DEV Community: Mate Technologies

Stop Using Slow Online SVG Converters — I Built a Faster Offline Tool Instead

Mate Technologies — Tue, 21 Apr 2026 14:09:03 +0000

If you’ve ever worked with SVG files in real projects, you probably know this pain:

Uploading files to random websites
Waiting for slow conversions
Dealing with file size limits
Losing time switching between tools
Worrying about privacy and file security

I got tired of that workflow — so I built something to fix it.

Meet SVG Converter PRO v2.2.0.

🧠 Why I Built This

As a developer working with UI assets and icon systems, I needed a tool that:

Works offline
Handles batch processing
Supports multiple output formats
Runs fast without web dependencies
Doesn’t force uploads or accounts

Most tools out there were either too basic or cloud-based.

So I built a desktop application in Python that does everything locally.

⚡ What SVG Converter PRO Does

This is not just a simple converter — it’s a full SVG processing toolkit.

🔄 Conversion Features

Convert SVG files into:

PNG
JPG
WebP
ICO (multi-size icon generation)
PDF
🌐 Web-Friendly Outputs

Generate developer-ready formats:

Base64 encoded SVG
Data URI strings
🛠 Advanced SVG Tools

Includes built-in processing features:

Transparency handling
Opacity adjustment
Noise filter effects
🚀 Built for Real Developer Workflows

Instead of clicking through online tools one by one, this app lets you:

Drag & drop multiple SVG files
Process everything in batch
Monitor real-time progress
Pause, resume, or stop tasks
Export everything as a ZIP file

It’s designed for speed and productivity.

⚙️ Performance & Architecture

Under the hood, it uses:

Multi-threaded processing (faster batch execution)
CairoSVG for high-quality rendering
Pillow for image optimization
Queue-based UI updates for smooth performance

Even with large batches, it stays stable and responsive.

🔒 Fully Offline = Full Privacy

Everything runs locally on your machine.

No:

Internet connection required
File uploads
External API calls
Tracking or logging of your files

Your assets stay 100% private.

👨‍💻 Who This Is For

This tool is ideal for:

Frontend developers
UI/UX designers
App developers
Icon designers
Anyone working with SVG assets

If you constantly convert icons or design assets, this saves a lot of time.

💡 Why It’s Different

Instead of juggling multiple tools, you get one unified desktop app that handles:

Conversion
Optimization
Processing
Exporting

All in one place, fully offline.

🛒 Get the Tool

If you want to try it or use it in your workflow:

👉 Buy SVG Converter PRO here:
https://matetools.gumroad.com/l/wdzph

🧾 Final Thoughts

Most SVG tools are built for convenience — but not for serious workflows.

This one is built for speed, control, and offline reliability.

If you work with SVGs regularly, it might save you more time than you expect.

🚀 Build a File Share Safety Checker (Python + Tkinter)

Mate Technologies — Tue, 21 Apr 2026 03:07:00 +0000

Detect hidden risks before sharing files — metadata, secrets, and more.

In this tutorial, we’ll build a desktop privacy scanner using Python.
It helps you analyze files and detect:

🔐 Sensitive filenames (passwords, API keys…)
📸 Image metadata (GPS location, device info)
📄 PDF author info
📊 Hidden Excel sheets
📦 Suspicious ZIP contents
🧰 1. Install Dependencies

First, install required libraries:

pip install pillow pypdf openpyxl ttkbootstrap tkinterdnd2

🏗️ 2. Basic App Setup

We start by creating the main window using tkinter and ttkbootstrap.

import tkinter as tk
import ttkbootstrap as tb
from tkinterdnd2 import TkinterDnD

APP_NAME = "File Share Safety Checker PRO"
APP_VERSION = "3.5.0"

app = TkinterDnD.Tk()
app.title(f"{APP_NAME} v{APP_VERSION}")
app.geometry("1400x780")

tb.Style("darkly")

💡 Explanation
TkinterDnD.Tk() → enables drag & drop
ttkbootstrap → modern UI theme
geometry() → sets window size
📦 3. App State (Core Variables)

We store files, results, and UI communication here:

from queue import Queue
import threading

file_list = []
results = {}

ui_queue = Queue()
progress_var = tk.IntVar(value=0)

context_mode = tk.StringVar(value="PUBLIC")
cancel_flag = threading.Event()

💡 Why this matters
results → stores scan findings
ui_queue → thread-safe UI updates
context_mode → affects risk scoring
⚠️ 4. Risk Engine (Scoring System)

This is the brain of the app.

def add_issue(file, score, msg):
    if file not in results:
        results[file] = {"score": 0, "issues": []}
    results[file]["score"] += score
    results[file]["issues"].append(msg)

💡 What it does
Adds issues per file
Increases risk score
Final Score Calculation

def finalize_score(file):
    score = min(results[file]["score"], 100)

    if context_mode.get() == "INTERNAL":
        score = int(score * 0.7)

    if score >= 70:
        risk = "HIGH"
    elif score >= 40:
        risk = "WARNING"
    elif score > 0:
        risk = "INFO"
    else:
        risk = "OK"

    return score, risk

💡 Logic
Caps score at 100
Reduces risk if internal use
Converts score → readable level
🔍 5. File Detection Rules
🧠 5.1 Filename Scanner

import os

def check_filename(file):
    keywords = ["password","secret","salary","api","key","private","token"]
    name = os.path.basename(file).lower()

    for k in keywords:
        if k in name:
            add_issue(file, 40, f"Sensitive keyword: {k}")

💡 Detects:
risky file names like password.txt
📸 5.2 Image Metadata Scanner

from PIL import Image, ExifTags

def check_image(file):
    try:
        img = Image.open(file)
        exif = img._getexif()

        if not exif:
            return

        for tag, val in exif.items():
            tag_name = ExifTags.TAGS.get(tag, tag)

            if "GPS" in str(tag_name):
                add_issue(file, 70, "GPS location found")

            if "Model" in str(tag_name):
                add_issue(file, 10, f"Device: {val}")
    except:
        pass

💡 Detects:
📍 GPS location (high risk)
📱 Device model
📄 5.3 PDF Metadata

from pypdf import PdfReader

def check_pdf(file):
    try:
        reader = PdfReader(file)
        meta = reader.metadata

        if meta and meta.author:
            add_issue(file, 30, f"Author: {meta.author}")
    except:
        pass

📊 5.4 Excel Hidden Sheets

from openpyxl import load_workbook

def check_excel(file):
    try:
        wb = load_workbook(file)

        for s in wb.worksheets:
            if s.sheet_state != "visible":
                add_issue(file, 30, f"Hidden sheet: {s.title}")
    except:
        pass

📦 5.5 ZIP Scanner

import zipfile

def check_zip(file):
    try:
        with zipfile.ZipFile(file) as z:
            for name in z.namelist():
                if any(x in name.lower() for x in ["password","secret","key"]):
                    add_issue(file, 60, f"ZIP contains: {name}")
    except:
        pass

⚡ 6. Multithreaded Scanner

We scan files in parallel for speed.

from concurrent.futures import ThreadPoolExecutor, as_completed

def scan():
    results.clear()
    ui_queue.put(("clear_results", None))

    files = list(file_list)
    total = len(files)

    def worker(file):
        check_filename(file)

        if file.lower().endswith((".jpg",".png",".jpeg")):
            check_image(file)
        elif file.endswith(".pdf"):
            check_pdf(file)
        elif file.endswith(".xlsx"):
            check_excel(file)
        elif file.endswith(".zip"):
            check_zip(file)

Run Threads

    done = 0

    with ThreadPoolExecutor(max_workers=6) as ex:
        futures = [ex.submit(worker, f) for f in files]

        for f in as_completed(futures):
            done += 1
            ui_queue.put(("progress", int(done/total*100)))

Push Results to UI

    for f in results:
        score, risk = finalize_score(f)
        issues = "; ".join(results[f]["issues"])

        ui_queue.put(("result", (f, risk, score, issues)))

🔐 7. Sanitize Images (Remove Metadata)

from PIL import Image

def strip_metadata_copy(src, dest_folder):
    try:
        img = Image.open(src)
        data = list(img.getdata())

        clean = Image.new(img.mode, img.size)
        clean.putdata(data)

        new_path = os.path.join(dest_folder, os.path.basename(src))
        clean.save(new_path)

        return new_path
    except:
        return None

💡 What it does
Removes EXIF metadata
Keeps only raw pixels
📁 8. File Input (UI Actions)
Add Files

from tkinter import filedialog

def add_files():
    files = filedialog.askopenfilenames()
    for f in files:
        if f not in file_list:
            file_list.append(f)

Add Folder

def add_folder():
    folder = filedialog.askdirectory()

    for root, _, files in os.walk(folder):
        for f in files:
            file_list.append(os.path.join(root, f))

Drag & Drop

def drop_files(event):
    files = app.tk.splitlist(event.data)

    for f in files:
        if os.path.isfile(f):
            file_list.append(f)

📊 9. Export Results (CSV)

import csv

def export_csv():
    path = filedialog.asksaveasfilename(defaultextension=".csv")

    with open(path,"w",newline="",encoding="utf-8") as f:
        writer = csv.writer(f)
        writer.writerow(["File","Risk","Score","Issues"])

        for row in tree.get_children():
            data = tree.item(row)["values"]
            if data[1] in ("HIGH","WARNING"):
                writer.writerow(data)

🔄 10. Thread-Safe UI Updates

from queue import Empty

def process_queue():
    try:
        while True:
            cmd, data = ui_queue.get_nowait()

            if cmd == "result":
                tree.insert("", "end", values=data, tags=(data[1],))

            elif cmd == "progress":
                progress_var.set(data)

            elif cmd == "clear_results":
                tree.delete(*tree.get_children())

    except Empty:
        pass

    app.after(80, process_queue)

🎯 Final Thoughts

You just built a real-world security tool with:

⚡ Multithreading
🧠 Risk scoring engine
📁 File analysis system
🔐 Metadata sanitization
🖥️ Modern GUI
💡 Next Improvements

Want to level this up?

🔍 Add AI-based content scanning
📸 Add thumbnail preview for all file types
📊 Add risk dashboard (charts)
🔐 Add one-click “Sanitize All”

WatermarkX v1.0 – Professional Watermark Tool for Images

Mate Technologies — Mon, 20 Apr 2026 13:16:00 +0000

Adding watermarks to images is a common task for photographers, designers, and content creators who want to protect their work. WatermarkX v1.0 is a lightweight, fast, and professional tool that allows you to add text and logo watermarks to your images with precision.

Get WatermarkX v1.0 here

Features
Text Watermarks: Add custom text with adjustable font size, color, rotation, and stroke (outline).
Logo Support: Overlay a PNG logo with transparency.
Repeat Diagonal Mode: Tile the watermark diagonally across the image.
Drag & Drop: Simply drag your images into the application for quick processing.
Real-Time Progress: Monitor processing speed and ETA with live updates.
Batch Processing: Apply watermarks to multiple images at once.
User Interface

WatermarkX uses a clean and intuitive interface built with Tkinter + TTKBootstrap:

Watermark Settings: Customize text, font size, opacity, rotation, stroke, and color.
Output & Actions: Choose your output folder, browse images, load logos, and apply watermarks.
Processing: Progress bar shows real-time updates for ETA and speed.
Image Preview: Gallery displays thumbnails of selected images, supporting drag & drop.
How It Works
Select Images: Use the "Browse Images" button or drag & drop into the preview area.
Set Watermark: Enter your watermark text, select font size, opacity, rotation, stroke, and pick a color.
Optional Logo: Load a PNG logo to include with your watermark.
Repeat or Single: Enable “Repeat Diagonal” to tile the watermark across the image.
Apply: Click “🔥 APPLY” to start processing. You can stop at any time using the "🛑 STOP" button.
Output: Your watermarked images are saved to the chosen output folder.
Developer Notes

WatermarkX v1.0 is built with:

Python 3.x
Tkinter + TTKBootstrap for UI
Pillow for image processing
TkinterDnD2 for drag & drop support
Threading for smooth UI during batch processing

The application ensures non-blocking UI updates while processing multiple images, with precise placement for text and logos, including rotation and stroke effects.

Download & Try

You can get the full version of WatermarkX v1.0 from Gumroad:

💻 Download WatermarkX v1.0

This version is perfect for photographers, designers, and content creators who want a fast, reliable, and professional watermarking solution without complicated setups.

🔗 Build a Link Extractor & Broken Link Checker (Python + PySide6)

Mate Technologies — Sun, 19 Apr 2026 13:59:00 +0000

In this tutorial, we’ll build a desktop app that:

✅ Extracts links from files (.txt, .pdf, .html)
✅ Filters links (include/exclude keywords)
✅ Checks if links are broken
✅ Displays results with colors (🟢 working / 🔴 broken)
✅ Uses a modern GUI with PySide6

📦 Step 1: Install Dependencies

First, install required packages:

pip install PySide6 requests PyPDF2

🧠 Step 2: Import Required Libraries

We start by importing everything we need:

import os
import sys
import re
import requests
import time
import platform
import subprocess

from PySide6.QtWidgets import *
from PySide6.QtCore import Qt, QThread, Signal, QTimer
from PySide6.QtGui import QColor, QIcon, QGuiApplication

import PyPDF2

💡 Explanation:
os, re → file handling + regex
requests → check links
PySide6 → GUI framework
PyPDF2 → extract text from PDFs
🧵 Step 3: Create a Background Worker (QThread)

We use a thread so the UI doesn’t freeze while scanning.

class LinkWorker(QThread):
    found = Signal(str, bool)
    progress = Signal(int)
    finished = Signal()

💡 Why?

GUI apps must stay responsive, so heavy work runs in a thread.

🔍 Step 3.1: Initialize Worker

def __init__(self, folder, file_types, check_broken, include_words=None, exclude_words=None):
    super().__init__()
    self.folder = folder
    self.file_types = file_types
    self.check_broken = check_broken
    self.include_words = include_words or []
    self.exclude_words = exclude_words or []
    self.seen_links = set()
    self._running = True

💡 Features:
Avoid duplicate links
Support include/exclude filters
Allow stopping process
📂 Step 3.2: Scan Files

def run(self):
    all_files = []

    for root, _, files in os.walk(self.folder):
        for f in files:
            ext = os.path.splitext(f)[1].lower()

            if (ext == '.txt' and self.file_types['txt']) or \
               (ext == '.pdf' and self.file_types['pdf']) or \
               (ext in ['.html', '.htm'] and self.file_types['html']):
                all_files.append(os.path.join(root, f))

💡 What happens:
Recursively scans folders
Filters only selected file types
🔗 Step 3.3: Extract Links

urls = re.findall(r'https?://[^\s"\'>]+', text)

💡 Regex explained:
Matches http:// or https://
Stops at spaces or quotes
📄 Handle PDF Files

reader = PyPDF2.PdfReader(f)
for page in reader.pages:
    text = page.extract_text()

🎯 Step 3.4: Apply Filters

if self.include_words and not any(w in url for w in self.include_words):
    continue

if self.exclude_words and any(w in url for w in self.exclude_words):
    continue

💡 Example:
Include: google
Exclude: facebook
🌐 Step 3.5: Check Broken Links

def check_link(self, url):
    try:
        res = requests.get(url, timeout=10)
        return not (200 <= res.status_code < 400)
    except:
        return True

💡 Logic:
200–399 → OK
400+ → broken
🖥️ Step 4: Build the GUI

Create the main window:

class LinkApp(QWidget):
    def __init__(self):
        super().__init__()
        self.setWindowTitle("LinkGuardian")
        self.setMinimumSize(1000, 600)

📁 Step 4.1: Folder Selection

self.path_input = QLineEdit()
self.path_input.setReadOnly(True)

browse_btn = QPushButton("Browse")
browse_btn.clicked.connect(self.browse_folder)
def browse_folder(self):
    folder = QFileDialog.getExistingDirectory(self)
    if folder:
        self.path_input.setText(folder)
        self.folder = folder

⚙️ Step 4.2: Options (Checkboxes)

self.txt_checkbox = QCheckBox(".txt")
self.pdf_checkbox = QCheckBox(".pdf")
self.html_checkbox = QCheckBox(".html")

self.check_broken_checkbox = QCheckBox("Check Broken Links")

🔍 Step 4.3: Filters

self.include_input = QLineEdit()
self.include_input.setPlaceholderText("Include words")

self.exclude_input = QLineEdit()
self.exclude_input.setPlaceholderText("Exclude words")

▶️ Step 4.4: Start Scan

def start_scan(self):
    self.worker = LinkWorker(
        self.folder,
        {
            'txt': self.txt_checkbox.isChecked(),
            'pdf': self.pdf_checkbox.isChecked(),
            'html': self.html_checkbox.isChecked()
        },
        self.check_broken_checkbox.isChecked(),
        self.include_input.text().split(","),
        self.exclude_input.text().split(",")
    )

    self.worker.found.connect(self.add_link)
    self.worker.start()

🎨 Step 5: Display Results

def add_link(self, link, is_broken):
    item = QListWidgetItem(link)

    color = QColor("red") if is_broken else QColor("green")
    item.setForeground(color)

    self.results_list.addItem(item)

💡 Result:
🟢 Green → Working link
🔴 Red → Broken link
📊 Step 6: Progress Bar

self.progress_bar = QProgressBar()
self.progress_bar.setMaximum(100)

Update it from the worker:

self.worker.progress.connect(self.progress_bar.setValue)
📋 Step 7: Copy All Links

def copy_all_links(self):
    links = "\n".join(
        self.results_list.item(i).text()
        for i in range(self.results_list.count())
    )

    QGuiApplication.clipboard().setText(links)

🌍 Step 8: Open Links on Double Click

def open_item(self, item):
    url = item.text()

    if platform.system() == "Windows":
        os.startfile(url)
    else:
        subprocess.Popen(["xdg-open", url])

🚀 Step 9: Run the App

if __name__ == "__main__":
    app = QApplication(sys.argv)
    window = LinkApp()
    window.show()
    sys.exit(app.exec())

🎉 Final Result

You now have a professional desktop tool that:

✔ Extracts links from files
✔ Filters intelligently
✔ Detects broken links
✔ Displays results beautifully
✔ Runs smoothly with threads

💡 Bonus Ideas

Want to upgrade it further?

Export results to CSV
Add domain grouping
Add link preview
Add multi-threaded link checking (faster 🚀)

FileScope v1.3.2 PRO – Ultra-Fast Professional File & Content Search

Mate Technologies — Sat, 18 Apr 2026 13:10:00 +0000

Looking for a powerful file search tool that can handle complex searches, filters, and exclusions with speed? Meet FileScope v1.3.2 PRO: a professional file & content search application designed for developers, power users, and IT professionals.

➡️ Get it here: FileScope v1.3.2 PRO on Gumroad

🚀 Key Features
Ultra-fast recursive scanning
Quickly scan directories of any size without slowing down.
Treeview-based results panel
Navigate matches easily with full path visibility.
Single-click copy full file path
Copy a path instantly with just one click.
Double-click to open files
Open files directly from the results panel.
Right-click to open containing folder
Access files in their folder context instantly.
Regex & multi-term search support
Advanced search options for precision filtering.
File type filters & folder exclusions
Focus your search on the files you care about.
Real-time ETA & scan speed metrics
Track progress with live updates for estimated completion and throughput.
🎯 Use Cases

FileScope PRO is perfect for:

Developers looking for specific files or code snippets.
IT admins performing content audits.
Researchers scanning large datasets.
Anyone who needs a fast, reliable file search tool beyond the OS default.
🖥️ User Interface

FileScope PRO comes with a sleek dark-themed UI, built using ttkbootstrap for Python. Its intuitive interface allows:

Selecting a root folder
Choosing search type: Folder Name, File Name, or Word in File
Applying file type filters and folder exclusions
Enabling Regex searches
Real-time progress monitoring
💡 How It Works
Choose a root folder to scan.
Select the type of search.
Enter your search query.
Optionally, set filters and excluded folders.
Click SEARCH and watch matches populate the treeview.
Stop search anytime with STOP.

Treeview interactions:

Click → copy file path
Double-click → open file
Right-click → open containing folder
📦 About the Developer

Developed by Mate Technologies, FileScope PRO is designed with professionals in mind. It combines speed, accuracy, and ease-of-use in a single lightweight tool.

Get your copy here: https://gum.new/gum/cmkbaon6z000004jq9gt46uk8

FileScope v1.3.2 PRO is a must-have tool if you regularly handle large file sets or need advanced search functionality beyond what your OS provides.

🔗 LinkGuardian PRO v5.0 – Scan, Validate, and Analyze Links Like a Pro

Mate Technologies — Fri, 17 Apr 2026 13:33:00 +0000

Broken links are one of those problems that quietly destroy the quality of your projects. Whether you're managing documentation, scraping data, or maintaining content, invalid URLs can lead to poor UX, failed integrations, and unreliable datasets.

I built LinkGuardian PRO v5.0 to solve this problem in a fast, local, and developer-friendly way.

⚡ The Problem

If you’ve ever tried to:

Audit links inside .txt, .pdf, or .html files
Validate hundreds (or thousands) of URLs
Identify broken endpoints
Organize links by domain

You already know how painful it is to do this manually.

Even with scripts, you often miss:

UI visibility
pause/resume control
structured reporting
domain-level insights
🚀 The Solution

LinkGuardian PRO v5.0 is a desktop-based, multi-threaded link scanner that:

Extracts URLs from local files
Checks link status (valid / broken)
Tracks domain-level statistics
Provides real-time feedback via UI

All without uploading your data anywhere.

🧠 Core Features
🔄 Multi-threaded Link Checking

Uses ThreadPoolExecutor to validate links concurrently for maximum speed.

📄 Multi-format Support

Parses links from:

.txt
.pdf (via PyPDF2)
.html / .htm
❌ Broken Link Detection

HTTP requests are validated with timeout handling to catch:

dead domains
unreachable servers
invalid endpoints
🌐 Domain Analytics

Automatically groups links by domain:

example.com | 120 links | 15 broken
api.service.io | 80 links | 2 broken

Perfect for auditing and prioritization.

🎯 Include / Exclude Filters

Filter links dynamically using keywords:

Include only specific patterns
Exclude tracking, ads, or unwanted URLs
📊 CSV Export

Export domain-level reports for:

audits
clients
documentation
⏸ Full Scan Control

Pause, resume, or cancel scans anytime without losing progress.

🖥️ UI Highlights

Built with Tkinter + ttkbootstrap, the app provides:

Dark-themed modern interface
Real-time logs
Progress tracking
Click-to-open links
Search/filter within results

This makes it more than just a script — it’s a usable tool.

🔧 How It Works (Simplified)

def safe_request(url):
    try:
        r = requests.get(url, timeout=8)
        return not (200 <= r.status_code < 400)
    except:
        return True

Each link is:

Extracted via regex
Checked via HTTP request
Categorized as valid or broken
Aggregated into domain statistics
🔐 Why Local-First Matters

Unlike many tools, LinkGuardian PRO runs entirely on your machine:

No cloud APIs
No data leaks
No rate-limited external services

This is especially important for:

internal company files
private datasets
sensitive documents
💼 Use Cases

This tool is useful if you:

Maintain documentation or knowledge bases
Work with scraped or extracted links
Audit SEO or content quality
Manage large file repositories
Build datasets from mixed file formats
📈 Developer Benefits
Clean Python architecture
Easy to customize (filters, UI, logic)
Extendable for APIs or automation
Works cross-platform (with source code)
🔗 Try It Out

If you want to save hours of manual work and bring structure to your link validation process:

👉 https://gum.new/gum/cmn1sdj00000804jsh4tu21gf

🏁 Final Thoughts

This project started as a simple link checker — but evolved into a full productivity tool.

If you deal with links at scale, having:

speed
visibility
control

…makes a huge difference.

RiskScan PRO v2.0.0 – Professional File Risk Assessment Tool

Mate Technologies — Thu, 16 Apr 2026 13:04:00 +0000

RiskScan PRO is a professional file risk assessment and threat discovery tool designed for security-conscious users. It uses heuristic scoring, MITRE ATT&CK mapping, and a confidence engine to detect potentially dangerous files on your system.

Get RiskScan PRO here
✅

Key Features
Scan files and folders for potential security risks
Heuristic scoring based on file type, size, name, and location
MITRE ATT&CK threat mapping for deeper analysis
Real-time scan progress with ETA and scan speed
Export results to TXT, JSON, or PDF for reporting
Interactive results tree: copy path, open file, or open folder directly
How It Works
Select a target: Choose a file or folder to scan.
Start scanning: RiskScan PRO evaluates files using predefined rules and heuristic scoring.
Review results: Files are categorized into HIGH, MEDIUM, or LOW severity.
Export reports: Generate TXT, JSON, or PDF reports for documentation or sharing.
Example Rules and Detection
Dangerous Extensions: .exe, .bat, .cmd, .ps1, .vbs, .js, .scr, .dll
Suspicious Names: crack, keygen, loader, hack, trojan, virus
Suspicious Directories: appdata, temp, startup
Small Executables: Executables under 15 KB may indicate potentially harmful files

Each file is scored based on these rules and mapped to MITRE ATT&CK techniques like T1059 (Command-Line Interface) and T1547 (Persistence).

User Interface Highlights
Dark-themed, modern UI powered by ttkbootstrap
Progress bar showing scan completion percentage
Speed & ETA updates in real-time
Interactive results tree with single-click copy, double-click to open, and right-click to open folder
Usage Tips
Always review HIGH severity files first.
Use the STOP button to halt scans safely.
Export reports for documentation or sharing with team members.
Add trusted paths to the exclude list to avoid false positives.
Developer Info

RiskScan PRO v2.0
Developed by Mate Technologies
https://matetools.gumroad.com

⚠ Note: RiskScan PRO is a security tool. Always verify files before opening, even after scanning. The software is designed to assist in file risk assessment, not replace full antivirus solutions.

Download RiskScan PRO v2.0.0

DupCleaner PRO v4.1.0 – Professional Duplicate File Cleaner for Developers and Power Users

Mate Technologies — Wed, 15 Apr 2026 08:41:00 +0000

If you’ve ever worked with large datasets, design assets, or development projects, you know how quickly duplicate files can pile up. DupCleaner PRO v4.1.0 is a professional desktop tool designed to scan, detect, and clean duplicate files efficiently, safely, and reliably.

Why Developers & Power Users Will Love It

DupCleaner PRO isn’t just a basic cleaner — it’s engineered for performance and control:

Fast Multi-threaded Scanning: Groups files by size first, then hashes them using SHA256 for precise duplicate detection.
Safe Deletion: Files are moved to the Recycle Bin; permissions are fixed automatically if needed.
Smart Cleaning: Keeps the largest and newest version while safely removing redundant files.
Preview & Verify: Supports thumbnails and full-size previews for images (PNG, JPG, GIF, BMP, TIFF).
Export Detailed Reports: CSV reports with file paths, sizes, last modified dates, and hashes — perfect for auditing or record keeping.
How It Works
Add Files or Folders: Add individual files or entire directories. DupCleaner PRO can handle large datasets efficiently.
Scan: Files are grouped and hashed, duplicates detected. Progress is displayed in real-time, with pause/resume support.
Review Duplicates: Duplicate groups appear in the UI with file size, modification date, and thumbnail previews.
Smart Clean: Safely remove duplicates while keeping your most relevant files intact.
Export Report: Save a detailed CSV for auditing or documentation.
Built for Professionals

Whether you’re a developer, designer, data analyst, or IT professional, DupCleaner PRO simplifies file management, reduces clutter, and improves productivity.

Getting Started

DupCleaner PRO v4.1.0 is ready to use on Windows and comes with a modern, dark-themed interface. It’s designed to be fast, safe, and intuitive, even for large projects with thousands of files.

💻 Buy or download now: https://gum.new/gum/cmn028ko9000004l2dkhjcxt5

Key Features
✅ Multi-threaded scan & hash
✅ Safe deletion with Recycle Bin support
✅ Pause/resume scanning
✅ Smart Clean to retain the newest/largest file
✅ Image preview with thumbnails
✅ CSV report export

PDFSnap – Convert PDFs to PNG or JPG Effortlessly

Mate Technologies — Tue, 14 Apr 2026 13:00:00 +0000

Get PDFSnap Here →

If you often work with PDFs and need high-quality images for documentation, presentations, or archiving, PDFSnap is a Windows-based tool designed to make PDF-to-image conversion fast, flexible, and professional.

Overview

PDFSnap is a lightweight desktop application built with Python and ttkbootstrap
, providing a sleek dark-themed GUI. It allows:

Single PDF conversion
Batch folder mode
Automatic subfolder creation per PDF
Preservation of original page numbers in filenames
Threaded conversion with live progress logging

It supports output in both PNG and JPG formats.

Key Features
Convert PDF pages to images – High-resolution PNG or JPG output.
Batch folder mode – Process multiple PDFs in one go.
Organized output – Automatically create subfolders for each PDF.
Flexible naming – Preserve original page numbers or use custom prefixes.
Real-time feedback – Live log updates and progress bar.
Dark-themed GUI – Modern, user-friendly interface using ttkbootstrap.
How It Works
Select a PDF or Folder – Choose a single PDF or an entire folder containing PDFs.
Set Output Options – Choose PNG or JPG, select an output folder, and set naming preferences.
Start Conversion – Click Start Conversion. The app processes PDFs in a separate thread, showing live logs and progress.
Stop Anytime – The Stop button lets you safely halt the process if needed.
Advanced Options
Preserve Original Page Numbers: Keeps filenames like Page1, Page2, etc.
Create Subfolder per PDF: Keeps output organized automatically.
Batch Folder Mode: Perfect for handling large PDF collections efficiently.
Typical Use Cases
Converting multi-page PDFs into individual image files for documentation or web use.
Quickly exporting pages from a large PDF library into JPG/PNG format.
Professional workflows requiring organized image output from PDFs.
Installation & Requirements
Windows OS
Python 3.x (if using the source code) or precompiled executable
Ghostscript installed for PDF rendering (required for image conversion)
Developer & Support

PDFSnap
Developed by Mate Technologies
Purchase / Download PDFSnap

Tip: Use batch mode with subfolder creation to keep your output neat when processing multiple PDFs.

This version keeps it concise, highlights features, workflow, and use cases, and links directly to your Gumroad page.

CSVtoExcel PRO v3.0.0 – Convert CSV to Excel Effortlessly (Offline, Batch, Styled Export)

Mate Technologies — Mon, 13 Apr 2026 10:58:00 +0000

CSVtoExcel PRO is a professional desktop application built for developers, data analysts, business professionals, and researchers who need a fast, reliable, and fully offline solution to convert CSV files into clean, structured Excel workbooks.

Whether you’re working with large datasets, preparing reports, or migrating data, CSVtoExcel PRO simplifies your workflow with multi-sheet export, smart delimiter detection, batch processing, drag & drop support, and live progress tracking.

💻 Get it here: https://gum.new/gum/cmmxp3gh6000g04l8cxzjd0nq

Key Features

Multi-sheet Excel export for large CSV files

Automatic delimiter detection (comma, semicolon, tab, etc.)

Clean uneven or broken CSV rows automatically

Batch processing for multiple files or entire folders

Drag & drop support for faster workflow

Conversion history tracking with SQLite

Preview first 200 rows before converting

Bold headers and auto-adjusted column widths

Support for UTF-8, Latin1, UTF-16, CP1252 encodings

Live progress updates and cancel conversion anytime

Modern dark-themed interface built with Tkinter + ttkbootstrap

Optional Python source code for full customization

How It Works

Add Files or Folder – Select individual CSV files or load an entire folder.

Preview Data – Check the first 200 rows, auto-detect delimiters, and choose whether to use headers.

Configure Options – Set output folder, choose encoding, enable/disable headers.

Convert CSV to Excel – Start conversion with live progress, batch processing, and multi-sheet splitting for large files.

View History – Track all previous conversions and manage files.

All processing is local. No cloud uploads, no internet required. Your data remains fully secure.

Workflow & Productivity Tips

Batch Conversion – Convert hundreds of CSV files in one go.

Drag & Drop – Easily add multiple files.

Live Progress – Monitor current file, row progress, and total conversion percentage.

Cancel Anytime – Stop long-running conversions safely.

Styled Output – Excel sheets come with bold headers and auto-adjusted column widths.

History Tracking – Keep a full record of previous conversions for auditing or reuse.

Who Is This For?

Data Analysts & Researchers

Business Professionals & Accountants

Developers handling CSV exports

Students working with large datasets

Anyone who needs clean Excel exports from CSV files

Versions & Pricing

EXE Version: $7 – Ready-to-run Windows executable, no Python required

Full Python Source Code: $10 – Fully editable code for customization

EXE + Full Source Code: $12 – Best of both worlds

📥 Get it now: https://gum.new/gum/cmmxp3gh6000g04l8cxzjd0nq

System Requirements

Windows 10+ (EXE version)

Python 3.10+ (source code version)

Packages: xlsxwriter, Tkinter, ttkbootstrap

Optional: pandas (for custom CSV preprocessing)

Fully offline execution, no internet required

CSVtoExcel PRO is designed to make CSV → Excel conversion professional, fast, and completely offline. Whether you just want a ready-to-use EXE or the full Python source for customization, it’s your all-in-one solution for handling CSV files like a pro.

🔗 LinkVault PRO v2.0.0 – Professional Link Extraction Tool

Mate Technologies — Sun, 12 Apr 2026 12:52:00 +0000

LinkVault PRO is a production-ready Python tool designed for extracting URLs from TXT, PDF, and HTML files in a folder recursively. It supports file type filtering, duplicate removal, and exports results in TXT, JSON, or PDF formats with a glowing progress interface.

Get it here: https://gum.new/gum/cmkf1hjun000404l2fqerdq39

Features
✅ Recursive folder scanning
✅ File type filtering: .txt, .pdf, .html/.htm
✅ Duplicate link filtering
✅ Glowing progress bar with ETA and speed
✅ Copy links to clipboard
✅ Open links by double-click
✅ Export results to TXT, JSON, or PDF
Installation

Install dependencies

pip install ttkbootstrap PyPDF2 reportlab

Download the executable version from Gumroad: https://gum.new/gum/cmkf1hjun000404l2fqerdq39

How to Use
Launch LinkVault PRO.
Select your target folder.
Choose which file types to scan (.txt, .pdf, .html).
Click START EXTRACTION to begin.
Monitor the progress, ETA, and speed in real time.
Once complete, you can export results to TXT, JSON, or PDF.

💡 Tips:

Double-click a link in the results to open it.
Right-click a link to open the folder containing the source file.
Copy links to clipboard by clicking once.
Use STOP to safely cancel extraction anytime.
Export Options
TXT – One link per line, ideal for documentation or scripts.
JSON – Structured export with timestamp and version info.
PDF – Report-ready format with all links listed.
Developer Info

LinkVault PRO v2.0
Developed by MateTools

Gumroad Link →

Screenshots / UI Highlights
Clean, dark-themed interface using ttkbootstrap
Tree view for extracted links with copy, open, and folder navigation
Progress bar with ETA, speed, and live counter
Export buttons for all supported formats
Code Snippet – Extraction Engine

def extract_links_worker(folder, file_types):
    global link_results, link_count
    link_results.clear()
    link_count = 0

    files = [
        os.path.join(root, f)
        for root, _, fs in os.walk(folder)
        for f in fs
        if (f.endswith('.txt') and file_types['txt']) or
           (f.endswith('.pdf') and file_types['pdf']) or
           (f.endswith(('.html', '.htm')) and file_types['html'])
    ]

    for i, path in enumerate(files, 1):
        urls = []
        ext = os.path.splitext(path)[1].lower()
        if ext in ['.txt', '.html', '.htm']:
            with open(path, 'r', encoding='utf-8', errors='ignore') as f:
                urls = re.findall(r"https?://[^\s\"'>]+", f.read())
        elif ext == '.pdf':
            with open(path, 'rb') as f:
                reader = PyPDF2.PdfReader(f)
                for page in reader.pages:
                    text = page.extract_text()
                    if text: urls.extend(re.findall(r"https?://[^\s\"'>]+", text))

        for url in urls:
            if url not in link_results:
                link_results.append(url)

LinkVault PRO v2.0.0 is perfect for developers, researchers, content managers, or anyone who needs to quickly collect and organize links from multiple file types in bulk.

Grab your copy here: https://gum.new/gum/cmkf1hjun000404l2fqerdq39

🚀 Build a CSV to Excel Desktop App (PySide6 + SQLite)

Mate Technologies — Sat, 11 Apr 2026 12:30:00 +0000

🔗 GitHub Repo: https://github.com/rogers-cyber/CSVtoExcel

In this tutorial, you’ll learn how to build a modern desktop app that:

Converts CSV → Excel (.xlsx)

Shows a preview of data

Saves history using SQLite

Supports batch processing

🧱 Step 1 — Install Dependencies

First, install required packages:

pip install PySide6 xlsxwriter

🧠 Step 2 — Project Structure

Create a simple structure:

csv_to_excel_app/
│
├── main.py
└── logo.ico (optional)
⚙️ Step 3 — Basic App Setup

Let’s create a minimal PySide6 app window.

import sys
from PySide6 import QtWidgets

app = QtWidgets.QApplication(sys.argv)

window = QtWidgets.QMainWindow()
window.setWindowTitle("CSVtoExcel")
window.resize(800, 500)

window.show()
sys.exit(app.exec())

👉 This gives you a blank desktop window.

🗂 Step 4 — Create App Data Folder

We store history (SQLite DB) in a system-safe location.

from pathlib import Path
import os
import sys

def get_app_dir() -> Path:
    if sys.platform.startswith("win"):
        base = Path(os.getenv('LOCALAPPDATA') or Path.home())
    elif sys.platform.startswith("darwin"):
        base = Path.home() / 'Library/Application Support'
    else:
        base = Path.home() / '.local/share'

    app_dir = base / "csv_to_excel_app"
    app_dir.mkdir(parents=True, exist_ok=True)
    return app_dir

🗄 Step 5 — Setup SQLite Database

We store conversion history.

import sqlite3

DB_PATH = get_app_dir() / "history.db"

def init_db():
    conn = sqlite3.connect(DB_PATH)
    c = conn.cursor()

    c.execute("""
        CREATE TABLE IF NOT EXISTS history(
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            src_path TEXT,
            dest_path TEXT,
            timestamp TEXT,
            rows INTEGER,
            cols INTEGER
        )
    """)

    conn.commit()
    conn.close()

👉 Call this once when the app starts.

📥 Step 6 — Load CSV File

Let users pick a CSV file.

from PySide6.QtWidgets import QFileDialog

def open_csv():
    file, _ = QFileDialog.getOpenFileName(
        None,
        "Open CSV",
        "",
        "CSV Files (*.csv)"
    )
    return file

👁 Step 7 — Preview CSV Data

We read first 100 rows.

import csv

def preview_csv(path, limit=100):
    rows = []

    with open(path, encoding="utf-8", errors="replace") as f:
        reader = csv.reader(f)
        for i, row in enumerate(reader):
            if i >= limit:
                break
            rows.append(row)

    return rows

👉 This keeps the app fast even with large files.

📊 Step 8 — Convert CSV → Excel

Now the core feature 🔥

import xlsxwriter

def convert_to_excel(csv_path, output_path):
    with open(csv_path, encoding="utf-8", errors="replace") as f:
        reader = csv.reader(f)
        rows = list(reader)

    workbook = xlsxwriter.Workbook(output_path, {'strings_to_urls': False})
    sheet = workbook.add_worksheet()

    for r, row in enumerate(rows):
        for c, value in enumerate(row):
            sheet.write(r, c, value)

    workbook.close()

🧾 Step 9 — Save History

Every conversion is stored.

from datetime import datetime

def save_history(src, dest, rows, cols):
    conn = sqlite3.connect(DB_PATH)
    c = conn.cursor()

    c.execute(
        "INSERT INTO history (src_path, dest_path, timestamp, rows, cols) VALUES (?, ?, ?, ?, ?)",
        (src, dest, datetime.utcnow().isoformat(), rows, cols)
    )

    conn.commit()
    conn.close()

🧵 Step 10 — Run Conversion in Background

We avoid freezing the UI using threads.

from PySide6.QtCore import QRunnable, QThreadPool

class Worker(QRunnable):
    def __init__(self, csv_path, output):
        super().__init__()
        self.csv_path = csv_path
        self.output = output

    def run(self):
        convert_to_excel(self.csv_path, self.output)

Run it:

pool = QThreadPool()
pool.start(Worker("input.csv", "output.xlsx"))

🖥 Step 11 — Build UI Layout

Add buttons + table preview.

layout = QtWidgets.QVBoxLayout()

btn_open = QtWidgets.QPushButton("Open CSV")
btn_convert = QtWidgets.QPushButton("Convert")

table = QtWidgets.QTableWidget()

layout.addWidget(btn_open)
layout.addWidget(btn_convert)
layout.addWidget(table)

🎨 Step 12 — Add Styling (QSS)

app.setStyleSheet("""
QPushButton {
    background: #1976d2;
    color: white;
    padding: 6px;
    border-radius: 6px;
}
QPushButton:hover {
    background: #125aa0;
}
""")

📦 Step 13 — Build EXE (Optional)

Use PyInstaller:

pip install pyinstaller
pyinstaller --onefile --windowed main.py

🎉 Final Result

You now have a desktop app that:

✅ Converts CSV to Excel
✅ Handles large files
✅ Saves history
✅ Has a modern UI

💡 Pro Tips

Add drag & drop support

Add batch folder conversion

Add encoding selector

Add preview table model (QTableView)

🔗 Full Source Code

👉 https://github.com/rogers-cyber/CSVtoExcel