The hash table in python is used to store the data through key-value pairs; it is implemented by using the dictionary. A Hash table is one of the data structures that store the data in the form of key-value pair. Every value has a unique key that is generated through a hash function, which makes accessing the data or value in the hash table faster, regardless of the number of values present in the hash table.

Dictionary is the built-in data type in python, with the help of which implements the hash table in python. A hashing function is used in Python to generate the keys of a dictionary. A dictionary’s keys are not ordered and can be modified.

The syntax to create the dictionary in the python –

The dictionary can be created in python by using the braces “{“ and “}” and also can be created by using the dict() function. When creating a dictionary by using the curly braces, the key and value are separated by the “:” and each pair separated by the “,”. Whereas direct() is the built-in function to create the dictionary using dict() function, the key and value are separated by the “=”, and each key-value pairs are separated by the “,”.

The hash table in python can be created with the help of the dictionary, and the dictionary can be created by using the curly braces and dict() function. Suppose we have a dictionary of the student marks which contains the student marks. Now we need to update the student marks data, so we can perform as “Student_marks[56] = 65”, where Student_marks is the dictionary, and 56 is the key stored in the dictionary for the student of roll no 56. So it updates the marks value 65 for roll no 56.

Given below are the examples of the hash table in python:

Example for a hash table in python to create and access the dictionary values –

d = { 'Name' : 'John', 'Rollno' : 34, 'Marks' : 89}

# Access the value of the dictionary with the key

# passing the non-available key in the dictionary

Example for a hash table in python to delete the dictionary key-value pair –

Fruits_count = { 'apple' : 50, 'banana' : 34, 'orange' : 89, 'cherry' : 78}

print( "Fruits_count['apple'] : ", Fruits_count['apple'])

print( "Fruits_count['cherry'] : ", Fruits_count['herry'])

print( "Fruits_count['orange'] : ", Fruits_count['orange'])

# delete the key value pair in dictionary with key

del Fruits_count['apple'] # printing the dictionary

# deleting the non-available key in the dictionary

Example for a hash table in python to update the dictionary values –

Student_marks = { 12 : 59, 56 : 60, 18 : 89, 27 :78, 30 : 68}

print( "Student_marks[56] : ", Student_marks[56] )

print( "Student_marks[12] : ", Student_marks[12] )

print( "Student_marks[27] : ", Student_marks[27] )

# update the value in dictionary with key

In this blog, we will discuss the Hash table in Python.

Hash table in Python

In the world of Capture The Flag (CTF) competitions, participants encounter various challenges that test their skills and knowledge in cybersecurity. One such challenge is type juggling, a technique used to manipulate data types and exploit vulnerabilities. This blog explores the concept of CTF type juggling and its association with RIPEMD160 hash, highlighting the power of this cryptographic algorithm in securing data integrity.

CTF type juggling is an intriguing technique used to exploit weakly typed programming languages. These languages allow for flexible data type conversions, which can lead to unintended consequences if not handled carefully. In CTF challenges, attackers may attempt to manipulate data types, such as converting strings to integers or performing arithmetic operations on strings. This manipulation can trick the program into executing unintended code paths or revealing sensitive information.

RIPEMD160 (RACE Integrity Primitives Evaluation Message Digest 160) is a cryptographic hash function known for its ability to produce a fixed-size hash value of 160 bits. It is widely used for data integrity verification and fingerprinting in various applications. Unlike encryption algorithms, hash functions are one-way functions, meaning it is computationally infeasible to retrieve the original data from its hash value.

The Power of RIPEMD160 in CTF Challenges:

In CTF challenges, RIPEMD160 hash can serve as a powerful tool for validating data integrity and ensuring secure communications. It provides a means to verify the authenticity and integrity of data by generating a unique hash value for each input. This property makes it suitable for scenarios where tampering or unauthorized modifications need to be detected.

CTF challenges may present scenarios where participants need to analyze and manipulate hash values. For example, they may be required to create a specific hash collision or reverse-engineer the original data from a given hash value. The robustness of RIPEMD160 in resisting collision attacks adds an extra layer of complexity to such challenges, making them both intellectually stimulating and demanding.

In the realm of Capture The Flag competitions, type juggling and RIPEMD160 hash play significant roles in assessing participants' abilities to exploit vulnerabilities and ensure data integrity. Type juggling allows for creative manipulation of data types, which can lead to unintended consequences if not handled with caution. On the other hand, RIPEMD160 hash provides a robust means of verifying data integrity and detecting unauthorized modifications. Both concepts showcase the diverse challenges and powerful tools that cybersecurity enthusiasts encounter in CTF competitions, pushing the boundaries of their knowledge and problem-solving skills.

Explore CTF type juggling and the power of RIPEMD160 hash in securing data integrity and manipulating vulnerabilities in cybersecurity challenges.

CTF Type Juggling and the Power of RIPEMD160 Hash

I saw that Deterministic is one of the property of Hashing. So can we predict the data on which we performed hasing algo by checking the hash output value?

Eg. If me and my friend uses the same hashign algo on our individual data. And at some point we both got ABCD as hash output value. So in that We can get to know on each other on which data we are performing hashing, right?

Can we predict the data from the Hash value?

My information is that a hash code and checksum are similar matters - a numeric value, computed for a block of data, that is rather specific.

i.e. The probability of  blocks of data yielding the equal numeric hash/checksum fee is low enough that it can be left out for the purposes of the utility.

So do we have two words for the same thing, or are there important differences between hash codes and checksums?

A checksum (such as CRC32) is to prevent accidental changes. If one byte changes, the checksum changes. The checksum is not safe to protect against malicious changes: it is pretty easy to create a file with a particular checksum.

A hash function maps some data to other data. It is often used to speed up comparisons or create a hash table. Not all hash functions are secure and the hash does not necessarily changes when the data changes.

A cryptographic hash function (such as SHA1) is a checksum that is secure against malicious changes. It is pretty hard to create a file with a specific cryptographic hash.

To make things more complicated, cryptographic hash functions are sometimes simply referred to as hash functions.

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