Virtual Machine Snapshot Recovery With Malicious File Patching
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Solution Overview
Problem
Existing methods for restoring virtual machine snapshots fail to address malicious files, preventing complete restoration and operation of applications, especially when files restrict booting or change access permissions.
Innovation Solution
A system and method for restoring virtual machine data that identifies and patches malicious files, or marks snapshots with similar block signatures as malicious, using processor-executable routines to manage block-level snapshots and generate reports for patching or quarantine.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If complete snapshot restoration is performed without patching files, then restoration speed is improved, but malicious files may disrupt applications and prevent VM operation
Solution Approach 1:
The system performs preliminary scanning of snapshots to identify malicious files before restoration occurs. This advance detection allows the restoration process to proceed with pre-computed patching instructions, maintaining speed while ensuring safety through pre-validated file replacements.
Solution Approach 2:
The system introduces an intermediary patching mechanism that acts between the snapshot restoration and the final VM state. This intermediary layer automatically replaces malicious files with clean versions from known-good snapshots, allowing rapid restoration while blocking harmful content through automated mediation.
2Ease of operation
If sandbox recovery is used to restore VMs, then application operations can be performed, but files may still restrict booting or change access permissions preventing full operation
Solution Approach 1:
The system extracts and removes malicious files from restored snapshots before the VM boots or applications run. By taking out harmful content in advance, the system ensures that only clean files are present in the restored VM, eliminating boot restrictions and permission issues while maintaining full operational capability.
Solution Approach 2:
The system converts the presence of malicious files into a benefit by using them as identification markers. Once detected, these previously harmful files trigger automated patching workflows that replace them with clean versions, transforming the harm into an opportunity for automated security enforcement and system hardening.
3Reliability
If manual file patching is performed during snapshot restoration, then malicious files are removed, but restoration time and resource consumption increase
Solution Approach 1:
The system performs file scanning, malicious content identification, and patching strategy formulation in advance of the actual restoration. These preliminary actions prepare patching instructions and identify all malicious files before restoration begins, allowing the restoration process to proceed with pre-computed instructions rather than performing analysis during restoration.
Solution Approach 2:
The system implements selective patching by focusing only on specific malicious files identified in the snapshot, rather than processing all files. This partial action approach applies patching only where necessary, reducing overall restoration time while maintaining comprehensive security by targeting all detected malicious content.
4Measurement precision
If block-level snapshots are scanned to identify malicious files, then accurate detection is achieved, but scanning time and computational resources increase
Solution Approach 1:
The system segments the snapshot into block-level units for scanning, allowing parallel processing of different blocks. This segmentation enables the scanning operation to be divided into independent tasks that can be processed concurrently, reducing overall scanning time and computational overhead while maintaining comprehensive coverage of all snapshot data.
Solution Approach 2:
The system performs scanning with focused precision on block-level data structures rather than exhaustive file-by-file analysis. By targeting specific block signatures and metadata that indicate malicious content, the system achieves accurate detection with reduced computational effort compared to complete content analysis of all snapshot files.
Data Source
AI summary
The invention relates to a system and method for restoring data of a virtual machine. The system includes a memory for storing one or more processor-executable routines, and a processor communicatively coupled to the memory to execute the one or more processor-executable routines to access a plurality of virtual machine snapshots of the virtual machine from a storage. The snapshots include block-level snapshots. The processor is configured to scan the plurality of virtual machine snapshots to identify one or more malicious files present in the snapshots, and generate a report with details of malicious files present in the snapshots. The processor is configured to implement a first workflow to patch the identified malicious files while restoring the data. The processor is further configured to implement a second workflow to identify snapshots that comprise block signatures similar to the malicious files and to mark the identified snapshots as malicious snapshots.