Your own service or solution that publishes events to Event Grid so that your customers can subscribe to them. Event Grid provides two type of resources you can use depending on your requirements.
Microsoft Sentinel is a scalable, cloud-native, security information and event management (SIEM) and security orchestration, automation, and response (SOAR) solution. Microsoft Sentinel delivers intelligent security analytics and threat intelligence across the enterprise, providing a single solution for attack detection, threat visibility, proactive hunting, and threat response.
Event – Resources used on the event [Introduction to Microsoft Azure Security]
Microsoft Defender for Cloud helps you prevent, detect, and respond to threats with increased visibility into and control over the security of your Azure resources. It provides integrated security monitoring and policy management across your Azure subscriptions, helps detect threats that might otherwise go unnoticed, and works with a broad ecosystem of security solutions.
Azure Monitor offers visualization, query, routing, alerting, auto scale, and automation on data both from the Azure subscription (Activity Log) and each individual Azure resource (Resource Logs). You can use Azure Monitor to alert you on security-related events that are generated in Azure logs.
Defender for Cloud helps you prevent, detect, and respond to threats, and provides you increased visibility into, and control over, the security of your Azure resources. It provides integrated Security monitoring and policy management across your Azure subscriptions, helps detect threats that might otherwise go unnoticed, and works with a broad ecosystem of security solutions.
Microsoft Sentinel has built-in connectors to the broader security and applications ecosystems for non-Microsoft solutions. You can also use common event format, Syslog, or REST-API to connect your data sources with Microsoft Sentinel.
Events that occur in end-user devices or IT systems are commonly recorded in log files. Operating systems record events using log files. Each operating system uses its own log files, and applications and hardware devices also generate logs. Security teams can use security logs to track users on the corporate network, identify suspicious activity and detect vulnerabilities.
Most security and IT organizations find that systems generate more log information than they can process. Event and log management tools help analyze logs, monitor important events recorded in logs, and leverage them to identify and investigate security incidents.
The Windows operating system logs activity on software or hardware components. Administrators can access this information to detect and troubleshoot issues. Six default categories are used to classify events:
The Windows system called Event Viewer can be used to view event logs across all the above categories. Event Viewer displays information about an event, including the date and time, username, computer, source, and type.
While all types of events could be relevant in the investigation of a security incident, security logs are of special significance. Windows generates a security log entry upon login attempts, and logs additional information if the login attempt succeeds. The types of events logged are:
Perform a risk assessment for Linux systems in your organization, and determine what level of logging they need, how logs should be reviewed and which log events should generate security alerts. In most cases you will need to log the following information about a Linux system for security purposes:
iOS does not log events, however it does log application crash reports. iOS 10.0 and later offers an API that can be used to log application events. You can use crash reports and the logging API to find and investigate errors generated by your applications, either during development or in production.
SIEM logging is the process of aggregating and monitoring logs for security purposes. SIEM systems are used by security teams to collect event data from IT systems and security tools across an organization, and use it to identify suspicious behavior that might signify a security incident.
Traditionally, SIEMs generated alerts from logs by using correlation rules. A correlation rule specifies a series of events and specific logs values or ranges of values that may indicate a security threat (for example, three or more failed login attempts). Another way to extract security risks from logs is a vulnerability analysis where automated scanners can scan networks for software vulnerabilities that can be targeted by attackers, and some of these scans rely on logs.
With AWS, you control where your data is stored, who can access it, and what resources your organization is consuming at any given moment. Fine-grain identity and access controls combined with continuous monitoring for near real-time security information ensures that the right resources have the right access at all times, wherever your information is stored. Reduce risk as you scale by using our security automation and activity monitoring services to detect suspicious security events, like configuration changes, across your ecosystem. You can even integrate our services with your existing solutions to support existing workflows, streamline your operations, and simplify compliance reporting.
Resources owned by the protected organization that are saved outside of the organization, including copy or transfer operations.
Attempts to access BigQuery resources that are protected by VPC Service Controls.
Exfiltration: BigQuery Data Extraction DATA_EXFILTRATION_BIG_QUERY_EXTRACTION Cloud Audit Logs: BigQueryAuditMetadata data access logs Permissions: DATA_READ Detects the following scenarios: A BigQuery resource owned by the protected organization is saved, through extraction operations, to a Cloud Storage bucket outside the organization.
A BigQuery resource owned by the protected organization is saved, through extraction operations, to a publicly accessible Cloud Storage bucket owned by that organization.
This finding isn't available for project-level activations. Exfiltration: BigQuery Data to Google Drive DATA_EXFILTRATION_BIG_QUERY_TO_GOOGLE_DRIVE Cloud Audit Logs: BigQueryAuditMetadata data access logs Permissions: DATA_READ Detects the following: A BigQuery resource owned by the protected organization is saved, through extraction operations, to a Google Drive folder.
Exfiltration: Cloud SQL Data Exfiltration CLOUDSQL_EXFIL_EXPORT_TO_EXTERNAL_GCS CLOUDSQL_EXFIL_EXPORT_TO_PUBLIC_GCS Cloud Audit Logs: MySQL data access logs PostgreSQL data access logs SQL Server data access logs Detects the following scenarios: Live instance data exported to a Cloud Storage bucket outside of the organization.
Live instance data exported to a Cloud Storage bucket that is owned by the organization and is publicly accessible.
This finding isn't available for project-level activations. Exfiltration: Cloud SQL Restore Backup to External Organization CLOUDSQL_EXFIL_RESTORE_BACKUP_TO_EXTERNAL_INSTANCE Cloud Audit Logs: MySQL admin activity logs PostgreSQL admin activity logs SQL Server admin activity logs Detects events where the backup of a Cloud SQL instance is restored to an instance outside of the organization.
The windows operating system can generate an event log in response to activity on any of its hardware or software components. Network security and operations analysts can use specialized software tools to aggregate and analyze these logs, detect patterns and trends, and respond to incidents or potential user issues. Windows is pre-configured to classify events into six categories:
iOS takes a unique approach to event log generation when compared to other operating systems. iOS does not log every event that happens in the system, but it does generate documentation for application crashes. Later versions of iOS (10.0 and beyond) offer an API that can be used to log application events that take place on the system. The iOS logging API allows network administrators to access log file data from:
Log files capture things like unsuccessful log-in attempts, failed user authentication, or unexpected server overloads, all of which can signal to an analyst that a cyber attack might be in progress. The best security monitoring tools can send alerts and automate responses as soon as these events are detected on the network.
AWS security services such as Amazon GuardDuty, Amazon Macie, and AWS Security Hub, as well as partner security products, can be used to identify potential security issues, or findings. These services are really helpful in alerting you when and where there is possible unauthorized access or suspicious behavior in your AWS deployment. However, sometimes there are security findings that you would like to perform deeper investigations of the events that led to the findings to remediate the root cause. Determining the root cause of security findings can be a complex process for security analysts that often involves collecting and combining logs from many data sources, using extract, transform, and load (ETL) tools, and custom scripting to organize the data.
Amazon Detective simplifies this process by enabling your security teams to easily investigate and quickly get to the root cause of a finding. Detective can analyze trillions of events from multiple data sources such as Amazon Virtual Private Cloud (VPC) Flow Logs, AWS CloudTrail, and Amazon GuardDuty. Detective uses these events to automatically create a unified, interactive view of your resources, users, and the interactions between them over time. With this unified view, you can visualize all the details and context in one place to identify the underlying reasons for the findings, drill down into relevant historical activities, and quickly determine the root cause. 2ff7e9595c
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