Cloud Resource Change Logs for Rapid Misconfiguration Detection
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Solution Overview
Problem
Cloud computing environments face challenges in quickly and accurately detecting complex and slow-developing malicious activities due to the structure and timeliness of data feeds, making it difficult for external threat management facilities to identify potential threats effectively.
Innovation Solution
A threat management facility receives and filters logs of resource modifications from cloud environments, extracts identity information, and fetches resource configuration data via an API to detect potential misconfigurations, issuing threat detections when necessary, thereby deferring high-latency API access until confirmation is required.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If continuous log reporting is used for fast threat detection, then detection speed is improved, but API access latency increases when additional information is needed
Solution Approach 1:
The system performs preliminary actions by continuously collecting and analyzing log data to identify potential misconfigurations before actual threats materialize. The threat management facility proactively monitors cloud resource modifications, extracts identity information, and detects suspicious patterns early, enabling fast threat detection without waiting for API confirmations for every event.
Solution Approach 2:
The patent introduces an intermediary mechanism that decouples the fast log reporting path from the slower API access path. The threat management facility acts as an intermediary that can operate on log data independently, only invoking API calls as a secondary confirmation step when specific conditions are met, thereby minimizing the impact of API latency on overall detection speed.
2Productivity
If API access is deferred until detection confirmation is required, then system efficiency is improved, but detection accuracy may be compromised
Solution Approach 1:
The system applies partial action by using log data alone for initial threat detection without requiring full API confirmation for every case. It performs detection with the available log information and only invokes additional API calls when the initial detection meets specific confidence thresholds or risk criteria, balancing efficiency and accuracy by applying the more resource-intensive verification selectively rather than universally.
Solution Approach 2:
The patent implements local quality by applying different verification strategies to different types of detections. High-confidence detections from log analysis alone receive minimal verification, while low-confidence or high-risk detections trigger full API confirmation workflows. This localized approach to verification quality ensures system efficiency for clear cases while maintaining high accuracy for ambiguous cases.
3Measurement precision
If all resource configuration data is fetched continuously, then detection accuracy is improved, but computational overhead increases
Solution Approach 1:
The system extracts only the specific resource configuration data that is relevant to the detected potential misconfiguration, rather than continuously fetching all configuration data. When a suspicious log entry is identified, the system extracts and fetches only the particular resource configuration needed to confirm that specific detection, significantly reducing computational overhead while maintaining detection accuracy for relevant threats.
Data Source
AI summary
A log of resource modifications in a cloud computing environment is incrementally transmitted to a threat management facility. The threat management facility can analyze the log, along with related identity information, to determine when additional information might be useful to detect a malicious misconfiguration of cloud resources. The threat management facility can then access additional information through an application programming interface, and the additional information can be used to perform a detection, initiate remediation, and so forth. This approach advantageously permits fast detection of potential threats based on the continuous log reporting, while deferring high-latency API access to the cloud platform (and/or other computationally expensive operations) until appropriate for confirming detections that are raised based on the log.