This advanced, challenge-only DFIR project reviews three focused incident-response workflows: carving evidence from a raw image, extracting rapid triage clues from a preserved memory artifact, and reconstructing the behavior of a suspicious Linux executable. You will preserve hashes, isolate indicators, and produce short handoff-ready findings.
The evidence is intentionally synthetic and compact. The course tests command-line reasoning and evidence discipline without exposing you to real malware, real victim data, or a live command-and-control service.
What You Will Learn
- Verify a raw evidence image against its recorded SHA-256 checksum
- Carve an embedded PDF with Foremost and preserve the recovery report
- Extract author and title clues from recovered PDF metadata with ExifTool
- Preserve a supplied memory artifact with
ddand record its hash - Use
stringsto isolate a suspicious process and remote network indicator - Summarize memory triage findings in an operational handoff note
- Classify a Linux ELF sample and extract a hardcoded credential clue
- Use
straceandltraceto reconstruct file-system activity and a simulated C2 indicator
Who This Course Is For
This course is for experienced learners who have already practiced Linux command-line forensics, evidence hashing, basic memory triage, and static and dynamic binary inspection. It suits aspiring DFIR analysts and incident responders who want a compact, independent review project.
Prerequisites: Strong Linux shell and text-filtering skills; familiarity with forensic integrity, file carving and metadata, readable-string extraction, ELF files, system calls, library calls, and incident indicators.
Learning environment: An Ubuntu 22.04 LabEx VM with a synthetic raw image, a compact synthetic memory artifact, and a harmless locally compiled ELF simulator. Tools include SHA-256 utilities, Foremost, ExifTool, file, strings, strace, and ltrace.
Frequently Asked Questions
Is this a guided beginner course?
No. It contains three advanced challenge-based assessments. Required evidence and outputs are defined, but you must build the commands, extract the correct clues, and assemble the findings independently.
Will I handle real malware or victim data?
No. The disk image, memory content, identities, network indicators, and credentials are synthetic. The executable is a harmless C program compiled during setup, not a real malware sample.
Does the memory challenge use Volatility?
No. It preserves a small supplied byte stream, hashes it, and uses strings to recover embedded process and network clues. It is rapid command-line triage, not full memory-image analysis with Volatility plugins.
Do I execute the sample, and is that safe?
You run the simulator locally under strace and ltrace. It creates one training file under /tmp and prints fictional indicators; it does not contact the displayed C2 domain or establish a network connection.
