Stacs-ci - A set of modules to enable integration of STACS with commonly used CI / CD systems

Related tags

Deep Learningstacs-ci
Overview

Shield Shield Shield Shield Shield Shield




Static Token And Credential Scanner
CI Integrations

What is it?

STACS is a YARA powered static credential scanner which supports source code, binary file formats, analysis of nested archives, composable rule-sets and ignore lists, and SARIF reporting.

This repository contains a set of modules to enable integration of STACS with commonly used CI / CD systems. Currently, supported is:

  • Github Actions

    • Fails the build on unsuppressed findings.
    • Automatically annotates pull requests with findings.
    • Automatically loads suppressions from a stacs.ignore.json in the root of the repository.
  • Generic CI Systems

    • Fails the build on unsuppressed findings.
    • Outputs findings to the console in formatted plain-text.
    • Automatically loads suppressions from a stacs.ignore.json in the scan directory.

Github Actions

This Github action enables running STACS as a Github action. This can be used to identify credentials committed in both source code, or even credentials accidentally compiled into binary artifacts - such as Android APKs, Docker images, RPM packages, ZIP files, and more!

If run as part of a pull request, this action automatically annotates a pull request with findings to allow simplified review integrated with existing code-review processes. As this integration does not use the Github security events framework, no additional subscription to Github is required, even for private repositories!

This action can also be used as part of a release event. Allowing scanning of binaries before publishing to catch credentials which may have been accidentally generated or included as part of the build process.

Additionally, this action can 'fail the build' if any static tokens and credentials are detected.

Appearance

If STACS detects a static credential during a pull request, a review comment will be added to the line containing the static credential:

Github Comment of finding

The STACS Github integration will even check the pull request to see whether there is an existing comment for this finding, preventing multiple comments being added to the same pull request on subsequent commits.

If the credential is found inside of an archive, in a part of a file not modified by the pull request, then a regular comment will be added to the triggering pull request.

Inputs

scan-directory

An optional sub-directory to scan, relative to the repository root. This allows scanning to be limited to a specific directory under the repository root.

Defaults to the repository root.

fail-build

Defines whether this action should 'fail the build' if any static token or credentials are detected. This will take any suppressed / ignore listed entries into account, allowing consumers to ignore known false positives - such as test fixtures.

Defaults to true

Example Usage

The following example scans the currently checked out commit and adds review comments for findings to an associated pull-request (see "Permissions" section below). If the trigger was not a pull-request, findings will instead be printed to the console and STACS CI will exit with a non-zero status (100) if unsupressed findings were present.

uses: stacscan/[email protected]

The following example scans a sub-directory in the repository. In this example the binaries/ sub-directory contains binary objects, compiled for release by another step of a Github actions pipeline.

uses: stacscan/[email protected]
with:
    scan-directory: 'binaries/'

The following example disables 'failing the build' if there are findings which have not been ignored / suppressed.

uses: stacscan/[email protected]
with:
    fail-build: false

Permissions

Please be aware that in order to annotate pull requests with comments, the action must also be granted write permissions to pull-requests. This can be done by adding the following to the respective job in your Github actions pipeline.

permissions:
    contents: read         # Required to read the repository contents (checkout).
    pull-requests: write   # Required to annotate pull requests with comments.

This is only required if running in response to pull-request triggers.

Generic CI

This repository can be integrated with a number of common CI systems using the provided Docker image, or Python module.

The pre-built Docker image greatly simplifies this process and provides a mechanism to quickly execute a STACS scan against a given directory, print the results in an actionable manner, and signal to the CI system that the build should fail on findings.

Appearance

If STACS detects a static credential, a results block will be printed to the console with information required to identify its location:

Terminal output of findings

If the credential is found within an archive, STACS will print a file tree to allow quick identification of exactly where the credential is.

Basic

The simplest form of executing the Generic CI integration can be performed using the following Docker command from the directory to be scanned. Using this default configuration Docker will complete with a non-zero exit code if any unsuppressed findings are found:

docker run -it -v $(pwd):/mnt/stacs/input stacscan/stacs-ci:latest

To prevent a non-zero exit code on unsuppressed findings, such as for initial 'dry run' style operation, the following command can be run:

docker run -it -e FAIL_BUILD=false -v $(pwd):/mnt/stacs/input stacscan/stacs-ci:latest

Jenkins

To be added.

Circle CI

To be added.

Comments
  • [0.1.6] Update to the latest STACS container.

    [0.1.6] Update to the latest STACS container.

    Overview

    Upgrades to the latest STACS container. See the STACS release notes for the new version for a list of changes in this container. Only changes to STACS-CI will be included below.

    πŸ› οΈ New Features

    • N/A

    🍩 Improvements

    • N/A

    πŸ› Bug Fixes

    • N/A
    opened by darkarnium 2
  • [0.1.5] Update to the latest STACS container.

    [0.1.5] Update to the latest STACS container.

    Overview

    PLEASE NOTE: There is a potentially breaking change as part of this update, as the Stripe rule has been relocated under SaaS. This modifies its reference to now be CredentialSaaSStripeAPI. Any previously suppressed findings for this rule will need to be updated to reflect this new identifier.

    πŸ› οΈ New Features

    • Upgrade to the latest STACS rules, which includes new rules for
      • PyPI Token
      • Slack Token
        • User (xoxp-...)
        • Bot (xoxb-...)
      • NPM
        • authToken
        • password
      • PKCS#12 / PFX
      • DER format RSA keys.
        • Detects keys with exponents 3 / 65537, and modulous sizes 64 / 128 / 256 / 512 / 1024.

    🍩 Improvements

    • Minor changes to AWS rule.
    • Simplify matching criteria for a number of rules.

    πŸ› Bug Fixes

    • N/A
    opened by darkarnium 2
  • [0.1.4] Github annotation off-by-one bug fix.

    [0.1.4] Github annotation off-by-one bug fix.

    Overview

    πŸ› οΈ New Features

    • N/A

    🍩 Improvements

    • Pulls in latest STACS rules (r57ce3ce).

    πŸ› Bug Fixes

    • Fix off-by-one edge case which caused Github pull-request annotation to fail.
      • This was triggered when a new file was added in a pull-request containing a credential on the first line.
    opened by darkarnium 1
  • [0.1.3] Update to the latest version of STACS.

    [0.1.3] Update to the latest version of STACS.

    Overview

    πŸ› οΈ New Features

    🍩 Improvements

    • Tweak to STACS-CI deployment pipeline to simplify testing prior to release.

    πŸ› Bug Fixes

    • N/A
    opened by darkarnium 1
  • [0.1.1] Use latest STACS release, absolute URLs for images

    [0.1.1] Use latest STACS release, absolute URLs for images

    Overview

    πŸ› οΈ New Features

    🍩 Improvements

    • N/A

    πŸ› Bug Fixes

    • Ensures that file with the finding appears in the change set.
      • This prevents attempts to add a review comment for a file which is already in the target branch.
      • In these cases a comment will be added instead.
    opened by darkarnium 1
  • [0.1.0] Change container tag format, add Action.

    [0.1.0] Change container tag format, add Action.

    Overview

    Unfortunately, Docker does not support + characters in tag names, so we cannot use semver package numbering to indicate rule version.

    πŸ› οΈ New Features

    • Add Github Action YAML.
    • Update STACS Rules on STACS CI release.

    🍩 Improvements

    • N/A

    πŸ› Bug Fixes

    • N/A
    opened by darkarnium 0
  • [0.1.0] Initial implementation of STACS CI

    [0.1.0] Initial implementation of STACS CI

    Overview

    Initial release of STACS CI Integrations.

    πŸ› οΈ New Features

    • Generic CI integration
    • Github Actions integration

    🍩 Improvements

    • N/A

    πŸ› Bug Fixes

    • N/A
    opened by darkarnium 0
  • Backport CI UI into STACS

    Backport CI UI into STACS

    Overview

    The STACS-CI UI should be moved back into STACS, removing th need for this repository to contain more than a Github action for STACS execution.

    opened by darkarnium 0
  • Documentation of the stacs.ignore.json

    Documentation of the stacs.ignore.json

    Hi!

    Great tool you are building here - happy with it working so well in a CI context and ease of config.

    I have searched a lot through your repos and am struggling to find docs on the ignore file? Some of the things you describe sound awesome but I am yet to find anything on how to do it :)

    Thanks in advance!

    documentation 
    opened by erzz 5
Releases(0.1.6)
  • 0.1.6(Mar 4, 2022)

    Overview

    Upgrades to the latest STACS container. See the STACS release notes for the new version for a list of changes in this container. Only changes to STACS-CI will be included below.

    πŸ› οΈ New Features

    • N/A

    🍩 Improvements

    • N/A

    πŸ› Bug Fixes

    • N/A
    Source code(tar.gz)
    Source code(zip)
  • 0.1.5(Jan 18, 2022)

    Overview

    PLEASE NOTE: There is a potentially breaking change as part of this update, as the Stripe rule has been relocated under SaaS. This modifies its reference to now be CredentialSaaSStripeAPI. Any previously suppressed findings for this rule will need to be updated to reflect this new identifier.

    πŸ› οΈ New Features

    • Upgrade to the latest STACS rules, which includes new rules for
      • PyPI Token
      • Slack Token
        • User (xoxp-...)
        • Bot (xoxb-...)
      • NPM
        • authToken
        • password
      • PKCS#12 / PFX
      • DER format RSA keys.
        • Detects keys with exponents 3 / 65537, and modulous sizes 64 / 128 / 256 / 512 / 1024.

    🍩 Improvements

    • Minor changes to AWS rule.
    • Simplify matching criteria for a number of rules.

    πŸ› Bug Fixes

    • N/A
    Source code(tar.gz)
    Source code(zip)
  • 0.1.4(Jan 11, 2022)

    Overview

    πŸ› οΈ New Features

    • N/A

    🍩 Improvements

    • Pulls in latest STACS rules (r57ce3ce).

    πŸ› Bug Fixes

    • Fix off-by-one edge case which caused Github pull-request annotation to fail.
      • This was triggered when a new file was added in a pull-request containing a credential on the first line.
    Source code(tar.gz)
    Source code(zip)
  • 0.1.3(Jan 10, 2022)

    Overview

    πŸ› οΈ New Features

    🍩 Improvements

    • Tweak to STACS-CI deployment pipeline to simplify testing prior to release.

    πŸ› Bug Fixes

    • N/A
    Source code(tar.gz)
    Source code(zip)
  • 0.1.2(Jan 7, 2022)

  • 0.1.1(Jan 4, 2022)

    Overview

    πŸ› οΈ New Features

    🍩 Improvements

    • N/A

    πŸ› Bug Fixes

    • Ensures that file with the finding appears in the change set.
      • This prevents attempts to add a review comment for a file which is already in the target branch.
      • In these cases a comment will be added instead.
    Source code(tar.gz)
    Source code(zip)
  • 0.1.0(Jan 2, 2022)

    Overview

    Initial release of STACS CI Integrations.

    πŸ› οΈ New Features

    • Github Actions

      • Fails the build on unsuppressed findings.
      • Automatically annotates pull requests with findings.
      • Automatically loads suppressions from a stacs.ignore.json in the root of the repository.
    • Generic CI Systems

      • Fails the build on unsuppressed findings.
      • Outputs findings to the console in formatted plain-text.
      • Automatically loads suppressions from a stacs.ignore.json in the scan directory.

    🍩 Improvements

    • N/A

    πŸ› Bug Fixes

    • N/A
    Source code(tar.gz)
    Source code(zip)
Owner
STACS
Static Token And Credential Scanner
STACS
γ€ŠDeep Single Portrait Image Relighting》(ICCV 2019)

Ratio Image Based Rendering for Deep Single-Image Portrait Relighting [Project Page] This is part of the Deep Portrait Relighting project. If you find

62 Dec 21, 2022
FNet Implementation with TensorFlow & PyTorch

FNet Implementation with TensorFlow & PyTorch. TensorFlow & PyTorch implementation of the paper "FNet: Mixing Tokens with Fourier Transforms". Overvie

Abdelghani Belgaid 1 Feb 12, 2022
[RSS 2021] An End-to-End Differentiable Framework for Contact-Aware Robot Design

DiffHand This repository contains the implementation for the paper An End-to-End Differentiable Framework for Contact-Aware Robot Design (RSS 2021). I

Jie Xu 60 Jan 04, 2023
Blender Add-on that sets a Material's Base Color to one of Pantone's Colors of the Year

Blender PCOY (Pantone Color of the Year) MCMC (Mid-Century Modern Colors) HG71 (House & Garden Colors 1971) Blender Add-ons That Assign a Custom Color

Don Schnitzius 15 Nov 20, 2022
PyTea: PyTorch Tensor shape error analyzer

PyTea: PyTorch Tensor Shape Error Analyzer paper project page Requirements node.js = 12.x python = 3.8 z3-solver = 4.8 How to install and use # ins

ROPAS Lab. 240 Jan 02, 2023
A state of the art of new lightweight YOLO model implemented by TensorFlow 2.

CSL-YOLO: A New Lightweight Object Detection System for Edge Computing This project provides a SOTA level lightweight YOLO called "Cross-Stage Lightwe

Miles Zhang 54 Dec 21, 2022
Learn other languages ​​using artificial intelligence with python.

The main idea of ​​the project is to facilitate the learning of other languages. We created a simple AI that will interact with you. Just ask questions that if she knows, she will answer.

Pedro Rodrigues 2 Jun 07, 2022
Stacked Recurrent Hourglass Network for Stereo Matching

SRH-Net: Stacked Recurrent Hourglass Introduction This repository is supplementary material of our RA-L submission, which helps reviewers to understan

28 Jan 03, 2023
Project code for weakly supervised 3D object detectors using wide-baseline multi-view traffic camera data: WIBAM.

WIBAM (Work in progress) Weakly Supervised Training of Monocular 3D Object Detectors Using Wide Baseline Multi-view Traffic Camera Data 3D object dete

Matthew Howe 10 Aug 24, 2022
PyTorch Live is an easy to use library of tools for creating on-device ML demos on Android and iOS.

PyTorch Live is an easy to use library of tools for creating on-device ML demos on Android and iOS. With Live, you can build a working mobile app ML demo in minutes.

559 Jan 01, 2023
Contains supplementary materials for reproduce results in HMC divergence time estimation manuscript

Scalable Bayesian divergence time estimation with ratio transformations This repository contains the instructions and files to reproduce the analyses

Suchard Research Group 1 Sep 21, 2022
Exploiting Robust Unsupervised Video Person Re-identification

Exploiting Robust Unsupervised Video Person Re-identification Implementation of the proposed uPMnet. For the preprint, please refer to [Arxiv]. Gettin

1 Apr 09, 2022
Hierarchical Metadata-Aware Document Categorization under Weak Supervision (WSDM'21)

Hierarchical Metadata-Aware Document Categorization under Weak Supervision This project provides a weakly supervised framework for hierarchical metada

Yu Zhang 53 Sep 17, 2022
[Machine Learning Engineer Basic Guide] λΆ€μŠ€νŠΈμΊ ν”„ AI Tech - Product Serving 자료

Boostcamp-AI-Tech-Product-Serving λΆ€μŠ€νŠΈμΊ ν”„ AI Tech - Product Serving 자료 Repository ꡬ쑰 part1(MLOps 개둠, Model Serving, λ¨Έμ‹ λŸ¬λ‹ ν”„λ‘œμ νŠΈ 라이프 사이클은 λ³„λ„μ˜ μ½”λ“œκ°€ μ—†μœΌλ©°, part

Sung Yun Byeon 269 Dec 21, 2022
Label-Free Model Evaluation with Semi-Structured Dataset Representations

Label-Free Model Evaluation with Semi-Structured Dataset Representations Prerequisites This code uses the following libraries Python 3.7 NumPy PyTorch

8 Oct 06, 2022
Pytorch implementation of the paper "COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking."

Expert-Linking Pytorch implementation of the paper "COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking." This is

BoChen 12 Jan 01, 2023
Roach: End-to-End Urban Driving by Imitating a Reinforcement Learning Coach

CARLA-Roach This is the official code release of the paper End-to-End Urban Driving by Imitating a Reinforcement Learning Coach by Zhejun Zhang, Alexa

Zhejun Zhang 118 Dec 28, 2022
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a

Microsoft 14.5k Jan 08, 2023
A lightweight deep network for fast and accurate optical flow estimation.

FastFlowNet: A Lightweight Network for Fast Optical Flow Estimation The official PyTorch implementation of FastFlowNet (ICRA 2021). Authors: Lingtong

Tone 161 Jan 03, 2023
Continuous Diffusion Graph Neural Network

We present Graph Neural Diffusion (GRAND) that approaches deep learning on graphs as a continuous diffusion process and treats Graph Neural Networks (GNNs) as discretisations of an underlying PDE.

Twitter Research 227 Jan 05, 2023