performing-linux-log-forensics-investigation
Perform forensic investigation of Linux system logs including syslog, auth.log, systemd journal, kern.log, and application logs to reconstruct user activity, detect unauthorized access, and establish event timelines on compromised Linux systems.
Best use case
performing-linux-log-forensics-investigation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Perform forensic investigation of Linux system logs including syslog, auth.log, systemd journal, kern.log, and application logs to reconstruct user activity, detect unauthorized access, and establish event timelines on compromised Linux systems.
Teams using performing-linux-log-forensics-investigation should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/performing-linux-log-forensics-investigation/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How performing-linux-log-forensics-investigation Compares
| Feature / Agent | performing-linux-log-forensics-investigation | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Perform forensic investigation of Linux system logs including syslog, auth.log, systemd journal, kern.log, and application logs to reconstruct user activity, detect unauthorized access, and establish event timelines on compromised Linux systems.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Performing Linux Log Forensics Investigation
## Overview
Linux systems maintain extensive logs that serve as primary evidence sources in forensic investigations. Unlike Windows Event Logs, Linux logs are typically plain-text files stored in /var/log/ and binary journal files managed by systemd-journald. Key forensic logs include auth.log (authentication events, sudo usage, SSH sessions), syslog (system-wide messages), kern.log (kernel events), and application-specific logs. The Linux Audit framework (auditd) provides detailed security event logging comparable to Windows Security Event Logs. Forensic analysis of these logs enables investigators to reconstruct user sessions, identify unauthorized access, detect privilege escalation, trace lateral movement, and establish comprehensive event timelines.
## When to Use
- When conducting security assessments that involve performing linux log forensics investigation
- When following incident response procedures for related security events
- When performing scheduled security testing or auditing activities
- When validating security controls through hands-on testing
## Prerequisites
- Familiarity with digital forensics concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities
## Key Log Files and Locations
| Log File | Path | Contents |
|----------|------|----------|
| auth.log / secure | /var/log/auth.log (Debian) or /var/log/secure (RHEL) | Authentication, sudo, SSH, PAM |
| syslog / messages | /var/log/syslog (Debian) or /var/log/messages (RHEL) | General system messages |
| kern.log | /var/log/kern.log | Kernel messages, USB events, driver loads |
| lastlog | /var/log/lastlog | Last login per user (binary) |
| wtmp | /var/log/wtmp | Login/logout records (binary, read with `last`) |
| btmp | /var/log/btmp | Failed login attempts (binary, read with `lastb`) |
| faillog | /var/log/faillog | Failed login counter (binary) |
| cron.log | /var/log/cron or /var/log/syslog | Scheduled task execution |
| audit.log | /var/log/audit/audit.log | Linux Audit Framework events |
| journal | /var/log/journal/ or /run/log/journal/ | systemd binary journal |
| dpkg.log | /var/log/dpkg.log | Package installation/removal (Debian) |
| yum.log | /var/log/yum.log | Package installation/removal (RHEL) |
## Analysis Techniques
### Authentication Log Analysis
```bash
# Find all successful SSH logins
grep "Accepted" /var/log/auth.log
# Find failed SSH login attempts
grep "Failed password" /var/log/auth.log
# Extract unique source IPs from failed logins
grep "Failed password" /var/log/auth.log | grep -oP '\d+\.\d+\.\d+\.\d+' | sort -u
# Find sudo command execution
grep "sudo:" /var/log/auth.log | grep "COMMAND"
# Detect brute force patterns (>10 failures from same IP)
grep "Failed password" /var/log/auth.log | awk '{print $(NF-3)}' | sort | uniq -c | sort -rn | head -20
# Find account creation events
grep "useradd\|adduser" /var/log/auth.log
# Detect SSH key authentication
grep "Accepted publickey" /var/log/auth.log
```
### Systemd Journal Analysis
```bash
# Export journal in JSON format for forensic processing
journalctl --output=json --no-pager > journal_export.json
# Filter by time range
journalctl --since "2025-02-01" --until "2025-02-15" --output=json > timerange.json
# Filter by unit/service
journalctl -u sshd --output=json > sshd_journal.json
# Show kernel messages (USB events, module loads)
journalctl -k --output=json > kernel_journal.json
# Filter by priority (0=emerg to 7=debug)
journalctl -p err --output=json > errors.json
# Boot-specific logs
journalctl -b 0 --output=json > current_boot.json
journalctl --list-boots # List all recorded boot sessions
```
### Linux Audit Framework Analysis
```bash
# Search audit log for specific event types
ausearch -m USER_AUTH --start today
# Search for file access events
ausearch -f /etc/shadow
# Search for process execution
ausearch -m EXECVE --start "02/01/2025" --end "02/28/2025"
# Generate report of login events
aureport --login --start "02/01/2025"
# Generate summary of failed authentications
aureport --auth --failed
# Search for specific user activity
ausearch -ua 1001 # By UID
ausearch -ua username # By username
```
### Cron Job Investigation
```bash
# Check system-wide crontab
cat /etc/crontab
# Check user crontabs
ls -la /var/spool/cron/crontabs/
# Review cron execution logs
grep "CRON" /var/log/syslog
# Check for at/batch jobs
ls -la /var/spool/at/
atq
```
## Python Forensic Log Parser
```python
import re
import json
import sys
import os
from datetime import datetime
from collections import defaultdict
class LinuxLogForensicAnalyzer:
"""Analyze Linux system logs for forensic investigation."""
def __init__(self, log_dir: str, output_dir: str):
self.log_dir = log_dir
self.output_dir = output_dir
os.makedirs(output_dir, exist_ok=True)
def parse_auth_log(self, auth_log_path: str) -> dict:
"""Parse auth.log for authentication events."""
events = {
"successful_logins": [],
"failed_logins": [],
"sudo_commands": [],
"account_changes": [],
"ssh_sessions": []
}
ssh_accepted = re.compile(
r'(\w+\s+\d+\s+[\d:]+)\s+(\S+)\s+sshd\[\d+\]:\s+Accepted\s+(\S+)\s+for\s+(\S+)\s+from\s+([\d.]+)'
)
ssh_failed = re.compile(
r'(\w+\s+\d+\s+[\d:]+)\s+(\S+)\s+sshd\[\d+\]:\s+Failed\s+password\s+for\s+(\S*)\s+from\s+([\d.]+)'
)
sudo_cmd = re.compile(
r'(\w+\s+\d+\s+[\d:]+)\s+(\S+)\s+sudo:\s+(\S+)\s+:.*COMMAND=(.*)'
)
useradd = re.compile(
r'(\w+\s+\d+\s+[\d:]+)\s+(\S+)\s+useradd\[\d+\]:\s+new user: name=(\S+)'
)
with open(auth_log_path, "r", errors="replace") as f:
for line in f:
m = ssh_accepted.search(line)
if m:
events["successful_logins"].append({
"timestamp": m.group(1), "host": m.group(2),
"method": m.group(3), "user": m.group(4), "source_ip": m.group(5)
})
continue
m = ssh_failed.search(line)
if m:
events["failed_logins"].append({
"timestamp": m.group(1), "host": m.group(2),
"user": m.group(3), "source_ip": m.group(4)
})
continue
m = sudo_cmd.search(line)
if m:
events["sudo_commands"].append({
"timestamp": m.group(1), "host": m.group(2),
"user": m.group(3), "command": m.group(4).strip()
})
continue
m = useradd.search(line)
if m:
events["account_changes"].append({
"timestamp": m.group(1), "host": m.group(2),
"new_user": m.group(3)
})
return events
def detect_brute_force(self, auth_events: dict, threshold: int = 10) -> list:
"""Detect brute force attempts from auth log data."""
ip_failures = defaultdict(int)
for event in auth_events.get("failed_logins", []):
ip_failures[event["source_ip"]] += 1
brute_force = []
for ip, count in ip_failures.items():
if count >= threshold:
brute_force.append({"source_ip": ip, "failed_attempts": count})
return sorted(brute_force, key=lambda x: x["failed_attempts"], reverse=True)
def generate_report(self, auth_log_path: str) -> str:
"""Generate comprehensive forensic analysis report."""
auth_events = self.parse_auth_log(auth_log_path)
brute_force = self.detect_brute_force(auth_events)
report = {
"analysis_timestamp": datetime.now().isoformat(),
"log_source": auth_log_path,
"summary": {
"successful_logins": len(auth_events["successful_logins"]),
"failed_logins": len(auth_events["failed_logins"]),
"sudo_commands": len(auth_events["sudo_commands"]),
"account_changes": len(auth_events["account_changes"]),
"brute_force_sources": len(brute_force)
},
"brute_force_detected": brute_force,
"auth_events": auth_events
}
report_path = os.path.join(self.output_dir, "linux_log_forensics.json")
with open(report_path, "w") as f:
json.dump(report, f, indent=2)
print(f"[*] Successful logins: {report['summary']['successful_logins']}")
print(f"[*] Failed logins: {report['summary']['failed_logins']}")
print(f"[*] Sudo commands: {report['summary']['sudo_commands']}")
print(f"[*] Brute force sources: {report['summary']['brute_force_sources']}")
return report_path
def main():
if len(sys.argv) < 3:
print("Usage: python process.py <auth_log_path> <output_dir>")
sys.exit(1)
analyzer = LinuxLogForensicAnalyzer(os.path.dirname(sys.argv[1]), sys.argv[2])
analyzer.generate_report(sys.argv[1])
if __name__ == "__main__":
main()
```
## References
- Linux Forensics In Depth: https://amr-git-dot.github.io/forensic%20investigation/Linux_Forensics/
- SANS Practical Linux Forensics: https://nostarch.com/linuxforensics
- HackTricks Linux Forensics: https://book.hacktricks.xyz/generic-methodologies-and-resources/basic-forensic-methodology/linux-forensics
- Log Sources for Digital Forensics: https://letsdefend.io/blog/log-sources-for-digital-forensics-windows-and-linuxRelated Skills
performing-yara-rule-development-for-detection
Develop precise YARA rules for malware detection by identifying unique byte patterns, strings, and behavioral indicators in executable files while minimizing false positives.
performing-wireless-security-assessment-with-kismet
Conduct wireless network security assessments using Kismet to detect rogue access points, hidden SSIDs, weak encryption, and unauthorized clients through passive RF monitoring.
performing-wireless-network-penetration-test
Execute a wireless network penetration test to assess WiFi security by capturing handshakes, cracking WPA2/WPA3 keys, detecting rogue access points, and testing wireless segmentation using Aircrack-ng and related tools.
performing-windows-artifact-analysis-with-eric-zimmerman-tools
Perform comprehensive Windows forensic artifact analysis using Eric Zimmerman's open-source EZ Tools suite including KAPE, MFTECmd, PECmd, LECmd, JLECmd, and Timeline Explorer for parsing registry hives, prefetch files, event logs, and file system metadata.
performing-wifi-password-cracking-with-aircrack
Captures WPA/WPA2 handshakes and performs offline password cracking using aircrack-ng, hashcat, and dictionary attacks during authorized wireless security assessments to evaluate passphrase strength and wireless network security posture.
performing-web-cache-poisoning-attack
Exploiting web cache mechanisms to serve malicious content to other users by poisoning cached responses through unkeyed headers and parameters during authorized security tests.
performing-web-cache-deception-attack
Execute web cache deception attacks by exploiting path normalization discrepancies between CDN caching layers and origin servers to cache and retrieve sensitive authenticated content.
performing-web-application-vulnerability-triage
Triage web application vulnerability findings from DAST/SAST scanners using OWASP risk rating methodology to separate true positives from false positives and prioritize remediation.
performing-web-application-scanning-with-nikto
Nikto is an open-source web server and web application scanner that tests against over 7,000 potentially dangerous files/programs, checks for outdated versions of over 1,250 servers, and identifies ve
performing-web-application-penetration-test
Performs systematic security testing of web applications following the OWASP Web Security Testing Guide (WSTG) methodology to identify vulnerabilities in authentication, authorization, input validation, session management, and business logic. The tester uses Burp Suite as the primary interception proxy alongside manual testing techniques to find flaws that automated scanners miss. Activates for requests involving web app pentest, OWASP testing, application security assessment, or web vulnerability testing.
performing-web-application-firewall-bypass
Bypass Web Application Firewall protections using encoding techniques, HTTP method manipulation, parameter pollution, and payload obfuscation to deliver SQL injection, XSS, and other attack payloads past WAF detection rules.
performing-vulnerability-scanning-with-nessus
Performs authenticated and unauthenticated vulnerability scanning using Tenable Nessus to identify known vulnerabilities, misconfigurations, default credentials, and missing patches across network infrastructure, servers, and applications. The scanner correlates findings with CVE databases and CVSS scores to produce prioritized remediation guidance. Activates for requests involving vulnerability scanning, Nessus assessment, patch compliance checking, or automated vulnerability detection.