AI Space

HTB
challenges
AI - ML
Abstract

You are assigned the important mission of locating and identifying the infamous space hacker. Your investigation begins by analyzing the data patterns and breach points identified in the latest cyber-attacks. Use the provided coordinates of the last known signal origins to narrow down his potential hideouts. Utilize advanced tracking algorithms to follow the digital footprint left by the hacker.

AI Space is a challenge designed by karamuz. It starts with a NumPy file, distance_matrix.npy. NumPy is a Python library to operate on multidimensional arrays, a.k.a. matrices.

Why use NumPy?

Python’s lists can be “heterogeneous”, meaning they can contain elements of dirrent types (integer, string, boolean, etc.), and are quite fast.

list = [4, "banana", TRUE]

data structure to store homogeneous multidimensional array, ndarray,

Reading distance_matrix.npy

import numpy as np
a = np.load("distance_matrix.npy")
a.shape

Your matrix has \(2\) dimensions

a.shape
a.dtype.name
a.size
type(a)

Each dimentsion countain \(1808\), (1808, 1808), of float64data points, so a size of 3268864.

print(a)