5 skills · sorted by relevance
Analyze endpoint, cloud storage, and email logs for signs of insider data theft. Use pandas to compare upload volumes with normal user behavior and examine data loss prevention alerts, unusual file access, and activity outside working hours.
Analyze access logs from AWS S3, GCS, and Azure Blob Storage to spot unusual downloads, unfamiliar IP addresses, and request spikes. Compare activity with normal patterns and prioritize findings for suspected data theft investigations.
Test whether a browsing AI agent follows fake security verification instructions that expose stored personal information through URL paths. Examine chained navigation, memory disclosure, and constructed URLs, then document confirmed findings with evidence and mitigation suggestions.
Detects insider data exfiltration by analyzing DLP policy violations, file access patterns, upload volume anomalies, and off-hours activity in endpoint and cloud logs. Uses pandas for behavioral analytics and statistical baselines. Use when investigating insider threats or building user behavior analytics for data loss prevention.
The English summary is being prepared. Showing the original description.
Detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API calls (GetObject spikes), and potential data exfiltration using statistical baselines and time-series anomaly detection.
The English summary is being prepared. Showing the original description.