graph_adversarial_attack | Adversarial Attack on Graph Structured Data | Cybersecurity library

 by   Hanjun-Dai Python Version: Current License: MIT

kandi X-RAY | graph_adversarial_attack Summary

kandi X-RAY | graph_adversarial_attack Summary

graph_adversarial_attack is a Python library typically used in Security, Cybersecurity applications. graph_adversarial_attack has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However graph_adversarial_attack build file is not available. You can download it from GitHub.

Adversarial Attack on Graph Structured Data (to appear in ICML 2018). This repo contains the code, data and results reported in the paper.
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              graph_adversarial_attack has a low active ecosystem.
              It has 99 star(s) with 27 fork(s). There are 3 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 6 open issues and 0 have been closed. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of graph_adversarial_attack is current.

            kandi-Quality Quality

              graph_adversarial_attack has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              graph_adversarial_attack is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              graph_adversarial_attack releases are not available. You will need to build from source code and install.
              graph_adversarial_attack has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions, examples and code snippets are available.
              graph_adversarial_attack saves you 1400 person hours of effort in developing the same functionality from scratch.
              It has 3131 lines of code, 154 functions and 33 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

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            graph_adversarial_attack Key Features

            No Key Features are available at this moment for graph_adversarial_attack.

            graph_adversarial_attack Examples and Code Snippets

            No Code Snippets are available at this moment for graph_adversarial_attack.

            Community Discussions

            QUESTION

            hardware based password manager integration with device
            Asked 2021-Apr-28 at 12:48

            I am aiming to build a hardware based password manager that will store credentials like -username and passwords- externally, right now I am searching about it but I am having trouble in identifying that how will that external device integrate with browsers and websites when connected to provide the credentials stored in it. I mean what technique is used to integrate the hardware password managers to the device or browser.

            I would appreciate any sort of help and guidance from your side, Thanks!

            ...

            ANSWER

            Answered 2021-Apr-28 at 12:48

            Usually they inject passwords using a HID device acting as a keyboard. Check out the OnlyKey as an example.

            The way these work is by injecting/typing username and password based on pressing a hardware button against which you have stored the relevant credentials. There is also the option to complete MFA by storing an OTP token. Some will act like any other password manager by parsing the website URL against what is stored, but I guess this opens an attack surface when feeding data back to the device.

            -- BVS

            Source https://stackoverflow.com/questions/67290550

            QUESTION

            What does "assumptions" refer to when writing a pentest report?
            Asked 2021-Apr-16 at 15:25

            I have to write the "assumptions" part of a pentest report and I am having trouble understanding what I should write. I checked multiple pentest reports (from https://github.com/juliocesarfort/public-pentesting-reports) but none of them had this paragraph.
            Also I found this explanation "In case there are some assumptions that the pen-tester considers before or during the test, the assumptions need to be clearly shown in the report. Providing the assumption will help the report audiences to understand why penetration testing followed a specific direction.", but still what I do have in mind it is more suited for "attack narative".
            Can you provide me a small example (for one action, situation) so I can see exactly how it should be written?

            ...

            ANSWER

            Answered 2021-Apr-16 at 15:25

            I would think the "assumptions" paragraph and the "Attack narrative" paragraph are somehow overlapping. I would use the "Assumptions" paragraph to state a couple of high level decisions made before starting the attack, with whatever little information the pentester would have on the attack. I would expand on the tools and techniques used in the "Attack narrative" paragraph

            For example an assumption could be: "The pentester is carrying on the exercise against the infrastructure of a soho company with less than 5 people It is common for soho companies to use consumer networking equipment that is usually unsecure, and left configured as defualt. For this reason the attacker focused on scanning for http and ssh using a database of vendors default username and passwords"

            Source https://stackoverflow.com/questions/67126985

            QUESTION

            Is there a way to use a particular C function/symbol as output by nm
            Asked 2021-Mar-10 at 23:13

            I'm trying to analyse a compiled file for cybersec learning purposes and want to use a particular function.

            Here is the output of nm --defined-only ./compiled_file:

            ...

            ANSWER

            Answered 2021-Mar-09 at 12:54

            Yes, it is possible. The point of having exported symbols in shared libraries is to be able to use them - after all. In C, you can do this either by linking the library to the application (not really an option for python), or runtime loading the library and finding the required symbol (on linux: dlopen, dlsym). The manpage example shows how to do this in C.

            Source https://stackoverflow.com/questions/66547182

            QUESTION

            How to allow XML, JSON and CSV files to be uploaded when CSP is set in the webpage
            Asked 2020-Nov-04 at 19:09

            Currently, I have set the following CSP header in the HTML file of my webpage -

            ...

            ANSWER

            Answered 2020-Nov-04 at 19:09

            The issue was caused and fixed as follows -

            The button that takes XML file as input in the HTML form has an inline event handler, which the CSP Policy was blocking, thereby blocking the upload. I moved this inline event handler to an external function and called the function. This fixed the issue and CSP is no longer blocking the function.

            Source https://stackoverflow.com/questions/64421818

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

            Vulnerabilities

            No vulnerabilities reported

            Install graph_adversarial_attack

            First clone the repo recursively, since it depends on another repo (https://github.com/Hanjun-Dai/pytorch_structure2vec):. (BTW if you have trouble downloading it because of permission issues, please see this issue ).
            The current code depends on pytorch 0.3.1, cffi and CUDA 9.1. Please install using the following command (for linux):.

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            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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            CLONE
          • HTTPS

            https://github.com/Hanjun-Dai/graph_adversarial_attack.git

          • CLI

            gh repo clone Hanjun-Dai/graph_adversarial_attack

          • sshUrl

            git@github.com:Hanjun-Dai/graph_adversarial_attack.git

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