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Description
Amazon Macie is an entirely managed service focused on data security and privacy that leverages machine learning and pattern recognition to locate and safeguard sensitive information within AWS.
As organizations grapple with the increasing amounts of data they generate, the task of identifying and securing sensitive information can become more complex, costly, and labor-intensive. By automating the process of discovering sensitive data at scale, Amazon Macie helps reduce the financial burden associated with data protection. It generates an inventory of Amazon S3 buckets, highlighting unencrypted buckets, those that are publicly accessible, and those shared with AWS accounts outside your designated AWS Organizations. Additionally, Macie utilizes machine learning and pattern matching methods on the selected buckets to pinpoint and notify you about sensitive data, including personally identifiable information (PII), ensuring that your organization remains compliant and secure. Furthermore, by streamlining this process, Macie enables businesses to focus more on their core operations while maintaining robust data security practices.
Description
Numerous applications and services hosted in public cloud environments utilize storage solutions like Amazon S3 buckets and Azure Blob storage. As time progresses, these storage solutions may become infected with malware, improperly configured buckets can lead to data breaches, and failure to classify sensitive information can lead to compliance issues and hefty fines. CWP for Storage plays a crucial role by automatically identifying and scanning Amazon S3 buckets and Azure Blobs, ensuring that cloud storage remains both clean and secure. Furthermore, CWP for Storage DLP implements Symantec DLP policy within Amazon S3 to effectively discover and categorize sensitive data. To facilitate remediation and additional actions, AWS Tags can be applied as necessary. Additionally, Cloud Security Posture Management (CSPM) is available for major platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). While containers enhance operational agility, they also introduce a variety of public cloud security challenges and vulnerabilities that can heighten overall risk, necessitating a proactive approach to security management. Organizations must remain vigilant and continually update their security measures to mitigate these evolving threats.
API Access
Has API
API Access
Has API
Integrations
Amazon S3
AWS App Mesh
AWS Security Hub
Amazon Aurora
Amazon CloudWatch
Amazon Detective
Bitcanopy
Chronicle SOAR
F5 BIG-IP SSL Orchestrator
Google Cloud Platform
Integrations
Amazon S3
AWS App Mesh
AWS Security Hub
Amazon Aurora
Amazon CloudWatch
Amazon Detective
Bitcanopy
Chronicle SOAR
F5 BIG-IP SSL Orchestrator
Google Cloud Platform
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/macie/
Vendor Details
Company Name
Broadcom
Founded
1991
Country
United States
Website
www.broadcom.com/products/cyber-security/endpoint/hybrid-cloud/cloud-workload-protection
Product Features
Cybersecurity
AI / Machine Learning
Behavioral Analytics
Endpoint Management
IOC Verification
Incident Management
Tokenization
Vulnerability Scanning
Whitelisting / Blacklisting
Product Features
Cloud Workload Protection
Anomaly Detection
Asset Discovery
Cloud Gap Analysis
Cloud Registry
Data Loss Prevention (DLP)
Data Security
Governance
Logging & Reporting
Machine Learning
Security Audit
Workload Diversity