tsunami-security-scanner | general purpose network security scanner | Security library

by google Java Version: v0.0.14 License: Apache-2.0

kandi X-RAY | tsunami-security-scanner Summary

tsunami-security-scanner is a Java library typically used in Security applications. tsunami-security-scanner has no bugs, it has build file available, it has a Permissive License and it has medium support. However tsunami-security-scanner has 4 vulnerabilities. You can download it from GitHub, Maven.

Tsunami is a general purpose network security scanner with an extensible plugin system for detecting high severity vulnerabilities with high confidence.

Support

Quality

Security

License

Reuse

kandi-support Support

tsunami-security-scanner has a medium active ecosystem.
It has 7760 star(s) with 858 fork(s). There are 330 watchers for this library.
There were 1 major release(s) in the last 6 months.
There are 31 open issues and 37 have been closed. On average issues are closed in 104 days. There are 6 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of tsunami-security-scanner is v0.0.14

This Library - Support

Best in #Security

Average in #Security

This Library - Support

Best in #Security

Average in #Security

quality kandi Quality

tsunami-security-scanner has 0 bugs and 421 code smells.

This Library - Quality

Best in #Security

Average in #Security

This Library - Quality

Best in #Security

Average in #Security

security Security

tsunami-security-scanner has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
tsunami-security-scanner code analysis shows 4 unresolved vulnerabilities (0 blocker, 2 critical, 2 major, 0 minor).
There are 68 security hotspots that need review.

This Library - Security

Best in #Security

Average in #Security

This Library - Security

Best in #Security

Average in #Security

license License

tsunami-security-scanner 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.

This Library - License

Best in #Security

Average in #Security

This Library - License

Best in #Security

Average in #Security

build Reuse

tsunami-security-scanner releases are available to install and integrate.
Deployable package is available in Maven.
Build file is available. You can build the component from source.
Installation instructions, examples and code snippets are available.
tsunami-security-scanner saves you 4260 person hours of effort in developing the same functionality from scratch.
It has 9036 lines of code, 842 functions and 145 files.
It has low code complexity. Code complexity directly impacts maintainability of the code.

This Library - Reuse

Best in #Security

Average in #Security

This Library - Reuse

Best in #Security

Average in #Security

Top functions reviewed by kandi - BETA

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

Run the scan

Builds a NetworkEndpoint from the given URI
Finds the fingerprinting of each network services
Starts the scanning workflow asynchronously

Parse CLI options

Binds an instance of the cli option

Archives a blob to a GCS URL

Parses the given GCS url and object name

Generate scan results

Signals the execution stage

Open a connection to the given URL

Provide a Dispatcher with the max requests

Validates the configuration

Builds the root url for a web application service

Builds an exception message

Uzzify query params with extended path payload

Detect vulnerabilities

Creates a NetworkEndpoint object from a given NetworkEndpoint and a port number

Archives data to a file

Provides a new TcsClient based on the configuration properties

Provide a list of Payloads

Sends the request asynchronously

Runs the tests

Validates the parameters

Compares two tokens

Parses a VersionSet from a list of strings

Get all kandi verified functions for this library.

tsunami-security-scanner Key Features

Tsunami is a general purpose network security scanner with an extensible plugin system for detecting high severity vulnerabilities with high confidence.

tsunami-security-scanner Examples and Code Snippets

Community Discussions

Trending Discussions on Security

How are code-branch side channel attacks mitigated on Java?
Trusting individual invalid certs in mitmproxy
Ways to stop other android applications from identifying my application?
Log4j vulnerability - Is Log4j 1.2.17 vulnerable (was unable to find any JNDI code in source)?
How to manage OAuth flow in mobile application with server
Which are safe methods and practices for string formatting with user input in Python 3?
Was slf4j affected with vulnerability issue in log4j
Which version of Django REST Framework is affected by IP Spoofing?
Can NPM show me the age of packages before installing them?
Does the Log4j security violation vulnerability affect log4net?

Trending Discussions on Security

QUESTION

How are code-branch side channel attacks mitigated on Java?

Asked 2022-Mar-10 at 18:18

When you are working with secret keys, if your code branches unequally it could reveal bits of the secret keys via side channels. So for some algorithms it should branch uniformly independently of the secret key.

On C/C++/Rust, you can use assembly to be sure that no compiler optimizations will mess with the branching. However, on Java, the situation is difficult. First of all, it does JIT for desktop, and AOT on Android, so there are 2 possibilities for the code to be optimized in an unpredictable way, as JIT and AOT are always changing and can be different for each device. So, how are side channel attacks that take advantage of branching prevented on Java?

ANSWER

Answered 2022-Mar-10 at 18:18

When performing side-channel attacks, one of the main ways of doing these are to read the power-consumption of the chip using differential power analysis (DPA). When you have a branch in a code, such as an if statement, this can adversely affect the power draw in such a way that correlations can be made as to which choices are being made. To thwart this analysis, it would be in your interest to have a "linear" power consumption. This can do some degree be mitigated by code, but would ultimately depend upon the device itself. According Brennan et.al [1], some chose to tackle the java JIT issue by caching instructions. In code, the "best" you could do would be to program using canaries, in order to confuse an attacker, as proposed by Brennan et.al [2], and demonstrated in the following (very simplified) example code:

public bool check(String guess) {
    for(int i=0; i<guess.len; i++)
        return false;
    }
    return true;
}

versus;

public bool check(String guess) {
    bool flag=true, fakeFlag=true;
    for(int i=0; i<guess.len; i++) {
        if (guess[i] != password[i])
            flag=false;
        else
            fakeFlag = false:
        }
    return flag;
    }
}

[1]: T. Brennan, "Detection and Mitigation of JIT-Induced Side Channels*," 2020 IEEE/ACM 42nd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), 2020, pp. 143-145.

[2]: T. Brennan, N. Rosner and T. Bultan, "JIT Leaks: Inducing Timing Side Channels through Just-In-Time Compilation," 2020 IEEE Symposium on Security and Privacy (SP), 2020, pp. 1207-1222, doi: 10.1109/SP40000.2020.00007.

Source https://stackoverflow.com/questions/71316831

QUESTION

How to manage OAuth flow in mobile application with server

Asked 2022-Jan-27 at 12:23

I am developing an Sports Mobile App with flutter (mobile client) that tracks it's users activity data. After tracking an activity (swimming, running, walking ...) it calls a REST API developed by me (with springboot) passing that activity data with a POST. Then, my user will be able to view the logs of his tracked activities calling the REST API with a GET.

As I know that my own tracking development isn't as good as Strava, Garmin, Huawei and so on ones, I want to let my app users to connect with their Strava, Garmin and so on accounts to get their activities data, so I need users to authorize my app to get that data using OAuth.

In a first approach, I have managed to develop all the flow of OAuth with flutter using the Authorization Code Grant. The authorization server login is launched by flutter in a user agent (chrome tab), and once the resource owner has done the login and authorize my flutter app, my flutter app takes the authorization code and the calls to the authorization server to get the tokens . So I can say, that my client is my flutter App. When the oauth flow is done, I send the tokens to my Rest API in order to store them in a database.

My first idea was to send those tokens to my backend app in order to store them in a database and develop a process that takes those tokens, consult resource servers, parses each resource server json response actifvities to my rest API activity model ones and store in my database. Then, if a resource owner consults its activities calling my Rest API, he would get a response with all the activities (the mobiles app tracked ones + Strava, Garmin, resource servers etc ones stores in my db).

I have discarded the option to do the call to the resource servers directly from my client and to my rest api when a user pushes a syncronize button and mapping those responses directly in my client because I need the data of those resource servers responses in the backend in order to implement a medal functionality. Further more, Strava, Garmin, etc have limits of usage and I don't want to let my resource owners the hability to push the button the times they want.

Here is the flow of my first idea:

Steps:

Client calls the authorization server launching a user agent to an oauth login. In order to make the resource owner login and authorize. The url and the params are hardcoded are hardcoded in my client.
Resource owner logins and authorize client.
Callback is sent with code.
Client captures code of the callback and makes a post to he authorization server to get the tokens. As some authorization servers accept PKCE, I am using PKCE when its possible, to avoid attacks and hardcoding my client secret in my client. Others like Strava's, don't allow PKCE, so I have to hardcode the client secret in my client in order to get the tokens.
Once the tokens are returned to my client, I send them to my rest api and store in a database identifying the tokens resource owner.

To call the resource server:

One periodic process takes the tokens of each resource owner and updates my database with the activities returned from each resource server.
The resource owner calls the rest api and obtains all the activities.

The problem to this first idea is that some of the authorization servers allow implementing PKCE (Fitbit) and others use the client secret to create the tokens (Strava). As I need the client secret to get the tokens for some of those authorization servers, I have hardcoded the secrets in the client and that is not secure.

I know that it is dangerous to insert the client secrets into the client as a hacker can decompile my client and get the client secret. I can't figure how to get the resource owner tokens of Strava without hardcoding the client secret if PKCE is not allowed in the authorization server.

As I don't want to hardcode my client secrets in my client because it is insafe and I want to store the tokens in my db, I dont see my first approach as a good option. Further more, I am creating a POST request to my REST API in order to store the access token and refresh token in my database and if i am not wrong, that process can be done directly from the backend.

I am in the situation that I have developed a public client (mobile app) that has hardcoded the client secrets because I can't figure how to avoid doing that when PKCE isn't allowed by the authorization server to get the tokens.

So after thinking on all those problems, my second idea is to take advantage of my REST API and do the call to the authorization server from there. So my client would be confidential and I would do the OAuth flow with a Server-side Application.

My idea is based on this image.

In order to avoid the client secret hardcoding in my mobile client, could the following code flow based on the image work and be safe to connect to Strava, Garmin, Polar....?

Strava connection example:

MOBILE CLIENT

Mobile public Client Calls my Rest API to get as a result the URI of Strava Authorization server login with needed params such as: callback, redirect_uri, client_it, etc.
Mobile client Catches the Rest API GET response URI.
Mobile client launches a user agent (Chrome custom tab) and listen to the callback.

USER AGENT

The login prompt to strava is shown to the resource owner.
The resource owner inserts credentials and pushes authorize.
Callback is launched

MOBILE CLIENT

When my client detects the callback, return to client and stract the code from the callback uri.
Send that code to my REST API with a post. (https://myrestapi with the code in the body)

REST API CLIENT

Now, the client is my REST API, as it is going to be the one that calls the authorization server with the code obtained by the mobile client. The client will take that code and with the client secret hardcoded in it will call to the Authorization server. With this approach, the client secret is no more in the mobile client, so it is confidential.
The authorization server returns the tokens and I store them in a database.

THE PROCESS

Takes those tokens from my database and make calls to the resource servers of strava to get the activities. Then parses those activities to my model and stores them into the database.

Is this second approach a good way to handle the client secrets in order to avoid making them public? Or I am doing something wrong? Whatr flow could I follow to do it in the right way? I am really stuck with this case, and as I am new to OAuth world I am overwhelmed with all the information I have read.

ANSWER

Answered 2022-Jan-25 at 12:54

From what I understand, the main concern here is, you want to avoid hardcoding of client secret.
I am taking keycloak as an example for the authorization server, but this would be same in other authorization server as well since the implementation have to follow the standards
In the authrization servers there are two types of client's one is the
1.Confidential client - These are the one's that require both client-id and client-secret to be passed in your Rest api call

The CURL would be like this, client secret required

curl --location --request POST 'http://localhost:8080/auth/realms/testrealm/protocol/openid-connect/token' \
--header 'Content-Type: application/x-www-form-urlencoded' \
--data-urlencode 'grant_type=authorization_code' \
--data-urlencode 'client_id=confidentialclient' \
--data-urlencode 'client_secret=<CLIENT_SECRET_VALUE>' \
--data-urlencode 'code=<AUTHORIZATION_CODE_VALUE>' \
--data-urlencode 'redirect_uri=http://localhost:8080/callback' \
--data-urlencode 'code_verifier=<CODE_VERIFIER_PKCE>'

2.Public Client - If you create clients with this option you won't have to pass the client secret. Only client-id is sufficient while making the API calls.

For public clients you won't need to pass client secret, one less problem to worry about

curl --location --request POST 'http://localhost:8080/auth/realms/testrealm/protocol/openid-connect/token' \
--header 'Content-Type: application/x-www-form-urlencoded' \
--data-urlencode 'grant_type=authorization_code' \
--data-urlencode 'client_id=publiclcient' \
--data-urlencode 'code=<AUTHORIZATION_CODE_VALUE>' \
--data-urlencode 'redirect_uri=http://localhost:8080/callback' \
--data-urlencode 'code_verifier=<CODE_VERIFIER_PKCE>'

These options would be and should be available in most of the standard authorization servers.

Source https://stackoverflow.com/questions/70770137

QUESTION

Which are safe methods and practices for string formatting with user input in Python 3?

Asked 2022-Jan-18 at 12:53

My Understanding

From various sources, I have come to the understanding that there are four main techniques of string formatting/interpolation in Python 3 (3.6+ for f-strings):

Formatting with %, which is similar to C's printf
The str.format() method
Formatted string literals/f-strings
Template strings from the standard library string module

My knowledge of usage mainly comes from Python String Formatting Best Practices (source A):

str.format() was created as a better alternative to the %-style, so the latter is now obsolete
- However, str.format() is vulnerable to attacks if user-given format strings are not properly handled
f-strings allow str.format()-like behavior only for string literals but are shorter to write and are actually somewhat-optimized syntactic sugar for concatenation
Template strings are safer than str.format() (demonstrated in the first source) and the other two methods (implied in the first source) when dealing with user input

I understand that the aforementioned vulnerability in str.format() comes from the method being usable on any normal strings where the delimiting braces are part of the string data itself. Malicious user input containing brace-delimited replacement fields can be supplied to the method to access environment attributes. I believe this is unlike the other ways of formatting where the programmer is the only one that can supply variables to the pre-formatted string. For example, f-strings have similar syntax to str.format() but, because f-strings are literals and the inserted values are evaluated separately through concatenation-like behavior, they are not vulnerable to the same attack (source B). Both %-formatting and Template strings also seem to only be supplied variables for substitution by the programmer; the main difference pointed out is Template's more limited functionality.

My Confusion

I have seen a lot of emphasis on the vulnerability of str.format() which leaves me with questions of what I should be wary of when using the other techniques. Source A describes Template strings as the safest of the above methods "due to their reduced complexity":

The more complex formatting mini-languages of the other string formatting techniques might introduce security vulnerabilities to your programs.

Yes, it seems like f-strings are not vulnerable in the same way str.format() is, but are there known concerns about f-string security as is implied by source A? Is the concern more like risk mitigation for unknown exploits and unintended interactions?

I am not familiar with C and I don't plan on using the clunkier %/printf-style formatting, but I have heard that C's printf had its own potential vulnerabilities. In addition, both sources A and B seem to imply a lack of security with this method. The top answer in Source B says,

String formatting may be dangerous when a format string depends on untrusted data. So, when using str.format() or %-formatting, it's important to use static format strings, or to sanitize untrusted parts before applying the formatter function.

Do %-style strings have known security concerns?
Lastly, which methods should be used and how can user input-based attacks be prevented (e.g. filtering input with regex)?
- More specifically, are Template strings really the safer option? and Can f-strings be used just as easily and safely while granting more functionality?

ANSWER

Answered 2022-Jan-18 at 12:53

It doesn't matter which format you choose, any format and library can have its own downsides and vulnerabilities. The bigger questions you need to ask yourself is what is the risk factor and the scenario you are facing with, and what are you going to do about it. First ask yourself: will there be a scenario where a user or an external entity of some kind (for example - an external system) sends you a format string? If the answer is no, there is no risk. If the answer is yes, you need to see whether this is needed or not. If not - remove it to eliminate the risk. If you need it - you can perform whitelist-based input validation and exclude all format-specific special characters from the list of permitted characters, in order to eliminate the risk. For example, no format string can pass the ^[a-zA-Z0-9\s]*$ generic regular expression.

So the bottom line is: it doesn't matter which format string type you use, what's really important is what do you do with it and how can you reduce and eliminate the risk of it being tampered.

Source https://stackoverflow.com/questions/70751249

QUESTION

Can NPM show me the age of packages before installing them?

Asked 2022-Jan-05 at 10:35

In light of recent malware in existing npm packages, I would like to have a mechanism that lets me do some basic checks before installing new packages or updating existing ones. My main issue are both the packages I install directly, and also the ones I install indirectly.

In general I want to get a list of package-version that npm would install before installing it. More specifically I want the age of the packages that would be installed, so I can generate a warning if any of them is less than a day old.

If I could do that directly with npm, that would be neat, but I'm afraid I need to do some scripting around it.

specific use case:

If I executed npm install react-native-gesture-handler on 2021-10-22 it would have executed the post-install hook of a malicious version of ua-parser and my computer would have been compromised, which is something I would like to avoid.

When I enter npm install react-native-gesture-handler --dry-run, it only tells me which version of react-native-gesture-handler it would have installed, but it would not tell me that it would install a version of ua-parser that was released on that day.

additional notes:

I know that npm i --dry-run exists, but it shows only the direct packages.
I know that npm list exists, but it only shows packages after installing (and thus after install-hooks have already done their harm)
both only show packages version and not their age
I do not know how I would get a list of packages that would come with a install-hook before installing them
pointers to alternative ways to deal with malicious npm packages are welcome.
so far my best solution would be to do "--ignore-scripts" but that would come with it's own set of problems

ANSWER

Answered 2021-Dec-07 at 07:26

To find out the malicious package, you will need a script that will check your package for vulnerabilities against national vulnerabilities database

The National Vulnerability Database includes databases of security checklist references, security related software flaws, misconfigurations, product names, and impact metrics.

Mostly all software companies use application security tools like Veracode, Snyk or Checkmarx that does this usually in a stage before deployment in the CICD pipeline.

If you're looking to achieve this locally, you can try

npm audit

But this will audit the installed dependencies and also its sub-dependencies in your project against the default registry (nexus or artifactory or npm registry) and gets you the list of known vulnerabilities with the version details in which patch is available.

npm view will get you the below details about the package even when it is not installed.

version checks before installing would need a script to do the necessary at preinstall, I would suggest to have a dedicated project for security checks (reusable for all projects), and link or publish it then configure that in your project scripts like below,

Security Project:

This will have the script to check for vulnerabilities, leverage npm view or npm version and audit the module then return the results.

Main project:

In here setup the scripts in package.json to use the above published project and check for vulnerabilities before installation.

npx security-project vulnerabilities


scripts: {
  vulnerability: npx security-project vulnerabilities
  preinstall: npx security-project vulnerabilities

  or

  preinstall: "sh ./checkVulnerabilities.sh" // this script can take package name through command line flags like --package axios
}

Snyk takes your package.json and will scan all the modules for security vulnerabilities. You could also search for specific module and check for a version's health score.

https://snyk.io/advisor/check/npm

Alternatively, you could use Snyk extension in your IDE for the same.

We have RetireJS chrome extension for scanning vulnerable JS module version with vulnerabilities in the application.

Good Ref:- 6-tools-you-can-use-to-check-for-vulnerabilities-in-node-js

Above are the ideas that I could think of, hope it helps.

Source https://stackoverflow.com/questions/69975960

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

Vulnerabilities

No vulnerabilities reported

Install tsunami-security-scanner

To quickly get started with Tsunami scans,.
install the following required dependencies:.
install the following required dependencies: nmap >= 7.80 ncrack >= 0.7
start a vulnerable application that can be identified by Tsunami, e.g. an unauthenticated Jupyter Notebook server. The easiest way is to use a docker image: docker run --name unauthenticated-jupyter-notebook -p 8888:8888 -d jupyter/base-notebook start-notebook.sh --NotebookApp.token=''
execute the following command: bash -c "$(curl -sfL https://raw.githubusercontent.com/google/tsunami-security-scanner/master/quick_start.sh)"
Clone the google/tsunami-security-scanner and google/tsunami-security-scanner-plugins repos into $HOME/tsunami/repos directory.
Compile all Google Tsunami plugins and move all plugin jar files into $HOME/tsunami/plugins directory.
Compile the Tsunami scanner Fat Jar file and move it into $HOME/tsunami directory.
Move the tsunami.yaml example config into $HOME/tsunami directory.
Print example Tsunami command for scanning 127.0.0.1 using the previously generated artifacts.
start a vulnerable application that can be identified by Tsunami, e.g. an unauthenticated Jupyter Notebook server. The easiest way is to use a docker image:.
start a vulnerable application that can be identified by Tsunami, e.g. an unauthenticated Jupyter Notebook server. The easiest way is to use a docker image: docker run --name unauthenticated-jupyter-notebook -p 8888:8888 -d jupyter/base-notebook start-notebook.sh --NotebookApp.token=''
build the docker image for Tsunami: docker build -t tsunami .
run the Tsunami image. The logs can be saved to the host machine by mounting a volume: docker run --network="host" -v "$(pwd)/logs":/usr/tsunami/logs tsunami