Command Injection Detection via Native Fragment Baseline
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Solution Overview
Problem
Command injection attacks exploit software vulnerabilities, allowing attackers to take control of software, steal data, or disrupt operations, and existing solutions like taint propagation are impractical due to performance overhead and complexity.
Innovation Solution
Identifying native command fragments within software and using a matching algorithm to reassemble commands, intercepting and analyzing them to detect and remediate potential attacks without tracking external malicious data, allowing software to continue operating despite attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If taint propagation is used to track external data processed by software, then command injection attacks can be effectively stopped, but performance is severely impacted and complexity increases
Solution Approach 1:
Instead of tracking foreign malicious data (taint propagation), the patent inverts the approach by identifying and tracking native command fragments within the software. The system builds a baseline of legitimate command components from the software's own code, then compares executed commands against this baseline to detect anomalies. This inversion eliminates the need for expensive data flow tracking while maintaining attack detection capability.
Solution Approach 2:
The patent performs preliminary action by extracting and storing native command fragments from the software code before execution. This baseline of legitimate command components is prepared in advance, allowing the system to quickly compare executed commands against known-good patterns during runtime without requiring complex real-time analysis of data origins.
2Reliability
If safe programming practices are used to prevent command injection attacks, then software security is improved, but redesigning legacy software and time-to-market are negatively affected
Solution Approach 1:
The patent introduces an intermediary security layer that sits between the software application and the operating system command interpreter. This mediator intercepts commands, analyzes them against the baseline of native fragments, and blocks malicious commands without requiring modifications to the original software code. This allows legacy software to benefit from security protections without redesign or reimplementation.
Solution Approach 2:
The patent creates a copy or representation of the software's legitimate command structure by extracting native fragments from the code. This baseline model serves as a reference for detecting attacks, allowing the system to identify malicious commands that deviate from the expected pattern without needing to modify the actual software or retrain developers in secure coding practices.
3Measurement precision
If taint propagation tracks all external data through software, then attack detection is improved, but device complexity and computational overhead increase significantly
Solution Approach 1:
The patent extracts only the essential native command fragments from the software code, taking out the specific patterns and components that define legitimate command structure. This extraction approach focuses on the critical elements needed for detection while eliminating the complexity of tracking all external data flows through the entire software system.
Data Source
AI summary
Methods and systems are described for detecting command injection attacks. A positive, taint inference method includes receiving signature fragments on one hand, converting command injection instructions into command fragments on another hand, thus identifying potential attacks upon the condition that a command injection instruction includes critical untrusted parts by using signature fragments. A system detects command injection attacks using this kind of method, and remediates and rejects potential attacks.