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Simple Tips for Bug Bounty Beginners: Content Spoofing via HTML Injection

NOTE: Make sure to test only on sites where it is allowed to test and carefully read and follow the guidelines for testing on the site.Continue reading on Medium »
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Medium

Simple Tips for Bug Bounty Beginners: Content Spoofing via HTML Injection

NOTE: Make sure to test only on sites where it is allowed to test and carefully read and follow the guidelines for testing on the site.

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The $2500 bug: Remote Code Execution via Supply Chain Attack

Hey there!😇Continue reading on Medium »
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Medium

💵 The $2500 bug: Remote Code Execution via Supply Chain Attack

Hey there!😇

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Exploiting a Referer Header for Open Redirect

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Medium

Exploiting a Referer Header for Open Redirect

Hello Everyone!

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I Hijacked Accounts in 10 Minutes (IDOR Bug)

How I Found a Critical IDOR ATO Exploit in HackerOne (2025)Continue reading on Medium »
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Medium

I Hijacked Accounts in 10 Minutes (IDOR Bug)

How I Found a Critical IDOR ATO Exploit in HackerOne (2025)

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# Walkthrough: VulnHub Machine — Ted 1 (Full Root Access)

⚠️ Disclaimer: This write-up is created purely for educational purposes. The testing was performed in a controlled lab environment on a…Continue reading on Medium »
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Medium

# Walkthrough: VulnHub Machine — Ted (Full Root Access)

⚠️ Disclaimer: This write-up is created purely for educational purposes. The testing was performed in a controlled lab environment on a…

2 views13:21

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Scrapling - An Undetectable, Powerful, Flexible, High-Performance Python Library That Makes Web Scraping Simple And Easy Again!
http://www.kitploit.com/2025/04/scrapling-undetectable-powerful.html

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Hacking Articles Tips Tricks Videos Tutorials

Dealing with failing web scrapers due to anti-bot protections or website changes? Meet Scrapling. Scrapling is a high-performance (https://www.kitploit.com/search/label/Performance), intelligent web scraping library for Python that automatically adapts to website changes while significantly outperforming popular alternatives. For both beginners and experts, Scrapling provides powerful features while maintaining simplicity. >> from scrapling.defaults import Fetcher, AsyncFetcher, StealthyFetcher, PlayWrightFetcher
# Fetch websites' source under the radar!
>> page = StealthyFetcher.fetch('https://example.com', headless=True, network_idle=True)
>> print(page.status)
200
>> products = page.css('.product', auto_save=True) # Scrape data that survives website design changes!
>> # Later, if the website structure changes, pass `auto_match=True`
>> products = page.css('.product', auto_match=True) # and Scrapling still finds them!
Key Features Fetch websites as you prefer with async support HTTP Requests: Fast and stealthy HTTP requests with the Fetcher class. Dynamic Loading & Automation: Fetch dynamic websites with the PlayWrightFetcher class through your real browser, Scrapling's stealth mode, Playwright's Chrome browser, or NSTbrowser (https://app.nstbrowser.io/r/1vO5e5)'s browserless! Anti-bot Protections Bypass: Easily bypass protections with StealthyFetcher and PlayWrightFetcher classes. Adaptive Scraping 🔄 Smart Element Tracking: Relocate elements after website changes, using an intelligent similarity system and integrated storage. 🎯 Flexible Selection: CSS selectors, XPath selectors, filters-based search, text search, regex search and more. 🔍 Find Similar Elements: Automatically locate elements similar to the element you found! 🧠 Smart Content Scraping: Extract data from multiple websites without specific selectors using Scrapling powerful features. High Performance 🚀 Lightning Fast: Built from the ground up with performance in mind, outperforming most popular Python scraping libraries. 🔋 Memory Efficient: Optimized data structures for minimal memory footprint. ⚡ Fast JSON serialization: 10x faster than standard library. Developer Friendly 🛠️ Powerful Navigation API: Easy DOM traversal in all directions. 🧬 Rich Text Processing: All strings have built-in regex, cleaning methods, and more. All elements' attributes are optimized dictionaries that takes less memory than standard dictionaries with added methods. 📝 Auto Selectors Generation: Generate robust short and full CSS/XPath selectors for any element. 🔌 Familiar API: Similar to Scrapy/BeautifulSoup and the same pseudo-elements used in Scrapy. 📘 Type hints: Complete type/doc-strings coverage for future-proofing and best autocompletion support. Getting Started from scrapling.fetchers import Fetcher

fetcher = Fetcher(auto_match=False)

# Do http GET request to a web page and create an Adaptor instance
page = fetcher.get('https://quotes.toscrape.com/', stealthy_headers=True)
# Get all text content from all HTML tags in the page except `script` and `style` tags
page.get_all_text(ignore_tags=('script', 'style'))

# Get all quotes elements, any of these methods will return a list of strings directly (TextHandlers)
quotes = page.css('.quote .text::text') # CSS selector
quotes = page.xpath('//span[@class="text"]/text()') # XPath
quotes = page.css('.quote').css('.text::text') # Chained selectors
quotes = [element.text for element in page.css('.quote .text')] # Slower than bulk query above

# Get the first quote element
quote = page.css_first('.quote') # same as page.css('.quote').first or page.css('.quote')[0]

# Tired of selectors? Use find_all/find
# Get all 'div' HTML tags that one of its 'class' values is 'quote'
quotes = page.find_all('div', {'class': 'quote'})
# Same as
quotes = page.find_all('div', class_='quote')
quotes = page.find_all(['div'], class_='quote')
quotes = page.find_all(class_='quote') # and so on...

# Working with elements

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