analyzing-linux-system-artifacts
Examine Linux system artifacts including auth logs, cron jobs, shell history, and system configuration to uncover evidence of compromise or unauthorized…
Skill by Joyooosama
Chalk Labs
Need help deploying analyzing-linux-system-artifacts?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/joyooosama-analyzing-linux-system-artifacts
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: security
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/analyzing-linux-system-artifacts
What's inside
- Skill name
analyzing-linux-system-artifacts- Description
- Examine Linux system artifacts including auth logs, cron jobs, shell history, and system configuration to uncover evidence of compromise or unauthorized activity.
- License
- Apache-2.0
- Instructions
- 311 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
- Instructions call the network
Files (4)
- LICENSE
- SKILL.md
- api-reference.md · references/
- agent.py · scripts/
SKILL.md (first lines)
# Analyzing Linux System Artifacts
## When to Use
- When investigating a compromised Linux server or workstation
- For identifying persistence mechanisms (cron, systemd, SSH keys)
- When tracing user activity through shell history and authentication logs
- During incident response to determine the scope of a Linux-based breach
- For detecting rootkits, backdoors, and unauthorized modifications
## Prerequisites
- Forensic image or live access to the Linux system (read-only)
- Understanding of Linux file system hierarchy (FHS)
- Knowledge of common Linux logging locations (/var/log/)
- Tools: chkrootkit, rkhunter, AIDE, auditd logs
- Familiarity with systemd, cron, and PAM configurations
- Root access for complete artifact collection
## Workflow
### Step 1: Mount and Collect System Artifacts
```bash
# Mount forensic image read-only
mount -o ro,loop,offset=$((2048*512)) /cases/case-2024-001/images/linux_evidence.dd /mnt/evidence
# Create collection directories
mkdir -p /cases/case-2024-001/linux/{logs,config,users,persistence,network}
# Collect authentication logs
cp /mnt/evidence/var/log/auth.log* /cases/case-2024-001/linux/logs/
cp /mnt/evidence/var/log/secure* /cases/case-2024-001/linux/logs/
cp /mnt/evidence/var/log/syslog* /cases/case-2024-001/linux/logs/
cp /mnt/evidence/var/log/kern.log* /cases/case-2024-001/linux/logs/
cp /mnt/evidence/var/log/audit/audit.log* /cases/case-2024-001/linux/logs/
cp /mnt/evidence/var/log/wtmp /cases/case-2024-001/linux/logs/
cp /mnt/evidence/var/log/btmp /cases/case-2024-001/linux/logs/
cp /mnt/evidence/var/log/lastlog /cases/case-2024-001/linux/logs/
cp /mnt/evidence/var/log/faillog /cases/case-2024-001/linux/logs/
# Collect user artifacts
for user_dir in /mnt/evidence/home/*/; do
username=$(basename "$user_dir")
mkdir -p /cases/case-2024-001/linux/users/$username
cp "$user_dir"/.bash_history /cases/case-2024-001/linux/users/$username/ 2>/dev/null
cp "$user_dir"/.zsh_history /cases/case-2024-001/linux/users/$username/ 2>/dev/null
cp -r "$user_dir"/.ssh/ /cases/case-2024-001/linux/users/$username/ 2>/dev/null
cp "$user_dir"/.bashrc /cases/case-2024-001/linux/users/$username/ 2>/dev/null
cp "$user_dir"/.profile /cases/case-2024-001/linux/users/$username/ 2>/dev/null
cp "$user_dir"/.viminfo /cases/case-2024-001/linux/users/$username/ 2>/dev/null
cp "$user_dir"/.wget-hsts /cases/case-2024-001/linux/users/$username/ 2>/dev/null
cp "$user_dir"/.python_history /cases/case-2024-001/linux/users/$username/ 2>/dev/null
done
# Collect root user artifacts
cp /mnt/evidence/root/.bash_history /cases/case-2024-001/linux/users/root/ 2>/dev/null
cp -r /mnt/evidence/root/.ssh/ /cases/case-2024-001/linux/users/root/ 2>/dev/null
# Collect system configuration
cp /mnt/evidence/etc/passwd /cases/case-2024-001/linux/config/
cp /mnt/evidence/etc/shadow /cases/case-2024-001/linux/config/
cp /mnt/evidence/etc/group /cases/case-2024-001/linux/config/
cp /mnt/evidence/etc/sudoers /cases/case-2024-001/linux/config/
cp -r /mnt/evidence/etc/sudoers.d/ /cases/case-2024-001/linux/config/
cp /mnt/evidence/etc/hosts /cases/case-2024-001/linux/config/
cp /mnt/evidence/etc/resolv.conf /cases/case-2024-001/linux/config/
cp -r /mnt/evidence/etc/ssh/ /cases/case-2024-001/linux/config/
```
### Step 2: Analyze User Accounts and Authentication
```bash
# Analyze user accounts for anomalies
python3 << 'PYEOF'
print("=== USER ACCOUNT ANALYSIS ===\n")
# Parse /etc/passwd
with open('/cases/case-2024-001/linux/config/passwd') as f:
for line in f:
parts = line.strip().split(':')
if len(parts) >= 7:
username, _, uid, gid, comment, home, shell = parts[0], parts[1], int(parts[2]), int(parts[3]), parts[4], parts[5], parts[6]
# Flag accounts with UID 0 (root equivalent)
if uid == 0 and username != 'root':
print(f" ALERT: UID 0 account: {username} (shell: {shell})")
# Flag accounts with login shells that shouldn't have them
if shell not in ('/bin/false', '/usr/sbin/nologin', '/bin/sync') and uid >= 1000:
print(f" User: {username} (UID:{uid}, Shell:{shell}, Home:{home})")
# Flag system accounts with login shells
if uid < 1000 and uid > 0 and shell in ('/bin/bash', '/bin/sh', '/bin/zsh'):
print(f" WARNING: System account with shell: {username} (UID:{uid}, Shell:{shell})")
# Parse /etc/shadow for account status
print("\n=== PASSWORD STATUS ===")
with open('/cases/case-2024-001/linux/config/shadow') as f:
for line in f:
parts = line.strip().split(':')
if len(parts) >= 3:
username = parts[0]
pwd_hash = parts[1]
last_change = parts[2]
if pwd_hash and pwd_hash not in ('*', '!', '!!', ''):
hash_type = 'Unknown'
if pwd_hash.startswith('$6$'): hash_type = 'SHA-512'
elif pwd_hash.startswith('$5$'): hash_type = 'SHA-256'
elif pwd_hash.startswith('$y$'): hash_type = 'yescrypt'
elif pwd_hash.startswith('$1$'): hash_type = 'MD5 (WEAK)'
print(f" {username}: {hash_type} hash, last changed: day {last_change}")
PYEOF
# Analyze login history
last -f /cases/case-2024-001/linux/logs/wtmp > /cases/case-2024-001/linux/analysis/login_history.txt
lastb -f /cases/case-2024-001/linux/logs/btmp > /cases/case-2024-001/linux/analysis/failed_logins.txt 2>/dev/null
```
### Step 3: Examine Persistence MechanismsFrom Joyooosama/dsh-skills-for-forensics, Apache-2.0.
More from Joyooosama/dsh-skills-for-forensics
- 0.570score
analyzing-kubernetes-audit-logs
Joyooosama
Parses Kubernetes API server audit logs (JSON lines) to detect exec-into-pod, secret access, RBAC modifications, privileged pod creation, and anonymous API…
SkillAFreshness: AClaude Code +9 - 0.570score
analyzing-linux-elf-malware
Joyooosama
Analyzes malicious Linux ELF (Executable and Linkable Format) binaries including botnets, cryptominers, ransomware, and rootkits targeting Linux servers…
SkillAFreshness: AClaude Code +9 - 0.567score
analyzing-golang-malware-with-ghidra
Joyooosama
Reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go…
SkillAFreshness: AClaude Code +9 - 0.565score
analyzing-device-images-as-cases
Joyooosama
First-pass analysis of a computer, server, or phone forensic exhibit (检材) — a whole disk image, server image, phone image, or phone backup — by examining it…
SkillAFreshness: AClaude Code +9 - 0.563score
analyzing-lnk-file-and-jump-list-artifacts
Joyooosama
Analyze Windows LNK shortcut files and Jump List artifacts to establish evidence of file access, program execution, and user activity using LECmd, JLECmd, and…
SkillAFreshness: AClaude Code +9
Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Oct 8, 2026 (23 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from Joyooosama
- 0.570score
analyzing-linux-elf-malware
Joyooosama
Analyzes malicious Linux ELF (Executable and Linkable Format) binaries including botnets, cryptominers, ransomware, and rootkits targeting Linux servers…
SkillAFreshness: AClaude Code +9 - 0.570score
analyzing-kubernetes-audit-logs
Joyooosama
Parses Kubernetes API server audit logs (JSON lines) to detect exec-into-pod, secret access, RBAC modifications, privileged pod creation, and anonymous API…
SkillAFreshness: AClaude Code +9 - 0.567score
analyzing-golang-malware-with-ghidra
Joyooosama
Reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go…
SkillAFreshness: AClaude Code +9 - 0.565score
analyzing-device-images-as-cases
Joyooosama
First-pass analysis of a computer, server, or phone forensic exhibit (检材) — a whole disk image, server image, phone image, or phone backup — by examining it…
SkillAFreshness: AClaude Code +9 - 0.563score
analyzing-lnk-file-and-jump-list-artifacts
Joyooosama
Analyze Windows LNK shortcut files and Jump List artifacts to establish evidence of file access, program execution, and user activity using LECmd, JLECmd, and…
SkillAFreshness: AClaude Code +9 - 0.406score
ctf-forensics
Joyooosama
CTF 鏁板瓧鍙栬瘉涓庝俊鍙峰垎鏋愭妧鏈€傚綋鎸戞垬鎻愪緵纾佺洏闀滃儚(.dd/.E01)銆佸唴瀛?dump(.raw/.vmem)銆佺綉缁滄姄鍖?.pcap/.pcapng)銆侀殣鍐欏浘鐗?闊抽銆乄indows 浜嬩欢鏃ュ織(.evtx)鏃朵娇鐢ㄣ€傝鐩?Volatility…
SkillDFreshness: DClaude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get analyzing-linux-system-artifacts running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
analyzing-linux-system-artifacts skill. Agent Mart. https://agentmart.dev/skills/joyooosama-analyzing-linux-system-artifacts (last updated 2026-10-24)