attack-surface-metrics | collecting metrics of the attack surface | Security Testing library

by andymeneely Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | attack-surface-metrics Summary

attack-surface-metrics is a Python library typically used in Testing, Security Testing applications. attack-surface-metrics 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 attack-surface-metrics' or download it from GitHub, PyPI.

Scripts for collecting metrics of the attack surface

Support

Quality

Security

License

Reuse

Support

attack-surface-metrics has a low active ecosystem.

It has 13 star(s) with 5 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 8 open issues and 37 have been closed. On average issues are closed in 62 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of attack-surface-metrics is current.

Quality

attack-surface-metrics has 0 bugs and 0 code smells.

Security

attack-surface-metrics has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

attack-surface-metrics code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

attack-surface-metrics is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

attack-surface-metrics 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.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed attack-surface-metrics and discovered the below as its top functions. This is intended to give you an instant insight into attack-surface-metrics implemented functionality, and help decide if they suit your requirements.

Collapse Android blacklisted edges
Create a function from a loader loader
The edges of the call graph
Return a list of AndroidCallGraph
Load the call graph
Execute the cflow command
Remove the item from the collection
Push a new value to the queue
Parse command line arguments
Calculate all nodes connected to the attack surface
Node entry points
Return the largest fragment from the list of fragments
A list of exit points
Write a summary file
Calculate the entry and exit points
Loads the call graph for the given index
Get instance of CflowLineParser instance
Get instance of GprofLineParser
Create a function from a C flow line
Merge the call graph into a single node
Find the function for a given line number
Get node attributes
Collapse Android call graph
Write the call graph
Construct a Function from a javacg line
Create a function from a gprof file

Get all kandi verified functions for this library.

attack-surface-metrics Key Features

No Key Features are available at this moment for attack-surface-metrics.

attack-surface-metrics Examples and Code Snippets

No Code Snippets are available at this moment for attack-surface-metrics.

Community Discussions

Trending Discussions on Security Testing

DAST security scaning of a IoT Nodemcu esp8266 LUA script www HTML server connected to camera and A/C relay

QUESTION

DAST security scaning of a IoT Nodemcu esp8266 LUA script www HTML server connected to camera and A/C relay

Asked 2021-Apr-08 at 01:04

I have not, but shall DAST* security test, out of curiosity, an IoT device; Nodemcu esp8266 www server I built. It's showing a HTML page (on a mobile phone for example) that allows to control and interact with a camera module and a A/C relay. With it I can for example show images captured in the camera I even think it has some image recognition built in, and I can switch on and off a relay for electrical current to a light bulb (110/220v A/C power)

Before I start pentest I though I better start thinking of what types of exploits one would be able to find and detect? Which sinister exploits I will be able to find, or rather ought be able to find given a proper pentest exercise? (And if I do not find exploits, my approach to the pentest of the Iot might be wrong)

I ponder it might be a totally pointless exercise since the esp8266 www server (or rather its LUA programming libraries) might not have any security built into it, so basically it is "open doors" and everything with it is unsafe ?

The test report might just conclude what I can foresee be that the the "user input needs to be sanitized"?

Anyone have any idea what such pentest of a generic IoT device generally reports? Maybe it is possible to crash or reset the IoT device? Buffer overruns, XXS, call own code ?

I might use ZAP or Burpsuite or similar DAST security test tool.

I could of course SAST test it instead, or too, but I think it will be hard to find a static code analyzer for the NodeMCU libraries and NUA scripting language easily ? I found some references here though: https://ieeexplore.ieee.org/abstract/document/8227299 but it seems to be a long read.

So if someone just have a short answer what to expect in a DAST scan/pentest , it would be much appreciated.

Stay safe and secure out there ! Zombieboy

...

ANSWER

Answered 2021-Apr-08 at 01:04

I do my vulnerability scanning with OpenVAS (I assume this is what you mean by pentesting?). I am not aware of any IOT focused Tools.

If your server is running on esp8266, i would imagine that there is no much room for authentication and encryption of http traffic, but correct me if i am wrong).

Vulnerability Scan results might show things like unencrypted http traffic, credentials transmitted in cleartext (if you have any credentials fields in the pages served by the web server) etc. Depending on if there is encryption, you might also see weak encryption findings.

You might get some false positives on your lua webserver reacting like other known webservers when exploits are applied. I have seen this kind of false positive specially on DoS vulnerabilities when a vulnerability scan is testing a vulnerability and the server becomes unresponsive. Depending on how invasive your vulnerability scanner is, you might get a lot of false positives for DoS on such a constrained platform.

Source https://stackoverflow.com/questions/66995125

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

Vulnerabilities

No vulnerabilities reported

Install attack-surface-metrics

You can install using 'pip install attack-surface-metrics' or download it from GitHub, PyPI.
You can use attack-surface-metrics 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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