diffy | triage tool used during cloud-centric security incidents | Cybersecurity library

 by   Netflix-Skunkworks Python Version: 0.1.0 License: Apache-2.0

kandi X-RAY | diffy Summary

kandi X-RAY | diffy Summary

diffy is a Python library typically used in Security, Cybersecurity applications. diffy has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install diffy' or download it from GitHub, PyPI.

Diffy is a triage tool used during cloud-centric security incidents, to help digital forensics and incident response (DFIR) teams quickly identify suspicious hosts on which to focus their response.
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            kandi-support Support

              diffy has a low active ecosystem.
              It has 631 star(s) with 62 fork(s). There are 138 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 8 open issues and 9 have been closed. On average issues are closed in 51 days. There are 4 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of diffy is 0.1.0

            kandi-Quality Quality

              diffy has 0 bugs and 21 code smells.

            kandi-Security Security

              diffy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              diffy code analysis shows 0 unresolved vulnerabilities.
              There are 4 security hotspots that need review.

            kandi-License License

              diffy is licensed under the Apache-2.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              diffy releases are not available. You will need to build from source code and install.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              diffy saves you 877 person hours of effort in developing the same functionality from scratch.
              It has 2006 lines of code, 191 functions and 66 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed diffy and discovered the below as its top functions. This is intended to give you an instant insight into diffy implemented functionality, and help decide if they suit your requirements.
            • Validate a request against a schema
            • Unwraps pagination data
            • Format errors in a dictionary
            • Wrap validation errors
            • Create a baseline
            • Gets the baseline data for the given target
            • Update the class list
            • Return a list of all registered plugins
            • Create a Flask application
            • Configure Flask hooks
            • Consume environment variables
            • Load a configuration variable from an environment variable
            • Execute analysis
            • Returns the first plugin that matches the given func_name
            • Adds plugin arguments to click Command
            • Fetch instances from Auto Scaling Group
            • Get plugin by slug
            • Query instances
            • Consume os environ
            • Main entry point
            • Validate account identifier
            • Read persistent data
            • Check if moto is broken
            • Save persistent data to persistent storage
            • Validate data
            • Create an asynchronous analysis
            • Save a file to S3
            Get all kandi verified functions for this library.

            diffy Key Features

            No Key Features are available at this moment for diffy.

            diffy Examples and Code Snippets

            No Code Snippets are available at this moment for diffy.

            Community Discussions

            QUESTION

            Why does unet have classes?
            Asked 2021-Jun-11 at 09:42
            import torch
            import torch.nn as nn
            import torch.nn.functional as F
            
            
            class double_conv(nn.Module):
                '''(conv => BN => ReLU) * 2'''
                def __init__(self, in_ch, out_ch):
                    super(double_conv, self).__init__()
                    self.conv = nn.Sequential(
                        nn.Conv2d(in_ch, out_ch, 3, padding=1),
                        nn.BatchNorm2d(out_ch),
                        nn.ReLU(inplace=True),
                        nn.Conv2d(out_ch, out_ch, 3, padding=1),
                        nn.BatchNorm2d(out_ch),
                        nn.ReLU(inplace=True)
                    )
            
                def forward(self, x):
                    x = self.conv(x)
                    return x
            
            
            class inconv(nn.Module):
                def __init__(self, in_ch, out_ch):
                    super(inconv, self).__init__()
                    self.conv = double_conv(in_ch, out_ch)
            
                def forward(self, x):
                    x = self.conv(x)
                    return x
            
            
            class down(nn.Module):
                def __init__(self, in_ch, out_ch):
                    super(down, self).__init__()
                    self.mpconv = nn.Sequential(
                        nn.MaxPool2d(2),
                        double_conv(in_ch, out_ch)
                    )
            
                def forward(self, x):
                    x = self.mpconv(x)
                    return x
            
            
            class up(nn.Module):
                def __init__(self, in_ch, out_ch, bilinear=True):
                    super(up, self).__init__()
            
                    #  would be a nice idea if the upsampling could be learned too,
                    #  but my machine do not have enough memory to handle all those weights
                    if bilinear:
                        self.up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=True)
                    else:
                        self.up = nn.ConvTranspose2d(in_ch//2, in_ch//2, 2, stride=2)
            
                    self.conv = double_conv(in_ch, out_ch)
            
                def forward(self, x1, x2):
                    x1 = self.up(x1)
                    diffX = x1.size()[2] - x2.size()[2]
                    diffY = x1.size()[3] - x2.size()[3]
                    x2 = F.pad(x2, (diffX // 2, int(diffX / 2),
                                    diffY // 2, int(diffY / 2)))
                    x = torch.cat([x2, x1], dim=1)
                    x = self.conv(x)
                    return x
            
            
            class outconv(nn.Module):
                def __init__(self, in_ch, out_ch):
                    super(outconv, self).__init__()
                    self.conv = nn.Conv2d(in_ch, out_ch, 1)
            
                def forward(self, x):
                    x = self.conv(x)
                    return x
            
            
            class UNet(nn.Module):
                def __init__(self, n_channels, n_classes):
                    super(UNet, self).__init__()
                    self.inc = inconv(n_channels, 64)
                    self.down1 = down(64, 128)
                    self.down2 = down(128, 256)
                    self.down3 = down(256, 512)
                    self.down4 = down(512, 512)
                    self.up1 = up(1024, 256)
                    self.up2 = up(512, 128)
                    self.up3 = up(256, 64)
                    self.up4 = up(128, 64)
                    self.outc = outconv(64, n_classes)
            
                def forward(self, x):
                    self.x1 = self.inc(x)
                    self.x2 = self.down1(self.x1)
                    self.x3 = self.down2(self.x2)
                    self.x4 = self.down3(self.x3)
                    self.x5 = self.down4(self.x4)
                    self.x6 = self.up1(self.x5, self.x4)
                    self.x7 = self.up2(self.x6, self.x3)
                    self.x8 = self.up3(self.x7, self.x2)
                    self.x9 = self.up4(self.x8, self.x1)
                    self.y = self.outc(self.x9)
                    return self.y
            
            ...

            ANSWER

            Answered 2021-Jun-11 at 09:42
            Answer

            Does n_classes signify multiclass segmentation?

            Yes, if you specify n_classes=4 it will output a (batch, 4, width, height) shaped tensor, where each pixel can be segmented as one of 4 classes. Also one should use torch.nn.CrossEntropyLoss for training.

            If so, what is the output of binary UNet segmentation?

            If you want to use binary segmentation you'd specify n_classes=1 (either 0 for black or 1 for white) and use torch.nn.BCEWithLogitsLoss

            I am trying to use this code for image denoising and I couldn't figure out what will should the n_classes parameter be

            It should be equal to n_channels, usually 3 for RGB or 1 for grayscale. If you want to teach this model to denoise an image you should:

            • Add some noise to the image (e.g. using torchvision.transforms)
            • Use sigmoid activation at the end as the pixels will have value between 0 and 1 (unless normalized)
            • Use torch.nn.MSELoss for training
            Why sigmoid?

            Because [0,255] pixel range is represented as [0, 1] pixel value (without normalization at least). sigmoid does exactly that - squashes value into [0, 1] range, hence linear outputs (logits) can have a range from -inf to +inf.

            Why not a linear output and a clamp?

            In order for the Linear layer to be in [0, 1] range after clamp possible output values from Linear would have to be greater than 0 (logits range to fit the target: [0, +inf])

            Why not a linear output without a clamp?

            Logits outputted would have to be within [0, 1] range

            Why not some other method?

            You could do that, but the idea of sigmoid is:

            • help neural network (any logit value can be outputted)
            • first derivative of sigmoid is gaussian standard normal, hence it models the probability of many real-life occurring phenomena (see also here for more)

            Source https://stackoverflow.com/questions/67932624

            QUESTION

            How to prevent ghost movement when dragging camera in Unity?
            Asked 2021-May-06 at 13:01

            I have the below script attached to my main camera. Its for a VR app. The script allows me to rotate the camera when pressing down on the mouse button.

            The script works but the problem is, while I have the mouse button pressed down the view slightly keeps rotating towards the left. When I release the mouse button the movement stops.

            I cant find the cause of this "ghost" movement

            ...

            ANSWER

            Answered 2021-May-06 at 13:01

            QUESTION

            Composition in JS
            Asked 2021-Mar-30 at 06:59

            I am learning the concepts of Composition in JS. Below is my demo code.

            The moveBy function assigns the values correctly to x and y.

            However, the setFillColor function does not assign the passed value to fillColor.

            What exactly is happening when the setFillColor function is called?

            ...

            ANSWER

            Answered 2021-Mar-29 at 14:30

            The problem stems from this assignment in createShape - annotations by me:

            Source https://stackoverflow.com/questions/66855754

            QUESTION

            How to get an angle by using tangent in javascript?
            Asked 2021-Feb-21 at 16:07

            The red circle is at a known angle of 130°, then I want to draw the navy line from the center to 130° using x and y of the red circle but it looks like I missed the calculation.

            Currently, the angle of the Navy line is a reflection to the angle of the red line and if I add minus sign ➖ to *diffX * at line13, it'll work as expected but Why do I need to do that by myself, why can't the Calculations at line 10 and 13 figured out if x should be minus ➖ or plus.

            I couldn't figure out where I was wrong..any help/suggestions are appreciated!

            ...

            ANSWER

            Answered 2021-Feb-21 at 16:07

            Seems you are using too much minuses.

            At first, you define angle -130 degrees, close to -3Pi/4. Cosine and sine values for this angle are about -0.7, using hypothenus = 100, we get x =W/2-70, y = H/2-70

            Source https://stackoverflow.com/questions/66299704

            QUESTION

            Changing to another View Controller after the launch screen animation in swift
            Asked 2020-Dec-31 at 13:41

            I am new to iOS Development and I want to build some workout app and want to have some zoom-in animation after launching the app. I searched for it on the internet and found some YouTube video, where I saw how to do the animation immediately after launching the app. So I wrote down the code, that was presented in the video. So in the ViewController.swift I got imageView variable, which is the logo. And in ViewController.swift my code looks like this:

            ...

            ANSWER

            Answered 2020-Dec-31 at 13:41

            welcome to stackOverflow. The problem is that you are not grabbing the correct instance of HomeViewController. By doing let viewController = HomeViewController() you are creating a new one rather than grabbing the instance you created in the storyboard.

            Change that line to

            Source https://stackoverflow.com/questions/65521235

            QUESTION

            Swipe detection and Touch listener not working inside fragment
            Asked 2020-Nov-27 at 07:31

            App has bottom navigation menus and fragments. This is the fragment which requires swipe detection similar to Tinder:

            ...

            ANSWER

            Answered 2020-Nov-27 at 07:31

            In Android, a gesture is defined as the beginning of ACTION_DOWN and ending with ACTION_UP. If you want your view to receive a gesture, you MUST return true for ACTION_DOWN, otherwise, you will got nothing.

            Root cause

            Source https://stackoverflow.com/questions/65022347

            QUESTION

            My Strings are not showing when game is clicked
            Asked 2020-Nov-23 at 22:36
            
                    Find the buried treasure!
                    
            
                    

            ...

            ANSWER

            Answered 2020-Nov-23 at 22:36

            As you say the code seems to work - I copied into the snippet below which you can run here. I added some console logging to see what was going on. The only change I made was to the width & height vars which were both set at 800 when in fact the image is 400 x 400. Maybe that was your issue. Otherwise it appears to work.

            You might want to consider breaking the image into a grid of squares, say 20x20px. Then maybe mark where the player clicked already with a semi-transparent div.

            Source https://stackoverflow.com/questions/64971214

            QUESTION

            2d gravity simulator - smaller object orbiting towards center of bigger object
            Asked 2020-Nov-22 at 16:47

            In my libgdx test game, I have initially created 2 circle objects (stellar) about which I will say more in details below. However, my goal is to simulate gravity in 2d, where smaller object orbits towards center of bigger object (just like earth orbits sun) but closer and closer to the center of bigger.

            So, I have created the following:

            • stellar1: smaller, 10px radius, 10 mass, dynamic (can move), initial position -160x90, velocity (0,0), accelerator (0,0)
            • stellar2: bigger, 30px radius, 30 mass, static (cannot move), initial position 0x0, velocity (0,0), accelerator (0,0)

            Here is also a screenshot, just to have a picture:

            I will give the full code below of what I did so far, before that I want to mention I have 2 approaches, StellarTest1 and StellarTest2.

            First StellarTest1, I've tried to add some extra values like 1000f to both x and y just to see something in action like:

            ...

            ANSWER

            Answered 2020-Nov-22 at 16:47

            Your update approach in StellarTest1 looks conceptually fine to me (I assume this 1000f factor is way to adjust the gravitational constant/mass of the bigger body). However, of you want some extra decay of the orbit, you need to add some fictitious velocity-dependent drag term to the acceleration. There is no need of StellarTest2, because you should get a comparable results while the calculation of cos and sin is slower and expensive, while the same components in StellarTest1 are calculated in a purely algebraic way (multiplication and division) which are much faster.

            But to achieve some interesting orbit you need not only the two coordinates of the initial position of the smaller object, but also the two coordinates of the initial velocity of the smaller object! Without specifying the initial velocity or assuming it is zero you are not going to get a nice curved orbit. You need to choose initial velocity. Also, the orbits should not get nowhere near the center of the big object, because the Newtonian gravitational force-field has a singularity at the center of the bigger body, so the closer the smaller body gets to that singularity, the worse the orbit will look (and the numerical errors will blow out of proportion) and it is not surprising you are getting the smaller body shot out of the center of the bigger one.

            In general there is a way to choose a velocity that will send the smaller body on an elliptic orbit with predefined orbital parameters: the length of the semi-major axis a, orbital eccentricity e, the angle omega between the semi-major axis and the horizontal x-axis and the angle f (called true anomaly) between the position vector from the bigger to the smaller body and the the semi-major axis.

            Source https://stackoverflow.com/questions/64938222

            QUESTION

            React - Canvas rendering, seperate draw logic & input logic
            Asked 2020-Nov-11 at 12:51

            Sorry if this has been asked before i did search and couldn't find anything.

            I am currently in the process of creating a react application and need to render details to a canvas. The program itself is going to be a map creation program. Currently I'm drawing to the canvas with the canvas context, although I want to change this out to konva or ocanvas eventually.

            My isssue at the moment is I'm struggling to find a nice way to seperate everything as the canvas need to handle lots of mouse events, rendering the data, and "tool" selection and some data manupulation. Ideally I'd like to seperate this code out to a seperate units so all of the code isn't in one place. IE: rendering logic, input logic, etc... How would I go about doing this? bearing in mind the map MAY need to be passed into the sub unit.

            Below is a snippet of the code i currently have i have removed some of the granular details but have kept all my mouse code and values:

            ...

            ANSWER

            Answered 2020-Nov-11 at 12:51

            After some considerations and thinking about the problem i have come up with the following solution:

            Within the canvas class create and initlise a list of "tools" part of this inilisation is giving a list of callback functions to update the state IE: render scale & offsets. the within the event functions for the canvas call the event within the selected tool.

            This method is quite expandable as any functions can be added to the callback, this means the tools can be coded to do anything. I also added a render function to the tool which get's called last and can render custom elements to the screen depending on the tool.

            Source https://stackoverflow.com/questions/64750960

            QUESTION

            Problems with ScaleGestureDetector.IOnScaleGestureListener C# Xamarin
            Asked 2020-Oct-29 at 10:22

            I'm building an app, that allows the user to move 2 textviews in Xamarin android .net. Everything works as it should, exept for onScale (pinch gesture). Debug shows that IOnScaleGestureListener functions are never called(that's why i left them empty). Does anyone know what do i need to do to call them? main activity

            ...

            ANSWER

            Answered 2020-Oct-29 at 10:22

            The problem was in OnTouch() i was returning return gestureDetector.OnTouchEvent(e); instead of return scaleDetector.OnTouchEvent(e);

            what's why non of this functions:

            Source https://stackoverflow.com/questions/64573583

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install diffy

            You can install using 'pip install diffy' or download it from GitHub, PyPI.
            You can use diffy like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            pip install diffy

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            https://github.com/Netflix-Skunkworks/diffy.git

          • CLI

            gh repo clone Netflix-Skunkworks/diffy

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            git@github.com:Netflix-Skunkworks/diffy.git

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