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AutoRecon is a powerful network reconnaissance tool designed to automate service enumeration, saving time during CTF challenges, penetration testing, and real-world engagements. This multi-threaded tool helps both beginners and experienced professionals streamline reconnaissance, allowing them to focus on critical vulnerabilities rather than repetitive tasks.
You Should Know:
Installation & Setup
git clone https://github.com/Tib3rius/AutoRecon.git cd AutoRecon pip3 install -r requirements.txt
Basic Usage
Scan a single target:
python3 autorecon.py <target-IP>
Scan multiple targets from a file:
python3 autorecon.py -t targets.txt
Advanced Scanning Options
Enable aggressive scan mode:
python3 autorecon.py <target-IP> --aggressive
Skip specific scans (e.g., HTTP):
python3 autorecon.py <target-IP> --skip http
Key Commands for Manual Verification
1. Nmap Aggressive Scan
nmap -A -T4 -p- <target-IP>
2. Directory Bruteforcing with Gobuster
gobuster dir -u http://<target-IP> -w /usr/share/wordlists/dirb/common.txt
3. SMB Enumeration
smbclient -L //<target-IP> -N
4. Nikto Web Vulnerability Scan
nikto -h http://<target-IP>
Automating with Custom Scripts
AutoRecon allows custom scripts in ~/tools/autorecon/local/. Example script (custom_scan.sh):
!/bin/bash echo "Running custom scan on $1" nmap -sV --script vulners $1 -oN custom_scan.txt
Parsing Results
AutoRecon organizes output in `results//`. Use:
cd results/<target-IP> cat _tcp.txt | grep "open"
What Undercode Say
AutoRecon revolutionizes network reconnaissance by automating tedious tasks, but manual verification remains crucial. Combining automated scans with tools like Metasploit, Burp Suite, and `Wireshark` ensures comprehensive security assessments.
Expected Output:
Starting AutoRecon scan on 192.168.1.1 [+] Nmap scan completed: 3 open ports [+] HTTP directories found: /admin, /backup [+] SMB shares discovered: IPC$, ADMIN$
Prediction
As AI-driven attacks rise, automated reconnaissance tools like AutoRecon will evolve with machine learning to predict attack surfaces, reducing human effort in vulnerability assessment.
(URL: AutoRecon GitHub)
IT/Security Reporter URL:
Reported By: Michael Tchuindjang – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
