Linux Evidence Acquisition Framework
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Updated
Sep 30, 2024 - Python
Linux Evidence Acquisition Framework
A memory forensics automation tool that wraps Volatility 3, runs plugins, detects suspicious activity (malicious processes, code injection, network anomalies), and generates professional reports from a single command. Supports Windows, Linux, and macOS.
Evidence-preserving digital forensics primitives and composable workflows for analysts, automation systems, and autonomous agents.
Digital forensics and incident response (DFIR) reference: evidence handling, memory/disk forensics workflows, and chain-of-custody procedures for enterprise investigations
AI-native MCP server for natural-language cyber incident investigation and triage across Windows, Linux, and macOS artifacts, plus Volatility3 memory forensics and Hashcat. Mount evidence, parse artifacts, trace lateral movement, correlate IOCs, and generate reports through conversation.
Local, offline, LLM-assisted forensic triage for Linux server images: established DFIR tools do detection; Gumshoe adds provenance, chain of custody, a cited RAG layer, evidence archive/export and reports.
SSH Authentication Incident Investigation & Forensics Lab with Kali Linux attack replay, Linux auth.log triage, Wireshark PCAP packet extraction, and brute-force forensic report.
Parse syslog/auth.log for auth failures and sudo abuse — Linux log forensics and server intrusion investigation offline.
Ongoing DFIR-focused Hack The Box write-ups highlighting my investigative methodology and forensic analysis.
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