Metadata Extraction for Early Data Leak Detection
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Solution Overview
Problem
Current methods for detecting exposed information and data leaks rely on internal credentials or web page indexing techniques, which are inadequate for early detection and can be exploited by attackers, and lack the ability to identify metadata for proactive threat identification without credentials.
Innovation Solution
A system and method that extracts metadata from publicly exposed files, uses pattern matching to identify sensitive information, and proactively searches public sources, including cloud storage and dark web, to detect potential threats without requiring internal credentials.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If internal credentials are required for access to internal systems, then security control is maintained, but detection of exposed information is delayed until after a breach occurs
Solution Approach 1:
The system performs preliminary actions by proactively searching public sources (data brokers, dark web, cloud storage) for exposed organizational information before attackers can exploit it. Metadata extraction and pattern matching are conducted in advance to identify compromised credentials, API keys, and sensitive data, enabling early warning and response before actual breaches occur.
2Difficulty of detecting and measuring
If web page indexing techniques are used to monitor adversary conversations, then exposed files can be detected, but the method requires API access and keyword scanning that limits utility
Solution Approach 1:
The system extracts and analyzes metadata from publicly accessible files without requiring internal API access or credential-based authentication. By focusing on metadata extraction from open sources rather than requiring system integration, the solution eliminates complex API dependencies while maintaining detection capability.
Solution Approach 2:
The system performs self-service by autonomously searching public sources, extracting metadata, and identifying exposed information without requiring organizational credentials or manual configuration. The automated pattern matching and metadata analysis enable the system to independently detect data leaks without human intervention or system access permissions.
3Loss of information
If metadata collection features are added to applications, then digital footprint inventory is improved, but adversaries can exploit this metadata for reconnaissance
Solution Approach 1:
The system converts the harmful effect of metadata exposure into a beneficial security feature by using the same metadata that adversaries exploit for reconnaissance as the basis for detecting data leaks. By monitoring public sources for exposed metadata and comparing it against known organizational patterns, the system turns adversary intelligence-gathering techniques into a detection mechanism that identifies compromised information.
Data Source
AI summary
The invention includes systems and methods for detecting exposed secrets using a combination of searches of metadata extracted from publicly exposed files, and searches of the exposed files for pattern matches to identify confidential or sensitive information. Significantly, the subject invention overcomes shortcomings found in the prior art in data leak detection and enables early identification of data leaks so users may take more proactive steps against system infiltration by unauthorized persons engaged in illegal or otherwise troublesome activities.