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Here’s a beginner-friendly Awesome List on creating, designing, and maintaining tools for bug bounty and cybersecurity development. This list focuses on a streamlined approach with templates, checklists, and best practices.

Awesome Tool Creation for Cybersecurity

A curated list of resources, templates, and checklists to help you quickly create tools that are functional, good-looking, and easy to maintain.

1. Introduction

Building custom tools for bug bounty or cybersecurity tasks is a skill that can save time, reduce errors, and improve efficiency. This list will guide you through creating tools with:

Proper documentation.
Easy-to-use interfaces.
Scalability for future updates.

2. Development Basics

Languages to Learn

Python: Great for automation and scripting.
Bash: Perfect for lightweight scripts and command-line tools.
Go: Efficient and fast for building scalable tools.

Environment Setup

Install essential software:

sudo apt update && sudo apt install -y git curl python3 python3-pip golang

Set up a project structure:

mkdir -p ~/tools/mytool/{src,docs,tests}

Version Control

Initialize Git:
```
git init
```
Use branches for new features:
```
git checkout -b feature/my-feature
```

3. Pre-Built Templates

CLI Tool Template

#!/bin/bash
# MyTool: A simple CLI example

target=$1
output_dir="./output"

# Ensure target is specified
if [ -z "$target" ]; then
  echo "Usage: ./mytool.sh <target>"
  exit 1
fi

# Create output directory
mkdir -p $output_dir

# Example task
echo "[+] Scanning $target"
nmap -sV -oN $output_dir/nmap_$target.txt $target

Python Recon Script

import subprocess
import sys

def check_tool(tool_name):
    result = subprocess.run(["which", tool_name], capture_output=True, text=True)
    if not result.stdout.strip():
        print(f"Error: {tool_name} not found. Install it first!")
        sys.exit(1)

def main(target):
    output_file = f"./output/{target}_scan.txt"
    print(f"[+] Scanning {target}")
    subprocess.run(["nmap", "-sV", "-oN", output_file, target])

if __name__ == "__main__":
    if len(sys.argv) != 2:
        print("Usage: python recon.py <target>")
        sys.exit(1)

    check_tool("nmap")
    main(sys.argv[1])

4. Tool Design Checklist

Basic Features

Accept input via command-line arguments.
Include usage instructions (--help flag).
Validate user input (e.g., ensure the domain is valid).

Structure

src/: Codebase.
docs/: Documentation files (README, usage guides).
tests/: Unit and functional tests.

Error Handling

Log errors to a file:
```
command_here 2>> error.log
```
Exit on failure with meaningful messages.

5. Automation and Recon Scripting

Recon Pipeline Example

#!/bin/bash

target=$1
output_dir="./recon/$target"

if [ -z "$target" ]; then
  echo "Usage: $0 <target>"
  exit 1
fi

mkdir -p $output_dir

# Subdomain enumeration
echo "[+] Enumerating subdomains..."
subfinder -d $target -silent > $output_dir/subdomains.txt

# Probing live domains
echo "[+] Probing live domains..."
cat $output_dir/subdomains.txt | httpx -silent > $output_dir/live_domains.txt

# Scanning for vulnerabilities
echo "[+] Running Nuclei..."
nuclei -l $output_dir/live_domains.txt -t ~/nuclei-templates -o $output_dir/nuclei_results.txt

6. User Interface Tips

Command-Line Features

Add colorful output:

echo -e "\033[0;32m[+] Task Completed\033[0m"

Include a progress bar for long tasks.

Customizing Output

Use tables for clarity:

printf "%-15s %-10s\n" "Domain" "Status"
printf "%-15s %-10s\n" "example.com" "Live"

Generate Markdown reports:

echo "# Report for $target" > report.md
echo "- Live Domains: $(wc -l live_domains.txt)" >> report.md

7. DevOps and CI/CD Integration

GitHub Actions Pipeline

name: Tool Deployment

on:
  push:
    branches:
      - main

jobs:
  build-and-deploy:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout Code
        uses: actions/checkout@v3

      - name: Install Dependencies
        run: |
          sudo apt update
          sudo apt install -y nmap subfinder nuclei

      - name: Run Tool
        run: ./mytool.sh example.com

8. Resources for Inspiration

Tool Repositories

Cheatsheets

Books

"Automate the Boring Stuff with Python" by Al Sweigart.
"Black Hat Python" by Justin Seitz.

This list is a starting point for building your tools and automating tasks. Feel free to customize and expand it for your needs. 🚀

Comprehensive guidelines for building effective, scalable, and user-friendly tools, focusing on bug bounty, cybersecurity, and automation.

1. Introduction

Building tools isn't just about automating tasks; it's about creating reliable, efficient, and reusable workflows. This list provides detailed steps to go from zero to building highly functional tools for bug bounty and security research.

2. Getting Started with Tool Development

Languages to Learn

Python: Ideal for rapid development and API integration.
Bash: Great for quick and lightweight automation scripts.
Go (Golang): Perfect for building high-performance tools.
JavaScript: Use for browser automation and interacting with web apps.

Tools to Install

Git for version control:
```
sudo apt install git
```
Package managers:
- Python: pip and pipenv
- JavaScript: npm or yarn
- Go: go install
Development Environment:
- IDE: VSCode, PyCharm, or IntelliJ.
- Linters: flake8 for Python, shellcheck for Bash, and golangci-lint for Go.

3. Tool Design Fundamentals

Key Design Principles

User-friendly interface:
- Use clear command-line options (-h, --help).
- Add error messages for incorrect inputs.
Scalable architecture:
- Use modular functions.
- Store reusable logic in libraries.
Comprehensive output:
- Include color-coded CLI output.
- Generate reports in multiple formats (JSON, CSV, Markdown).

Directory Structure for Projects

mytool/
├── README.md          # Documentation
├── LICENSE            # License file
├── requirements.txt   # Python dependencies
├── main.py            # Entry point
├── src/               # Core logic
│   ├── utils.py       # Helper functions
│   ├── modules/       # Submodules
├── tests/             # Unit tests
├── config/            # Configuration files
└── output/            # Scan results

4. Advanced Automation Scripts

Full Recon Workflow

#!/bin/bash

domain=$1
output_dir="./output/$domain"

if [ -z "$domain" ]; then
  echo "Usage: $0 <domain>"
  exit 1
fi

mkdir -p $output_dir

echo "[+] Enumerating subdomains..."
subfinder -d $domain -silent > $output_dir/subdomains.txt
amass enum -passive -d $domain >> $output_dir/subdomains.txt

echo "[+] Checking live hosts..."
cat $output_dir/subdomains.txt | httpx -silent > $output_dir/live_hosts.txt

echo "[+] Running Nuclei..."
nuclei -l $output_dir/live_hosts.txt -t ~/nuclei-templates -o $output_dir/nuclei_results.txt

Scheduled Recon with Crontab

Edit the crontab:
```
crontab -e
```

Add a daily schedule:

0 2 * * * /path/to/your/script.sh >> /path/to/logfile.log 2>&1

5. Scripting Best Practices

Bash

Set strict mode to catch errors:
```
set -euo pipefail
```

Handle arguments:

while getopts "d:o:" opt; do
  case $opt in
    d) domain=$OPTARG ;;
    o) output_dir=$OPTARG ;;
    *) echo "Invalid option"; exit 1 ;;
  esac
done

Python

Use argparse for CLI tools:

import argparse

parser = argparse.ArgumentParser(description="Tool Description")
parser.add_argument("-d", "--domain", help="Target domain", required=True)
args = parser.parse_args()

Leverage virtual environments:

python3 -m venv venv
source venv/bin/activate

6. Integrating APIs in Tools

API Keys

Store them in environment variables:
```
export API_KEY="your_api_key"
```

Access in Python:

import os
api_key = os.getenv("API_KEY")

Example API Call

Using Python's requests library:

import requests

url = "https://api.shodan.io/shodan/host/search"
params = {"key": "your_api_key", "query": "apache"}
response = requests.get(url, params=params)

print(response.json())

7. Report Generation

Markdown Report Template

# Recon Report: [Target]

## Summary
- Total Subdomains Found: XX
- Live Hosts: XX
- Vulnerabilities Found: XX

## Subdomains
- subdomain1.example.com
- subdomain2.example.com

## Vulnerability Findings
1. **XSS**: URL: `https://example.com/test?param=<script>alert()</script>`
2. **SQL Injection**: URL: `https://example.com?id=1'`

JSON Output

import json

data = {
    "target": "example.com",
    "subdomains": ["sub1.example.com", "sub2.example.com"],
    "vulnerabilities": [
        {"type": "XSS", "url": "https://example.com/test"},
        {"type": "SQLi", "url": "https://example.com?id=1"}
    ]
}

with open("report.json", "w") as f:
    json.dump(data, f, indent=4)

8. Testing and Debugging

Unit Testing

Use Python’s unittest module:

import unittest

def add(a, b):
    return a + b

class TestMath(unittest.TestCase):
    def test_add(self):
        self.assertEqual(add(1, 2), 3)

if __name__ == "__main__":
    unittest.main()

Debugging Tips

Use set -x in Bash scripts for tracing.
In Python, use pdb:
```
import pdb; pdb.set_trace()
```

9. Useful Libraries and Frameworks

Bash

: Fast HTTP requests.
: Vulnerability scanner.

Python

: Simplified HTTP requests.
: Web scraping.

Go

: Subdomain enumeration.
: Fast web fuzzer.

10. Resources and Learning Platforms

: Security best practices.
: Offensive techniques.
: Exploitation payloads.

This comprehensive guide should give you the confidence to start building, automating, and refining your own tools. 🚀

Certainly! Here's an expanded version of the Awesome List with additional tips, tools, workflows, and techniques.

Extended Ultimate Awesome List for Tool Building and Automation

Build faster, more efficient tools for bug bounty, cybersecurity, and recon tasks with this comprehensive guide.

11. Advanced Recon Techniques

Subdomain Enumeration

Passive Techniques:
- Use crt.sh for Certificate Transparency Logs.
- Tools: subfinder, amass, assetfinder, dnsx.
Active Techniques:
- DNS brute-forcing with puredns or dnsx.
- Permutation-based enumeration using gotator.
DNS Data Gathering:
- Retrieve DNS records with dig, host, or dnsx:
  dnsx -d target.com -a -resp
Recursive Subdomain Search:
- Use tools like dsieve to recursively find deeper subdomains:
  dsieve -d target.com -r

URL Discovery

Combine Wayback Machine, Common Crawl, and gau for maximum coverage:

cat targets.txt | gau | sort -u > urls.txt
waybackurls < target.txt >> urls.txt

12. Dynamic Wordlist Generation

Generating Wordlists from JS Files

Use getjs and jsluice:

cat urls.txt | getjs | xargs -n 1 jsluice -u > wordlist.txt

Generate Password Lists

Use pydictor:

pydictor -base rule.txt -o passwords.txt

Custom Subdomain Lists
- Combine existing lists with dnsvalidator:
  cat resolvers.txt | dnsvalidator -tL subdomains.txt > valid.txt

13. Advanced Scripting Tips

Parallel Processing

Use GNU Parallel for running commands on multiple cores:
```
cat subdomains.txt | parallel -j 10 "curl -Is {}"
```

Tool Dependency Checker

Ensure all required tools are installed before execution:

tools=("nuclei" "amass" "subfinder")
for tool in "${tools[@]}"; do
  if ! command -v $tool &>/dev/null; then
    echo "$tool is not installed. Please install it first!"
    exit 1
  fi
done

Error Handling

Redirect errors to a separate log file:
```
command_here >> results.log 2>> errors.log
```

14. Automation Pipelines

GitHub Actions Pipeline

Automate recon with scheduled scans:

name: Automated Recon Pipeline

on:
  schedule:
    - cron: '0 2 * * *' # Daily at 2 AM
  workflow_dispatch:

jobs:
  recon:
    runs-on: ubuntu-latest

    steps:
      - name: Checkout Code
        uses: actions/checkout@v3

      - name: Install Tools
        run: |
          sudo apt update
          sudo apt install -y subfinder httpx nuclei

      - name: Run Recon
        run: |
          ./scripts/recon.sh

Google Cloud Automation

Schedule automated scans with Google Cloud Functions and Cloud Scheduler.

Example function for subdomain enumeration:

import subprocess

def enumerate(event, context):
    domain = event.get("domain", "example.com")
    subprocess.run(["subfinder", "-d", domain, "-o", f"{domain}.txt"])

15. Post-Processing and Data Visualization

Filtering Unique URLs

Deduplicate and sort URLs:
```
cat urls.txt | sort -u > clean_urls.txt
```

Create Visual Maps

Subdomain Graphs
- Use amass and Maltego for visualizing subdomain connections.
- Export with:
  amass viz -d target.com -o output.json
Network Graphs
- Use tools like neo4j or Graphviz.

HTML Reporting

Use Python libraries like BeautifulSoup or j2html to generate reports:

from jinja2 import Template

template = Template("<h1>Report for {{ domain }}</h1>")
print(template.render(domain="example.com"))

16. Tool Examples

API Token Validator

import requests

def check_api_key(api_key):
    response = requests.get("https://api.example.com", headers={"Authorization": f"Bearer {api_key}"})
    if response.status_code == 200:
        print("API Key is valid")
    else:
        print("Invalid API Key")

Port Scanning Automation

#!/bin/bash

target=$1
output_dir="./output/$target"

mkdir -p $output_dir

echo "[+] Scanning ports on $target..."
nmap -sC -sV -oN $output_dir/ports.txt $target

17. Notifications

Slack Integration

Send results to Slack:

webhook_url="https://hooks.slack.com/services/your/webhook/url"
message="Recon complete for $target"

curl -X POST -H 'Content-type: application/json' --data '{"text":"'"$message"'"}' $webhook_url

Telegram Bot

Notify via Telegram:

import requests

bot_token = "your_bot_token"
chat_id = "your_chat_id"
message = "Recon complete"

requests.post(f"https://api.telegram.org/bot{bot_token}/sendMessage", data={"chat_id": chat_id, "text": message})

18. Advanced Tools and Frameworks

Recon Tools

katana: Fast crawler for endpoints.
waymore: Wayback URLs with custom filtering.
Interlace: Automate tool chaining for multithreaded scans.

Fuzzing Tools

ffuf: Fast web fuzzer for directories and parameters.
GoFuzz: Fuzzing Go applications.

19. Continuous Improvement

Set Benchmarks

Track metrics for improvement:
- Time to find vulnerabilities.
- Tool efficiency (false positives vs. true positives).
- Automation speed.

Integrate Machine Learning

Use AI-based tools like ChatGPT or Weka to analyze recon data patterns for hidden vulnerabilities.

20. Resources for Inspiration

Books

"Black Hat Python" by Justin Seitz.
"Hacking APIs" by Corey Ball.

Communities

Learning Platforms

This extended guide is designed to give you everything you need to get started with tool development, automation, and advanced recon workflows. Here’s an extended Awesome List to further cover the essentials and advanced aspects of scripting, automation, and tool creation in bug hunting and cybersecurity. This builds on the previous list with new categories and actionable insights:

31. Web Scraping and Automation

Python Web Scraping

Scraping with requests and BeautifulSoup:

import requests
from bs4 import BeautifulSoup

url = "https://example.com"
response = requests.get(url)
soup = BeautifulSoup(response.content, "html.parser")

for link in soup.find_all("a"):
    print(link.get("href"))

Scraping APIs:

import requests

url = "https://api.example.com/data"
headers = {"Authorization": "Bearer your_api_token"}
response = requests.get(url, headers=headers)
print(response.json())

Browser Automation

Using Selenium for Dynamic Content:

from selenium import webdriver

driver = webdriver.Chrome()
driver.get("https://example.com")
print(driver.page_source)
driver.quit()

Headless Browsing with Puppeteer:

const puppeteer = require('puppeteer');
(async () => {
    const browser = await puppeteer.launch({ headless: true });
    const page = await browser.newPage();
    await page.goto('https://example.com');
    console.log(await page.content());
    await browser.close();
})();

32. Advanced Network Scanning

Bash Utilities

Masscan for Fast Port Scanning:

masscan -p1-65535 192.168.1.0/24 --rate 10000 -oG masscan_results.txt

Custom Banner Grabbing:
```
nmap -sV --script=banner 192.168.1.1
```

Python Scanners

Custom Port Scanner:

import socket

def scan(ip, port):
    try:
        sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
        sock.settimeout(1)
        sock.connect((ip, port))
        print(f"Port {port} is open on {ip}")
        sock.close()
    except:
        pass

scan("192.168.1.1", 80)

33. OSINT Automation

OSINT Tools

Email Enumeration with holehe:
```
holehe -l emails.txt
```
Search Leaked Credentials:
```
theharvester -d target.com -b all
```

Custom Scripts

Automate Google Dorking:

dorks=("site:example.com inurl:admin" "site:example.com ext:sql")
for dork in "${dorks[@]}"; do
    query=$(echo $dork | sed 's/ /+/g')
    curl "https://www.google.com/search?q=$query"
done

LinkedIn Scraping for Employee Info:

import requests

url = "https://www.linkedin.com/search/results/people/"
headers = {"User-Agent": "Mozilla/5.0"}
response = requests.get(url, headers=headers)
print(response.text)

34. Advanced Vulnerability Exploitation

Exploitation Scripts

SQL Injection Exploitation with Python:

import requests

payload = "' OR '1'='1"
url = "https://example.com/login"
data = {"username": payload, "password": payload}
response = requests.post(url, data=data)
print(response.text)

XSS Automation:

echo "<script>alert(1)</script>" > payloads.txt
cat urls.txt | while read url; do
    curl "$url?q=$(cat payloads.txt)"
done

35. API Security Testing

Custom Scripts

API Endpoint Testing:

import requests

url = "https://api.example.com/v1/data"
headers = {"Authorization": "Bearer token"}
response = requests.get(url, headers=headers)

if response.status_code == 200:
    print("API is functional")
else:
    print("API error:", response.status_code)

Automate Rate-Limiting Checks:

for i in {1..100}; do
    curl -X GET "https://api.example.com" &
done

36. Data Extraction

Extract Key Info

Find All IPs in a Log File:

grep -Eo '([0-9]{1,3}\.){3}[0-9]{1,3}' logs.txt | sort -u > ips.txt

Extract Emails:

grep -Eo "\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b" logs.txt > emails.txt

37. Continuous Monitoring Pipelines

GitHub Actions for Automation

Recon Automation:

name: Recon Automation
on:
  schedule:
    - cron: '0 0 * * *'

jobs:
  recon:
    runs-on: ubuntu-latest
    steps:
      - name: Subdomain Enumeration
        run: subfinder -d example.com > subs.txt

Slack Alerts for Findings:

curl -X POST -H 'Content-type: application/json' --data '{"text":"Scan completed!"}' $SLACK_WEBHOOK

38. File Handling in Automation

Parse and Process Large Files

Bash: Split Large Files:
```
split -l 1000 large_file.txt small_
```

Python: Process JSON:

import json

with open("data.json") as f:
    data = json.load(f)
    for item in data:
        print(item)

39. Advanced Reporting

Visualizations

Graph Vulnerabilities:

Use Python’s matplotlib:

import matplotlib.pyplot as plt

data = [10, 15, 20]
labels = ["XSS", "SQLi", "SSRF"]

plt.pie(data, labels=labels, autopct='%1.1f%%')
plt.title("Vulnerability Distribution")
plt.show()

Heatmaps for Severity:

import seaborn as sns
import matplotlib.pyplot as plt

data = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
sns.heatmap(data, annot=True)
plt.show()

40. Quick Automation Ideas

Instant Tools

Certificate Transparency:

curl -s "https://crt.sh/?q=example.com" | grep "example.com"

Screenshot Script:

cat live.txt | while read url; do
    eyewitness -u $url
done

Check for WAF:
```
wafw00f https://example.com
```

This expanded list includes even more actionable insights for scripting, automation, and creating tools with over 40 unique sections. Each item is tailored to help you create effective, automated, and scalable bug bounty workflows.

21. Advanced Recon Pipelines

GitOps for Recon

Use GitLab CI/CD for recon pipelines:

stages:
  - recon
  - scan

recon:
  stage: recon
  script:
    - subfinder -d target.com > subs.txt
    - httpx -l subs.txt -o live.txt

scan:
  stage: scan
  script:
    - nuclei -l live.txt -t ~/nuclei-templates/

Kubernetes Integration:
- Deploy tools like nuclei and ffuf on a Kubernetes cluster for scalable recon.
Axiom for Distributed Scanning:
- Create distributed pipelines using Axiom:
  axiom-scan live.txt -m nuclei -t ~/nuclei-templates/

22. Custom Scripting for Bug Bounty

Enhanced Bash Utilities

Retry Logic for Unstable Commands:

retry() {
    local n=1
    local max=5
    local delay=5
    while true; do
        "$@" && break || {
            if [[ $n -lt $max ]]; then
                ((n++))
                echo "Command failed. Attempt $n/$max:"
                sleep $delay;
            else
                echo "Command failed after $n attempts."
                return 1
            fi
        }
    done
}

Use as:
```
retry curl -I https://example.com
```

Dynamic Wordlist Updates:

cat live_urls.txt | grep ".js" | cut -d '/' -f3 | sort -u > js_wordlist.txt

Automated Screenshot Script:

cat live.txt | aquatone -out screenshots

Python Recon Scripts

HTTP Header Analyzer:

import requests

def analyze_headers(url):
    response = requests.get(url)
    headers = response.headers
    for header, value in headers.items():
        print(f"{header}: {value}")

analyze_headers("https://example.com")

Directory Brute-Forcer:

import requests

url = "https://example.com"
wordlist = ["admin", "login", "config"]
for word in wordlist:
    response = requests.get(f"{url}/{word}")
    if response.status_code == 200:
        print(f"Found: {url}/{word}")

23. Advanced Data Parsing

Extract Domains from JS Files

Using Bash:

grep -oP 'https?://[a-zA-Z0-9.-]+' *.js | sort -u > domains.txt

With Python:

import re

with open("file.js", "r") as f:
    content = f.read()
    urls = re.findall(r"https?://[a-zA-Z0-9./-]+", content)
    for url in urls:
        print(url)

Parse JSON Files for Sensitive Data

Use jq:

jq '.keys[] | select(.type=="AWS")' sensitive.json

24. Enhanced Vulnerability Detection

Custom Scripts

SSRF Testing:

import requests

payload = {"url": "http://localhost:8080/admin"}
response = requests.post("https://target.com/api", json=payload)
print(response.text)

XSS Payload Testing:

cat urls.txt | while read url; do
    curl "$url?q=<script>alert(1)</script>"
done

SQL Injection Automation:

sqlmap -u "https://example.com?id=1" --batch --dbs

25. Workflow Optimization Tools

Version Control

Use Git hooks to enforce standards:

# pre-commit hook
echo "Running security checks..."

Linters and Formatters

Python: black, flake8
Bash: shellcheck

Automated Deployment

Use Docker:

FROM python:3.9
WORKDIR /app
COPY . .
RUN pip install -r requirements.txt
CMD ["python", "app.py"]

26. Best Practices for Tool Development

Modularization

Use reusable functions:

def subdomain_enum(domain):
    # Code here
    return results

Error Handling

Provide detailed error messages:

try:
    response = requests.get("https://example.com")
    response.raise_for_status()
except requests.RequestException as e:
    print(f"Error: {e}")

Performance Optimization

Multi-threading:

from concurrent.futures import ThreadPoolExecutor

def scan(url):
    print(f"Scanning {url}")

urls = ["https://example.com", "https://test.com"]
with ThreadPoolExecutor(max_workers=5) as executor:
    executor.map(scan, urls)

27. Continuous Monitoring

Scheduled Tasks

Use cron for periodic scans:

0 2 * * * /path/to/recon.sh >> /path/to/logs.txt

Real-Time Alerts

Integrate Slack or Telegram for notifications:

curl -X POST -H 'Content-type: application/json' --data '{"text":"Scan completed"}' $SLACK_WEBHOOK

28. GitHub Awesome List Templates

Building Your Own List

Use :

Structure:

# Awesome List

## Introduction
## Tools
## Resources
## Tutorials
## Contributing

Automated Updates

Use GitHub Actions to periodically update content:
```
on:
  schedule:
    - cron: '0 0 * * 1'
```

29. Advanced Reporting

HTML Reports

Create visually appealing reports using ReportLab or Flask:

from flask import Flask, render_template

app = Flask(__name__)

@app.route("/")
def index():
    return render_template("report.html")

Markdown Reports

Script Example:

echo "# Recon Report" > report.md
cat results.txt >> report.md

Export to PDF:
- Use pandoc:
  pandoc report.md -o report.pdf

GitHub has blocked your push because it detected a secret (like a GitHub Personal Access Token) in your repository. To resolve this and safeguard your repository:

Steps to Fix and Prevent Issues

1. Remove Secrets from History

Identify the Secret: GitHub tells you where the secret is located, e.g., MyMac/Automated-Scanner/tools/.tokens:1. Open the file and remove the secret.

Amend the Commit: After removing the secret, re-commit the changes:

git rm --cached MyMac/Automated-Scanner/tools/.tokens
git commit --amend --no-edit
git push origin main --force

2. Use git filter-repo to Remove Secrets from Entire History

If the secret exists in older commits:

Install git-filter-repo:
```
pip install git-filter-repo
```
Remove the Secret: Replace <path> with the file path containing the secret:
```
git filter-repo --path <path> --invert-paths
```
Force Push Clean History:
```
git push origin main --force
```

Set Up Best Practices to Prevent Future Issues

3. Enable GitHub Push Protection

GitHub will block pushes containing sensitive information by default if push protection is enabled. Ensure it's active in your repository settings:

Go to Settings > Code Security and Analysis > Push Protection.
Enable Push Protection.

4. Use .gitignore to Prevent Secrets from Being Committed

Add paths of sensitive files to a .gitignore file:

# Ignore token files
*.tokens
*.env

Then stage and commit the .gitignore file:

git add .gitignore
git commit -m "Add .gitignore to prevent committing sensitive files"
git push origin main

5. Scan for Secrets Locally

Use tools like to scan your commits for secrets before pushing:

ggshield secret scan pre-commit

6. Replace Existing Tokens

If a token was exposed, revoke it and create a new one:

Revoke the token via GitHub's Settings > Developer Settings > Personal Access Tokens.
Create a new token and securely store it in environment variables or secret management tools like AWS Secrets Manager or HashiCorp Vault.

7. Use .env Files for Secrets

Store secrets in .env files and load them dynamically into your scripts using tools like dotenv. Example .env file:

GITHUB_TOKEN=your_token_here

Add .env to .gitignore:

.env

Push Again After Fixing Issues

After cleaning the history and ensuring no secrets remain, retry your push:
```
git push origin main
```

Comprehensive GitHub Solutions and Best Practices

Here’s a detailed guide to handling common Git issues, maintaining repository hygiene, securing your code, and improving workflows for professional-grade repositories.

1. General Git and GitHub Commands

Clone a Repository

git clone https://github.com/username/repo.git

Create and Push a New Branch

git checkout -b feature-branch
git push origin feature-branch

Merge Branches

git checkout main
git merge feature-branch
git push origin main

Stash Uncommitted Changes

git stash
# Apply the stash later
git stash pop

2. Fixing Common Git Issues

Remove Untracked Files

git clean -f -d

Undo the Last Commit

git reset --soft HEAD~1  # Keeps changes staged
git reset --hard HEAD~1  # Discards changes completely

Resolve Merge Conflicts

Open conflicted files.
Edit the conflict markers (<<<<<<, ======, >>>>>>).
Stage the resolved files:
```
git add <file>
```
Continue the merge:
```
git commit
```

Fix Detached HEAD

git checkout <branch>

3. Managing Secrets

Prevent Secrets in Commits

Add sensitive files to .gitignore:

.env
*.key
*.pem
*.tokens

Scan Commits for Secrets

Use tools like :

trufflehog --regex --entropy=True https://github.com/username/repo.git

Replace Leaked Secrets

If a secret is exposed:

Revoke the token immediately.

Use git filter-repo to remove it:

git filter-repo --path-sensitive-file --invert-paths

Push the cleaned history:
```
git push origin main --force
```

4. Improving Repository Security

Enable 2FA for Your GitHub Account

Go to Settings > Security > Two-factor authentication.
Follow the prompts to set up 2FA.

Set Up Branch Protection

Go to Settings > Branches > Add branch protection rule.
Enable:
- Require pull request reviews.
- Require status checks.
- Restrict who can push.

Enable Secret Scanning

Go to Settings > Security & Analysis.
Enable Secret Scanning and Push Protection.

5. Automating Workflows

Using GitHub Actions

Create a .github/workflows/main.yml file:

name: CI/CD Pipeline

on:
  push:
    branches:
      - main

jobs:
  build:
    runs-on: ubuntu-latest

    steps:
      - name: Checkout Code
        uses: actions/checkout@v3

      - name: Run Tests
        run: |
          npm install
          npm test

Schedule Automated Tasks

Run a workflow daily:

on:
  schedule:
    - cron: "0 0 * * *"

6. Commit Hygiene

Write Descriptive Commit Messages

Follow the conventional commit format:

<type>(<scope>): <short summary>

[optional body]

[optional footer(s)]

Example:

feat(auth): add login endpoint
fix(auth): resolve token expiration issue

Sign Commits

Enable GPG signing for commits:

git config --global user.signingkey <GPG_KEY_ID>
git config --global commit.gpgsign true

7. Version Control Best Practices

Tagging Releases

git tag -a v1.0.0 -m "Initial release"
git push origin v1.0.0

Changelog Automation

Use :

npx conventional-changelog-cli -p angular

8. Collaboration

Create a Pull Request

Push changes:
```
git push origin feature-branch
```
Go to the repository on GitHub and create a PR.

Review PRs

Use GitHub’s review tools to add comments.
Mark a PR as approved or request changes.

9. Repository Hygiene

Archive Old Branches

Delete merged branches:

git branch -d feature-branch
git push origin --delete feature-branch

Clean Up Commit History

Use rebase for a cleaner history:

git rebase -i HEAD~<number-of-commits>

10. Advanced Git Commands

Revert a Specific Commit

git revert <commit-hash>

Cherry-Pick a Commit

git cherry-pick <commit-hash>

View Commit History

git log --oneline --graph --decorate

Show Changes Between Branches

git diff branch1..branch2

11. Backup and Restore

Backup a Repository

git bundle create repo.bundle --all

Restore from Backup

git clone repo.bundle

12. Troubleshooting

Fix Corrupted Repositories

git fsck --full

Rebuild the Index

rm -f .git/index
git reset

Recover Lost Commits

git reflog
git reset --hard <commit-hash>

13. Resources for Learning

This list ensures you have everything covered, from basic Git operations to advanced GitHub features, to help you create efficient, secure, and collaborative workflows. If you still encounter issues, GitHub’s documentation provides more details on resolving blocked pushes.

30. Learning Resources

Tutorials

Videos

YouTube Channels:

Books

"The Web Application Hacker's Handbook" by Dafydd Stuttard.
"Practical Binary Analysis" by Dennis Andriesse.

This expanded Awesome List now provides 200+ actionable tips, tools, and workflows for building, automating, and optimizing cybersecurity scripts and tools!

Awesome Tool Creation for Cybersecurity

Table of Contents

1. Introduction

2. Development Basics

Languages to Learn

Environment Setup

Version Control

3. Pre-Built Templates

CLI Tool Template

Python Recon Script

4. Tool Design Checklist

Basic Features

Structure

Error Handling

5. Automation and Recon Scripting

Recon Pipeline Example

6. User Interface Tips

Command-Line Features

Customizing Output

7. DevOps and CI/CD Integration

GitHub Actions Pipeline

8. Resources for Inspiration

Tool Repositories

Cheatsheets

Books

Table of Contents

1. Introduction

2. Getting Started with Tool Development

Languages to Learn

Tools to Install

3. Tool Design Fundamentals

Key Design Principles

Directory Structure for Projects

4. Advanced Automation Scripts

Full Recon Workflow

Scheduled Recon with Crontab

5. Scripting Best Practices

Bash

Python

6. Integrating APIs in Tools

API Keys

Example API Call

7. Report Generation

Markdown Report Template

JSON Output

8. Testing and Debugging

Unit Testing

Debugging Tips

9. Useful Libraries and Frameworks

Bash

Python

Go

10. Resources and Learning Platforms

Extended Ultimate Awesome List for Tool Building and Automation

11. Advanced Recon Techniques

Subdomain Enumeration

URL Discovery

12. Dynamic Wordlist Generation

13. Advanced Scripting Tips

Parallel Processing

Tool Dependency Checker

Error Handling

14. Automation Pipelines

GitHub Actions Pipeline

Google Cloud Automation

15. Post-Processing and Data Visualization

Filtering Unique URLs

Create Visual Maps

HTML Reporting

16. Tool Examples

API Token Validator

Port Scanning Automation

17. Notifications

Slack Integration

Telegram Bot

18. Advanced Tools and Frameworks

Recon Tools

Fuzzing Tools

19. Continuous Improvement

Set Benchmarks