
AI summary
The present disclosure is directed to assessing API service security and may include the steps of identifying an API service called by an application based on information provided by an agent embedded within the application; collecting telemetry associated with the API service, the telemetry collected from one or more telemetry sources and indicating any deficiencies in the API service; generating a reputation score for the API service based on analysis of the collected telemetry; and transmitting the reputation score to at least one of the following: the agent embedded within the application, wherein the reputation score is associated with at least one policy having at least one policy action, and wherein the reputation score is operable to be used by the agent to invoke the at least one policy action relating to use of the API service by the application; or a continuous integration/continuous delivery pipeline associated with the application.