Cloudfall Advanced Threat Hunting
Sold by: 云纷科技
Cloudfall Advanced Threat Hunting Service (Advanced Threat Hunting) is a proactive security defense solution designed to identify and eliminate potential advanced persistent threats (APTs) and other complex cyber attacks in advance through in-depth analysis and threat detection techniques. By simulating hacker attacks, the service actively searches for abnormal behavior in the network to help enterprises prevent and respond to unknown security threats
Overview
Key features: Active detection: Through advanced data analysis and machine learning techniques, we dive deep into networks and systems to actively search for potential security threats, without relying on traditional signatures or known attack patterns.
In-depth threat analysis: Combining the experience of artificial intelligence and security experts, a comprehensive cross-platform and cross-system threat analysis is carried out to discover malicious acts and potential risks hidden in the network.
Quick response: Once a threat is discovered, it is possible to act quickly and take measures such as quarantine and blocking to prevent the spread of the attack and fix the vulnerability in a timely manner.
Continuous optimization: Through in-depth understanding of attack methods and attack paths, detection rules are continuously optimized, defense capabilities are enhanced, and overall security situation awareness is enhanced.
Comprehensive reports and recommendations: Provide detailed threat reports and analysis to help enterprises understand potential threats and provide improved security protection suggestions to improve the overall level of security.
Applicable scenarios: Advanced Persistent Threat (APT) Detection and Response Cross-platform security threat tracking and elimination In-depth security analysis in enterprise network environments Yunfan Cloudfall's advanced threat hunting service helps enterprises identify and effectively respond to hidden security threats in advance, enhance defense capabilities, and ensure the security and business continuity of enterprise information systems.
Highlights
- Active detection and in-depth analysis: Through advanced security analysis technology, it actively searches for potential threats in the network environment. It does not rely on traditional protective measures, and can identify unknown advanced persistent threats (APT) and covert attacks.
- Comprehensive threat hunting: Combine multiple security tools and data sources to carry out comprehensive threat hunting across platforms and systems to ensure that no security gaps are left. Intelligent threat identification: Using machine learning and behavioral analysis, abnormal behavior and potential attack patterns are discovered in real time to improve the accuracy of threat identification.
- Rapid response and repair: Once a threat is discovered, quarantine and remediation measures are taken quickly to prevent the spread of attacks and minimize the impact of security incidents on the enterprise. Continuous optimization and reporting: Based on analysis results, protection policies are continuously optimized, and detailed threat reports and improvement suggestions are provided to help enterprises improve overall security defense capabilities.
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Product associated with this service
Cloudfall RedKernel UEBA was born out of a deep understanding of enterprise security requirements and continuous exploration of technical challenges. With the continuous improvement of enterprise informatization and the continuous evolution of cyber threats, traditional security protection can no longer meet the dual requirements of enterprises for security performance and cost efficiency. Therefore, in order to help enterprises meet increasingly complex security challenges, the RedKernel team developed UEBA (SaaS) products using AI-driven anomaly detection technology.
Cloudfall InsightX - SIEM (hereinafter referred to as IX) provides enterprises with integrated secure data storage and analysis services. The main advantage of IX is that enterprises do not need to consider huge security data storage costs and the performance consumption required to analyze computing engines. They only need to centrally send equipment data that needs to be monitored and analyzed to IX to achieve storage and analysis requirements. At the same time, pre-set security rules and machine learning algorithms and models can truly effectively focus on internal threats and unknown threats.