Skip to main content

PHT train container library

Project description

Documentation Status CodeQL main-ci codecov PyPI version

Train Container Library

Python library for validating and interacting with pht-train images/containers.

Installation

pip install pht-train-container-library

Security Protocol

The pht security protocol adapted from docs/Secure_PHT_latest__official.pdf performs two main tasks:

  1. Before executing a train-image on the local machine, unless the station is the first station on the route, the previous results need to be decrypted and the content of the image needs to be validated based on the configuration of the individual train -> pre-run.
  2. After executing the train the updated results need to be encrypted and the train configuration needs to be updated to reflect the current state ->post-run.

To function the protocol expects two environment variables to be set:

  1. STATION_ID String identifier that has public key/s registered with the central service
  2. RSA_STATON_PRIVATE_KEY Hex string containing the private key to be used for decryption and signing.

Pre-run protocol

The pre-run protocol consists of the following steps

  1. The hash of the immutable files (train definition) is verified making sure that the executable files did not change during the the train definition.
  2. The digital signature is verified ensuring the correctness of the results at each stop of the train.
  3. The symmetric key is decrypted using the provided station private key
  4. The mutable files in /opt/pht_results are decrypted using the symmetric key obtained in the previous step
  5. The decrypted files are hashed and the hash is compared to the one stored in the train configuration file.

Once these steps have been completed the image is ready to be executed.

Post-run protocol

  1. Calculate the hash of the newly generated results
  2. Sign the hash of the results using the provided RSA_STATION_PRIVATE_KEY
  3. Update the the train signature using the session id that is randomly generated at each execution step
  4. Encrypt the resulting files using a newly generated symmetric key
  5. Encrypt the generated symmetric key with the public keys of the train participants
  6. Update the train configuration file

With the completion of these steps the train is ready to be pushed into the registry for further processing

Tests

Run the tests to validate the security protocol is working as intended. From this projects root directory run pytest train_lib

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pht-train-container-library-1.0.2.tar.gz (37.3 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file pht-train-container-library-1.0.2.tar.gz.

File metadata

  • Download URL: pht-train-container-library-1.0.2.tar.gz
  • Upload date:
  • Size: 37.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.5

File hashes

Hashes for pht-train-container-library-1.0.2.tar.gz
Algorithm Hash digest
SHA256 c4ac6018bc240b8bd5fb3d8c230687ea2127c7f69b58fe79a3f9a758d6daed42
MD5 008b2008bff6e8ea7cfb6a1b4d67a248
BLAKE2b-256 b03f05f3f4eee5755db66cd5504f8287415ecb4ee5efe6bcf1869ef1aed941b7

See more details on using hashes here.

File details

Details for the file pht_train_container_library-1.0.2-py3-none-any.whl.

File metadata

  • Download URL: pht_train_container_library-1.0.2-py3-none-any.whl
  • Upload date:
  • Size: 45.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.5

File hashes

Hashes for pht_train_container_library-1.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 f796fec5e2575b5292f0bc5d39788b7d4f75940c0bc5117e1da54a2faf4ae5ab
MD5 2e14b48cd809b6ff3c7832cd8d000e8a
BLAKE2b-256 e9f0c4bacf79a34d7dc42b0f7df7d9f296cc2e37fa233a3f8003e9e236563485

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page