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Unsafe Python Functions and Their Alternatives

Python, a versatile and widely adopted programming language, grants developers a toolbox brimming with functions to tackle an array of tasks. Yet, the equal footing of all functions is a misconception; a subset of these functions harbors security vulnerabilities and a propensity for unintended repercussions if wielded imprudently. This segment of the article casts a spotlight on these unsafe Python functions that warrant a discerning eye. We’ll journey through concrete examples, highlighting the associated risks, and then chart a course towards secure alternatives that ensure functionality parity, all while fortifying the bedrock of security and stability.

Introduction: Safeguarding Your Python Odyssey

In the sprawling landscape of programming languages, Python’s allure stems from its expansive library and intuitive syntax. However, beneath this veil of simplicity lie certain functions that, if mishandled, can unravel the very fabric of security and reliability that developers strive to weave. Our voyage into this realm is not one of alarm but of enlightenment. By acclimating ourselves to these potential pitfalls and embracing alternative methodologies, we empower ourselves to construct code that stands resolute against adversity.

Unsafe Python Functions and Their Risks

Using eval() for Dynamic Code Execution

The eval() function allows dynamic execution of Python code from a string. While powerful, it can lead to code injection attacks if user inputs are not properly sanitized. Instead of using eval(), consider using ast.literal_eval() or exec() for controlled and secure code execution.

Using eval() for Dynamic Code Execution:

# Unsafe: Using eval() for dynamic code execution
user_input = input("Enter a Python expression: ")
result = eval(user_input)
print("Result:", result)

Safer alternative using ast.literal_eval():

import ast

user_input = input("Enter a literal value: ")
    parsed_value = ast.literal_eval(user_input)
    print("Parsed value:", parsed_value)
except (ValueError, SyntaxError):
    print("Invalid input.")

String Concatenation with Unsanitized Data

Concatenating strings with unsanitized user inputs can result in SQL injection or cross-site scripting (XSS) vulnerabilities. Utilize f-strings or the str.format() method along with input validation to prevent these security issues.

Unsafe string concatenation:

user_input = input("Enter your name: ")
message = "Hello, " + user_input + "!"

Using f-strings (formatted string literals):

user_input = input("Enter your name: ")
message = f"Hello, {user_input}!"

Pickle for Object Serialization

The pickle module can serialize and deserialize Python objects, but it’s not secure against erroneous or maliciously constructed data. To safely serialize data, opt for libraries like json or marshal that adhere to safer serialization practices.

Using pickle (unsafe):

import pickle

data = {'user': 'admin', 'role': 'admin'}
serialized_data = pickle.dumps(data)
# Store or send serialized_data

Safer alternative using json:

import json

data = {'user': 'admin', 'role': 'admin'}
serialized_data = json.dumps(data)
# Store or send serialized_data

Insufficiently Escaped HTML with mark_safe()

The mark_safe() function in Django allows developers to mark a string as safe HTML, potentially exposing applications to cross-site scripting (XSS) attacks. Instead, utilize template escaping and the safe filter to ensure secure rendering of HTML content.

Unsafe use of mark_safe() in Django template:

from django.utils.safestring import mark_safe

input_data = input("Enter some HTML content: ")
safe_html = mark_safe(input_data)

Safer approach with template escaping:

from django.utils.html import escape

input_data = input("Enter some HTML content: ")
escaped_html = escape(input_data)

Using os.system() for System Commands

The os.system() function can execute system commands, but it’s prone to command injection attacks. Employ the subprocess module for a more secure way to execute system commands and handle their outputs.

Unsafe use of os.system():

command = input("Enter a command: ")

Safer alternative using subprocess:

import subprocess

command = input("Enter a command: ")
result =, shell=True, capture_output=True, text=True)
print("Output:", result.stdout)

Inadequate Password Hashing with hash()

The hash() function is not suitable for securely hashing passwords due to its speed and vulnerability to brute force attacks. Implement robust password hashing using libraries like bcrypt or Argon2 to enhance password security.

Unsafe password hashing with hash():

password = input("Enter your password: ")
hashed_password = hash(password)
# Store hashed_password in the database

Safer approach using bcrypt:

import bcrypt

password = input("Enter your password: ")
hashed_password = bcrypt.hashpw(password.encode('utf-8'), bcrypt.gensalt())
# Store hashed_password in the database

Safer Alternatives and Best Practices

Utilizing requests Instead of urllib

When making HTTP requests, favor the requests library over the outdated urllib. requests provides a more user-friendly and secure interface for sending HTTP requests and handling responses.

Using requests library for HTTP requests:

import requests

url = ""
response = requests.get(url)
if response.status_code == 200:
    data = response.json()
    print("Request failed.")

Secure File Handling with with Statement

To avoid resource leaks and ensure proper file handling, use the with statement when working with files. It automatically handles file closure, reducing the risk of errors and vulnerabilities.

Using with statement for file handling:

filename = "example.txt"

# Unsafe: Without using `with`
file = open(filename, "r")
content =

# Safer: Using `with` statement
with open(filename, "r") as file:
    content =

Sanitizing Inputs with html.escape()

To prevent XSS attacks, sanitize user inputs using the html.escape() function. This ensures that any potentially harmful HTML content is properly escaped before rendering.

Sanitizing user input to prevent XSS attacks:

import html

user_input = input("Enter some text: ")
sanitized_input = html.escape(user_input)
print("Sanitized input:", sanitized_input)

Parameterized Queries with sqlite3

When interacting with databases, employ parameterized queries with the sqlite3 library. This guards against SQL injection attacks by automatically escaping user inputs within queries.

Using parameterized queries with sqlite3:

import sqlite3

db_connection = sqlite3.connect("database.db")
cursor = db_connection.cursor()

name = input("Enter a name: ")
age = input("Enter an age: ")

query = "INSERT INTO users (name, age) VALUES (?, ?)"
cursor.execute(query, (name, age))


Securely Managing Environment Variables

Instead of exposing sensitive information directly in code, use environment variables with the os.environ dictionary or a package like python-decouple for better security and configuration management.

Using os.environ for managing environment variables:

import os

api_key = os.environ.get("API_KEY")
if api_key:
    print("API Key:", api_key)
    print("API Key not set.")

Using python-decouple for managing environment variables:

from decouple import config

api_key = config("API_KEY")
print("API Key:", api_key)

Strong Randomness with secrets

For generating cryptographically secure random values, rely on the secrets module instead of the random module. This ensures a higher level of randomness and is suitable for security-sensitive operations.

Generating secure random tokens with secrets:

import secrets

token = secrets.token_hex(16)
print("Secure Token:", token)


Python’s vast ecosystem empowers developers to create powerful and feature-rich applications. However, using certain functions recklessly can introduce security vulnerabilities and compromise the integrity of your code. By following best practices and opting for safer alternatives, developers can build more secure and reliable software.