Mscp jamf - Build compliance in jamf

Overview

mscp_jamf

Build compliance in Jamf.

This will build the following xml pieces to be used by Jamf:

  • Categories (Section within baseline file)
  • Extension Attributes (the check within the mSCP project rule)
  • Scripts (the fix withn the mSCP project rule)
  • Smart Groups (passed and failed)
  • Policy scoped to failed with passed set as exempted.

Built for use with the macOS Security Compliance Project (https://github.com/usnistgov/macos_security)

Drop the generate_jamf.py script in the scripts directory within the project folders.

Then when running generate_jamf.py use the -j to generate the pieces for jamf and the -p to generate profiles.

Use the build_jamf.py script to upload the pieces built by the generate_jamf.py script. This will not upload the configuration profiles however, as Jamf will modify the contents which can cause issues.

Owner
Bob Gendler
Amateur hour Swifter. Jamf Pro Professional. And scripter of AppleScript, Python, and Bash.
Bob Gendler
Planning from Pixels in Environments with Combinatorially Hard Search Spaces -- NeurIPS 2021

PPGS: Planning from Pixels in Environments with Combinatorially Hard Search Spaces Environment Setup We recommend pipenv for creating and managing vir

Autonomous Learning Group 11 Jun 26, 2022
This is the pytorch implementation for the paper: *Learning Accurate Performance Predictors for Ultrafast Automated Model Compression*, which is in submission to TPAMI

SeerNet This is the pytorch implementation for the paper: Learning Accurate Performance Predictors for Ultrafast Automated Model Compression, which is

3 May 01, 2022
DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021)

Evaluation, Training, Demo, and Inference of DeFMO DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021) Denys Rozumnyi, Martin R. O

Denys Rozumnyi 139 Dec 26, 2022
A python library to build Model Trees with Linear Models at the leaves.

A python library to build Model Trees with Linear Models at the leaves.

Marco Cerliani 212 Dec 30, 2022
PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)

PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)

Yonglong Tian 2.2k Jan 08, 2023
Pytorch reimplementation of the Vision Transformer (An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale)

Vision Transformer Pytorch reimplementation of Google's repository for the ViT model that was released with the paper An Image is Worth 16x16 Words: T

Eunkwang Jeon 1.4k Dec 28, 2022
As-ViT: Auto-scaling Vision Transformers without Training

As-ViT: Auto-scaling Vision Transformers without Training [PDF] Wuyang Chen, Wei Huang, Xianzhi Du, Xiaodan Song, Zhangyang Wang, Denny Zhou In ICLR 2

VITA 68 Sep 05, 2022
Co-GAIL: Learning Diverse Strategies for Human-Robot Collaboration

CoGAIL Table of Content Overview Installation Dataset Training Evaluation Trained Checkpoints Acknowledgement Citations License Overview This reposito

Jeremy Wang 29 Dec 24, 2022
ML From Scratch

ML from Scratch MACHINE LEARNING TOPICS COVERED - FROM SCRATCH Linear Regression Logistic Regression K Means Clustering K Nearest Neighbours Decision

Tanishq Gautam 66 Nov 02, 2022
Graph Analysis From Scratch

Graph Analysis From Scratch Goal In this notebook we wanted to implement some functionalities to analyze a weighted graph only by using algorithms imp

Arturo Ghinassi 0 Sep 17, 2022
Code for "Contextual Non-Local Alignment over Full-Scale Representation for Text-Based Person Search"

Contextual Non-Local Alignment over Full-Scale Representation for Text-Based Person Search This is an implementation for our paper Contextual Non-Loca

Tencent YouTu Research 50 Dec 03, 2022
Changing the Mind of Transformers for Topically-Controllable Language Generation

We will first introduce the how to run the IPython notebook demo by downloading our pretrained models. Then, we will introduce how to run our training and evaluation code.

IESL 20 Dec 06, 2022
Credit fraud detection in Python using a Jupyter Notebook

Credit-Fraud-Detection - Credit fraud detection in Python using a Jupyter Notebook , using three classification models (Random Forest, Gaussian Naive Bayes, Logistic Regression) from the sklearn libr

Ali Akram 4 Dec 28, 2021
Command-line tool for downloading and extending the RedCaps dataset.

RedCaps Downloader This repository provides the official command-line tool for downloading and extending the RedCaps dataset. Users can seamlessly dow

RedCaps dataset 33 Dec 14, 2022
Implementation of DropLoss for Long-Tail Instance Segmentation in Pytorch

[AAAI 2021]DropLoss for Long-Tail Instance Segmentation [AAAI 2021] DropLoss for Long-Tail Instance Segmentation Ting-I Hsieh*, Esther Robb*, Hwann-Tz

Tim 37 Dec 02, 2022
A Collection of Papers and Codes for ICCV2021 Low Level Vision and Image Generation

A Collection of Papers and Codes for ICCV2021 Low Level Vision and Image Generation

196 Jan 05, 2023
Keras like implementation of Deep Learning architectures from scratch using numpy.

Mini-Keras Keras like implementation of Deep Learning architectures from scratch using numpy. How to contribute? The project contains implementations

MANU S PILLAI 5 Oct 10, 2021
This repository contains all data used for writing a research paper Multiple Object Trackers in OpenCV: A Benchmark, presented in ISIE 2021 conference in Kyoto, Japan.

OpenCV-Multiple-Object-Tracking Python is version 3.6.7 to install opencv: pip uninstall opecv-python pip uninstall opencv-contrib-python pip install

6 Dec 19, 2021
Controlling Hill Climb Racing with Hand Tacking

Controlling Hill Climb Racing with Hand Tacking Opened Palm for Gas Closed Palm for Brake

Rohit Ingole 3 Jan 18, 2022
Pytorch library for end-to-end transformer models training and serving

Pytorch library for end-to-end transformer models training and serving

Mikhail Grankin 768 Jan 01, 2023