Malicious Application Detection via Sandbox Risk Scoring
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Solution Overview
Problem
Existing systems fail to effectively evaluate applications for malicious activity before they are installed on user devices, allowing potentially harmful applications to exfiltrate data or perform malicious actions immediately after installation.
Innovation Solution
A threat management system that intercepts connection data related to application downloads, executes the application in a secure sandbox environment to gather behavioral data, calculates a risk score, and makes a download decision based on this score to prevent malicious applications from being installed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If applications are downloaded directly to user devices without pre-evaluation, then download speed and user convenience are improved, but security reliability deteriorates as malicious applications can execute harmful actions immediately after installation
Solution Approach 1:
The system performs preliminary evaluation of applications in a sandbox environment before they are installed on user devices. The threat management facility intercepts download requests, executes the application in a controlled sandbox, analyzes its behavioral data, and only then allows the download to proceed if the application is deemed safe. This preliminary action prevents malicious applications from reaching user devices.
Solution Approach 2:
The system introduces a sandbox environment as an intermediary between the application source and the user device. The sandbox acts as a mediation layer where applications are executed and evaluated without direct access to user device resources. The threat management facility mediates the download process by intercepting connection data, analyzing application behavior in the sandbox, and making authorization decisions.
2Reliability
If applications are evaluated in a sandbox environment before download, then security reliability is improved, but device complexity and processing time worsen due to additional evaluation infrastructure
Solution Approach 1:
The system segments the application evaluation process from the user device by implementing a separate threat management facility and sandbox environment. The sandbox is isolated from the user device, creating distinct operational segments. Connection data is intercepted and processed separately in the threat management facility, while the actual application execution occurs in the sandbox segment, keeping the user device simple and unaffected.
Solution Approach 2:
The system creates a copy of the application in the sandbox environment for evaluation purposes. Instead of modifying the user device or installing the application directly, the system copies the application to the sandbox where it can be executed and analyzed. This copying approach allows security evaluation without impacting the user device's complexity or resources.
3Measurement precision
If connection data is intercepted and analyzed before download, then measurement precision of malicious activity detection is improved, but loss of time occurs due to additional analysis steps
Solution Approach 1:
The system maintains continuous monitoring and analysis of application behavior throughout the sandbox execution process. Connection data interception and analysis occur continuously during the sandbox evaluation, allowing real-time detection of malicious activities. The threat management facility continuously processes behavioral data and updates risk assessments, ensuring precise detection without unnecessary delays.
Solution Approach 2:
The system rapidly processes connection data and behavioral analysis through automated algorithms and machine learning models. The sandbox execution and analysis are optimized to complete quickly by skipping unnecessary manual review steps for low-risk applications. High-confidence safe applications are approved faster, while only suspicious applications undergo extended analysis, reducing overall evaluation time.
Data Source
AI summary
Systems and methods for methods network activity. The methods include receiving at an interface connection data associated with a request from a first device to download an application from a source, downloading the application to a second device based on the request, and executing, using one or more processors executing instructions stored on memory, the downloaded application to obtain behavioral data of the application. The methods further include assigning, using the one or more processors, a risk score to the application based on the behavioral data of the application to determine whether the application is malicious before the application is downloaded by the first device, and implementing, using the one or more processors, a download decision for the first device based on the assigned risk score, wherein the download decision indicates at least whether the first device is able to download the application associated with the request.