README.md

---
license: cc-by-4.0
configs:
- config_name: 1024-unrolled
  data_files:
  - split: train
    path: 1024-unrolled/*train*.tar
  - split: valid
    path: 1024-unrolled/*valid*.tar
  - split: test
    path: 1024-unrolled/*test*.tar
- config_name: 2048-unrolled
  data_files:
  - split: train
    path: 2048-unrolled/*train*.tar
  - split: valid
    path: 2048-unrolled/*valid*.tar
  - split: test
    path: 2048-unrolled/*test*.tar
- config_name: 4096-unrolled_n
  data_files:
  - split: train
    path: 4096-unrolled_n/*train*.tar
  - split: valid
    path: 4096-unrolled_n/*valid*.tar
  - split: test
    path: 4096-unrolled_n/*test*.tar
task_categories:
- image-classification
- image-segmentation
size_categories:
- 1K<n<10K
---

# COSOCO: Compromised Software Containers Image Dataset

COSOCO (Compromised Software Containers) is a synthetic dataset of 3364 images representing benign
and malware-compromised software containers. Each image in the dataset represents a dockerized 
software container that has been converted to an image using common byte-to-pixel tools widely used
in malware analysis. Software container records are labelled (1) **benign** or (2) **compromised**: 
A benign software container will have installed commonly used harmless packages and tools, whereas 
a compromised software container, will have, among harmless benign tools and packages, its underlying
file system affected by some activated malware instance. Each compromised instance is accompanied by 
a mask, i.e. a black and white image which marks the pixels that correspond to the files of the 
underlying system that have been altered by a malware.

COSOCO aims to support the identification of compromised software containers via the task of image 
classification task and the identification of compromised files and file system regions inside a 
container via the image segmentation task.