Server Vulnerability Detection via Service Heuristics
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Solution Overview
Problem
Organizations face challenges in efficiently and accurately detecting vulnerabilities on public-facing servers, which can lead to security incidents and data breaches, as traditional methods are resource-intensive or inaccurate.
Innovation Solution
A computer-implemented method and system that sends requests to servers to gather information about services, creates heuristics to parse service information in different formats, and determines vulnerabilities by extracting service identifiers, allowing for automatic detection and remediation of vulnerabilities, as well as calculating vulnerability scores for organizations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional vulnerability detection methods are used, then vulnerabilities can be detected, but the process becomes resource-intensive and less efficient
Solution Approach 1:
The system performs preliminary actions by pre-compiling vulnerability signatures and service identification patterns before actual vulnerability scanning. Heuristics are pre-trained and stored for rapid matching during detection, reducing real-time computational overhead and improving scanning efficiency without requiring intensive resources during the actual detection process.
Solution Approach 2:
The patent creates simplified copies of vulnerability detection logic through heuristic rules that mimic complex vulnerability assessment algorithms. These heuristic copies enable fast, resource-efficient detection by approximating the behavior of full vulnerability scanners without requiring the same computational resources, thus improving productivity while reducing energy consumption.
2Measurement precision
If traditional vulnerability detection methods are used, then vulnerabilities can be detected, but the accuracy is insufficient
Solution Approach 1:
The detection system is segmented into distinct functional modules: service identification module, heuristic matching module, vulnerability signature database, and result analysis module. Each segment handles a specific aspect of detection, improving overall accuracy by specializing functions while managing complexity through modular design. This segmentation allows the system to achieve high measurement precision without becoming unmanageably complex.
Solution Approach 2:
The patent introduces heuristics as intermediary elements that bridge the gap between raw service information and vulnerability determination. These heuristics act as mediators that translate complex service configurations into standardized vulnerability assessments, improving detection accuracy by providing a systematic intermediate processing layer that reduces errors while maintaining manageable system complexity.
3Productivity
If manual service identification is performed, then service information can be obtained, but the process is time-consuming and labor-intensive
Solution Approach 1:
The system implements self-service by automatically extracting service information from server responses without requiring manual intervention. The heuristic engine autonomously identifies services, matches them against vulnerability signatures, and generates vulnerability assessments independently, eliminating time-consuming manual processes and significantly improving productivity while reducing time loss.
Solution Approach 2:
The patent replaces manual mechanical processes of service identification with automated computational heuristics. Instead of human analysts manually examining service responses, the system uses algorithmic pattern matching and automated parsing to extract service information rapidly, substituting mechanical human labor with efficient computational processes that improve speed and reduce time loss.
4Reliability
If comprehensive vulnerability scanning is performed across all services, then all vulnerabilities can be identified, but the complexity of managing different service formats increases
Solution Approach 1:
The patent implements a universal heuristic framework that can handle multiple service formats and protocols through a single unified system. The heuristic engine is designed to adapt to different service types (web services, database services, file services, etc.) using the same core matching logic, enabling comprehensive vulnerability detection across all services while managing format diversity through universal processing rules rather than separate specialized systems.
Data Source
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AI summary
The disclosed computer-implemented method for detecting vulnerabilities on servers may include (i) sending requests to servers for information about services potentially executing on the servers, (ii) receiving, in response to requests, messages from the servers that comprise the information about the services, wherein the set of messages use different formats for transmitting the information, (iii) creating, by analyzing the set of the messages, at least one heuristic that is capable of automatically extracting, from a message, an identifier of a service that executes on a server that sent the message, (iv) extracting, from the message, via the heuristic, the identifier of the service executes on the server that sent the message, and (v) determining, based on the identifier of the service, that the service contributes to a vulnerability on the server that sent the message. Various other methods, systems, and computer-readable media are also disclosed.