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This guide details advanced digital forensics techniques for recovering deleted file metadata and content from NTFS volumes. It focuses on analyzing the Master File Table (MFT), USN Journals, and $LogFile transaction records. Techniques include parsing MFT slack space and utilizing specialized tools like MFTECmd to reconstruct file system timelines and identify deleted evidence remnants.

A comprehensive guide utilizing Splunk Enterprise Security and SPL to conduct deep forensic analysis of security incidents. This skill covers correlating disparate sources like Windows event logs, firewall records, proxy data, and Sysmon logs to detect TTPs, reconstruct timelines, and identify anomalies, making it essential for incident response and threat hunting.

A specialized tool for digital forensics investigators that parses the Windows Amcache.hve registry hive. It extracts crucial evidence regarding program execution history, application installation metadata, and loaded driver binaries. By correlating SHA-1 hashes and reconstructing timelines, users can determine which executables ran on a system, aiding in incident response and threat detection.

This skill provides a method to parse Windows Prefetch files (.pf) using Python, allowing security analysts to reconstruct detailed application execution histories. It is crucial for incident response, enabling the detection of renamed binaries, identifying suspicious execution patterns, and building accurate chronological timelines of system activity for deep forensic investigation.

Timesketch is a collaborative, open-source platform for security teams to analyze and reconstruct complex forensic timelines. It ingests and normalizes multi-source security data (logs, artifacts) using methods like Plaso, CSV, and JSONL. Users can visualize event chronology, track attack chains, and utilize advanced built-in analyzers (e.g., Sigma, Chain of Events) for comprehensive incident investigation and documentation.

This framework provides a comprehensive solution for tracking vulnerability aging and measuring remediation performance against defined Service Level Agreements (SLAs). It helps organizations enforce severity-based timelines, calculate key performance indicators (KPIs) like Mean Time to Remediate (MTTR), and automate escalation procedures to ensure continuous compliance and improve overall security posture.

This system manages vulnerabilities that cannot be remediated within Service Level Agreement (SLA) timelines. It provides structured workflows for requesting exceptions, documenting compensating controls, obtaining formal risk acceptance approvals, and automatically managing expiration. It helps organizations maintain visibility into accepted risks to comply with major frameworks like PCI DSS, SOC 2, and NIST CSF.

This skill implements an automated system to monitor and alert on vulnerabilities that exceed their defined remediation Service Level Agreements (SLAs). It supports severity-based timelines, complex escalation workflows (e.g., PagerDuty, email), and generates comprehensive compliance reports, ensuring continuous adherence to security best practices.

This skill provides SOC teams with a structured, multi-source workflow to investigate potential insider threats. It correlates data from SIEM, DLP, EDR, and HR feeds to detect data exfiltration attempts (via cloud, USB, email), unauthorized access patterns, and policy violations. It is crucial for building comprehensive investigation timelines, especially when handling departing employees or suspected data theft.

A detailed guide for conducting professional disk forensics investigations, covering the entire lifecycle from evidence acquisition to artifact analysis. This includes establishing a strict chain of custody, performing bit-for-bit forensic imaging using write blockers, identifying file system structures (MFT, inodes), recovering deleted files, analyzing key artifacts (Prefetch, Amcache), and reconstructing precise timelines of activity for incident response cases.

This skill guides comprehensive digital forensics investigations on compromised endpoints. It covers evidence collection (memory acquisition, disk imaging) and deep artifact analysis, including volatile data, MFT records, and prefetch files. Use it for incident response, legal evidence collection, and determining the scope of a breach by reconstructing attacker timelines.

This comprehensive guide details how to perform deep forensic analysis on various Linux system logs (auth.log, syslog, systemd journal, audit.log). It teaches methods to reconstruct user activity, identify unauthorized access attempts, trace privilege escalation, and establish comprehensive event timelines following a security incident or during a security audit.