Native Integrations

AWS S3 log monitoring with Log360

Overview

ManageEngine Log360 provides comprehensive monitoring, analysis, and threat detection for Amazon Web Services (AWS) S3 logs. By collecting and correlating S3 Server Access Logs and AWS CloudTrail events for S3, Log360 delivers critical visibility into data access patterns, helps detect security threats and misconfigurations, and ensures your cloud object storage remains secure and compliant with industry regulations.

How Log360 collects and analyzes AWS S3 logs

Log360 integrates directly and securely with your AWS environment to provide automated, real-time log collection.

Collection method:

Native AWS integration: Log360 securely connects to your AWS account using a configured IAM role. It automatically collects S3 Server Access Logs and CloudTrail logs from the designated S3 buckets where they are stored. This agentless method is secure, scalable, and aligns with cloud best practices, requiring no complex software installation on your part.

Once collected, Log360's intelligent parsing engine automatically identifies and enriches the log data, structuring complex events into easy-to-understand reports and dashboards. This provides immediate insights into who is accessing your data, what they are doing, and where they are coming from.

Monitoring capabilities

Log360 collects and analyzes the two primary log sources for S3, providing complete coverage for both operational and security auditing:

S3 server access logs: Records detailed information for every request made to your S3 buckets, including the requester, bucket name, request time, action (e.g., GET, PUT, DELETE), response status, and error codes.
AWS CloudTrail data events for S3: Provides a granular audit trail of API activity on S3 objects. This includes tracking object-level operations like GetObject, DeleteObject, and PutObject, which is essential for detailed security forensics.

Critical AWS S3 events monitored

Log360 tracks essential security and operational events for S3 including:

Changes to bucket policies, ACLs, and public access settings
Unauthorized or anomalous data access (GetObject) from unusual IPs or locations
Deletion of objects (DeleteObject) and buckets (DeleteBucket)
Failed access attempts (403 Forbidden errors) indicating misconfigured permissions or malicious probing
Cross-account access activity
Changes to bucket life cycle, replication, and encryption configurations

Key benefits

Centralized cloud storage visibility: Gain a unified view of all access and configuration changes across all your S3 buckets in a single console.
Data breach detection: Instantly identify suspicious access patterns, potential data exfiltration, and unauthorized activity targeting your sensitive data.
Detection of S3 misconfigurations: Proactively detect and receive alerts on risky changes to bucket policies or public access settings that could lead to a data breach.
Simplified cloud compliance & auditing: Automate the collection and reporting of data access events to meet compliance requirements for PCI DSS, HIPAA, GDPR, and other regulations.

Address key AWS S3 security challenges with Log360

The following table details common challenges and the solutions offered by Log360:

Challenges	Solution offered by Log360
Detecting unauthorized data access	Monitors every access request to your S3 objects, alerting on suspicious activity such as access from unusual IP addresses, unauthorized users, or anomalous data download patterns.
Preventing "leaky" or public buckets	Audits and alerts on changes to S3 bucket policies, ACLs, and public access block settings in real-time, helping you prevent accidental data exposure before it happens.
Investigating data deletion or modification	Provides a clear and immutable audit trail for all PutObject and DeleteObject API calls, enabling rapid investigation into accidental data loss or malicious tampering.
Meeting compliance mandates	Generates detailed reports on data access patterns required for compliance with frameworks like PCI DSS, HIPAA, and GDPR, demonstrating control over sensitive data stored in S3.
Identifying data exfiltration attempts	Uses correlation rules to detect suspicious patterns indicative of data exfiltration, such as a single user accessing an unusually high number of objects or data being accessed from a dormant account.