Textual Pattern Search Engine for Login Credential Detection
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Solution Overview
Problem
Existing systems fail to effectively detect and prevent the exposure of login credentials in documents, particularly in unstructured data, leading to security risks as malicious actors can obtain sensitive information, which is exacerbated by the use of plaintext documents.
Innovation Solution
Implementing a textual-pattern searching method using a three-segment structure within a regular expression, comprising a username segment, a proximity segment, and a password segment, to identify and isolate login credentials in documents, thereby taking appropriate security actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional search methods are used to detect login credentials in documents, then the search can be performed on all documents, but the detection accuracy is low and false positives are high
Solution Approach 1:
The patent divides the search pattern into three distinct segments: a username segment that matches common username formats, a proximity segment that specifies the distance constraint between username and password, and a password segment that matches common password formats. This segmentation allows the system to precisely identify credential pairs while avoiding false positives from unrelated text matches.
Solution Approach 2:
The patent introduces a spatial dimension to the search by implementing a proximity constraint that specifies the maximum distance between username and password segments. This dimensional constraint transforms the search from a simple text pattern match into a spatially-aware pattern recognition system, significantly improving detection accuracy by eliminating matches that are too far apart to be credible credential pairs.
2Productivity
If a simple search pattern is used, then the search is fast and easy to implement, but it cannot accurately distinguish credentials from other text
Solution Approach 1:
The patent segments the search pattern into distinct username and password portions with a defined proximity relationship. This segmentation enables the system to use efficient pattern matching algorithms while maintaining high accuracy, as each segment can be optimized independently for both speed and precision.
Solution Approach 2:
The patent employs configurable parameters within the proximity segment that allow the search pattern to adapt to different document types and credential formats. By adjusting parameters such as the maximum proximity distance and pattern complexity, the system can optimize the balance between search speed and detection accuracy for specific use cases.
3Adaptability or versatility
If comprehensive search patterns are used to catch all credential variations, then detection coverage is improved, but the complexity of the search system increases
Solution Approach 1:
The patent creates a universal search pattern structure that can match multiple credential formats through configurable segments. The username and password segments can be customized to recognize various formats (alphanumeric, special characters, different lengths) while maintaining the same underlying pattern structure, thus achieving versatility without proportionally increasing system complexity.
Solution Approach 2:
The patent applies different levels of pattern complexity to different segments based on their specific requirements. The username segment may use simpler patterns while the password segment uses more complex patterns to account for greater variability. This localized optimization allows comprehensive coverage while keeping overall system complexity manageable.
4Measurement precision
If manual review of all documents is performed, then false positives can be reduced, but the time and resources required increase significantly
Solution Approach 1:
The patent performs preliminary filtering by applying the three-segment search pattern to identify potential credential pairs before any manual review occurs. The proximity constraint and structured pattern matching pre-screen documents to highlight only the most likely credential exposures, dramatically reducing the volume of material requiring manual verification while maintaining high precision.
Data Source
AI summary
Disclosed herein are embodiments of methods and systems for textual-pattern searching of documents for login credentials. In an embodiment, a computer system obtains a document, and uses a textual-pattern-matching engine to search the document for a portion of the document that matches a contiguous textual search pattern. The contiguous textual search pattern includes a username segment, a proximity segment that is positioned after the username segment in the contiguous textual search pattern, and a password segment that is positioned after the proximity segment in the contiguous textual search pattern. In response to finding at least one portion of the document that matches the contiguous textual search pattern, the computer system takes one or more match-triggered actions such as displaying identified matches, augmenting one or more reports, sending one or more notifications, imposing one or more security measures, and/or the like.