vhxs

#include <stdio.h>

int main(void) {
    int input;
    scanf("%d", &input);
    printf("%s", __builtin_popcount(input));
}

vhxs

FROM python:3.10-slim

WORKDIR /app

COPY poetry.lock /app/poetry.lock
COPY pyproject.toml /app/pyproject.toml
COPY example.py /app/example.py

RUN apt-get update && \
    apt-get install -y --no-install-recommends gcc curl gnupg2 wget && \

vhxs

This writeup outlines a solution for Locking Mechanism and also my thought process in solving it. This was my first time doing a CTF and my very first solve ever.

We're given a Dockerized Rust application, but I decided to build the code directly on my machine since I already had Cargo installed and up to date. I'm not that well-versed in Rust yet (I solved a few Advent of Code problems in it), but I know enough to poke around. The first thing I tried was to just cargo build and cargo run the application and see what happens. It didn't halt, so upon looking at the code it looked like it was expecting an input of comma-separated integers.

In the file I noticed that there was a list of 104 integers, particularly this:

vhxs

#include <Arduino.h>

struct BCD {
  int eights;
  int fours;
  int twos;
  int ones;
};

struct BCD decimal_to_BCD(int value) {

vhxs

import random

import networkx as nx


def random_graph() -> nx.Graph:
    num_nodes = 20
    probability = 0.2

    return nx.erdos_renyi_graph(num_nodes, probability)

vhxs

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("t5-base")
model = AutoModelForSeq2SeqLM.from_pretrained("t5-base")

example_input = "This sentence is false"
input_ids = tokenizer("translate English to German: "+example_input, return_tensors="pt").input_ids
outputs = model.generate(input_ids)
decoded = tokenizer.decode(outputs[0], skip_special_tokens=True)

vhxs

import requests
import os
from datetime import datetime, timezone

# Fetch the current time
# Using a trailing "Z" is preferred over the "+00:00" format
now = datetime.now(timezone.utc).isoformat().replace("+00:00", "Z")

# Required fields that each post must include
post = {

vhxs

import os
import torch
import torch.nn as nn
import torch.optim as optim
import torchvision.models as models
import torchvision.transforms as transforms
import torchvision.datasets as datasets

# Load pre-trained ResNet-18
model = models.resnet18(pretrained=True)

vhxs

import pygame

# Initialize Pygame
pygame.init()

# Set up display
width, height = 800, 600
screen = pygame.display.set_mode((width, height))
pygame.display.set_caption("Pygame Glide Transformation Animation")

vhxs

from langchain.document_loaders import OnlinePDFLoader
from langchain.indexes import VectorstoreIndexCreator

loader = OnlinePDFLoader("https://arxiv.org/pdf/1606.06353.pdf")
documents = loader.load()
index = VectorstoreIndexCreator().from_documents(documents)

print(index.query("What are the main results of this paper?"))