dangerzone VS bandit

I don't have experience with Qubes in order to know what the files do, but this repo references two files in a qubes directory: e.g. https://github.com/freedomofpress/dangerzone/blob/v0.6.0/qub...

start here: https://github.com/freedomofpress/dangerzone

i've never used it, but i've been meaning to check it out. at least it should give you a jumping off point for further investigation.

if that is insufficient, use proofpoint.

for archives that are tickling bugs, you have to use a similar technique. it's not enough to analyze them and send them on as-is. you have to unpack in a sandbox (which will be detectable, no 2 ways about it, but the question is will anyone expend enough effort to detect -- no, not for your use case, seeing as how you're asking the question at all), process with dangerzone or dangerzone-like tool, then re-archive it and let the user see only that new archive.

I've read about the concept of "trusted PDFs" [1] from Qubes OS and the Dangerzone project [2].

I noticed people saying they use such tools to open applicant attachments in the context of employee hiring processes.

Isn't it simpler to just open these untrusted files in a cloud service like Google Drive or Microsoft Office online?

[1] https://blog.invisiblethings.org/2013/02/21/converting-untrusted-pdfs-into-trusted.html

[2] https://github.com/freedomofpress/dangerzone

You can use something similar on macOS, Windows or Linux, based on Docker containers, see Dangerzone: https://github.com/freedomofpress/dangerzone

https://github.com/freedomofpress/dangerzone has been a great tool to use as an added layer of defense. Definitely check out this users other projects as you can tell by the users name that they are made for journalists.

This is exactly what DangerZone is built for. Takes ‘dangerous’ PDFs, converts them to images and back (via OCR) so there’s nothing potentially harmful inside. Does all the conversion inside docker containers so there’s little chance of a sandbox escape or network access

The source code for the CLI application is probably the best place to look for an example of how to use the internal parts of the code which perform the actual conversion: https://github.com/freedomofpress/dangerzone/blob/main/dangerzone/cli.py

Check out danger zone - https://github.com/freedomofpress/dangerzone

Bandit is a tool designed to find common security issues in Python code. It was developed by the OpenStack Security Project and is a great addition to any serious Python project.

For the SAST stage, I used SonarQube tool. SonarQube is an open-source platform developed by SonarSource for continuous inspection of code quality to perform automatic reviews with static analysis of code to detect bugs and code smells on more than 30 programming languages. I preferred SonarQube instead of other SAST tools because it has a detailed documentation and plugins about integration with Jenkins and SonarQube works with Java projects pretty well. Of course you can similar multi-language-supported tools such as Semgrep or language-specific tools such as Bandit.

repos: - repo: https://github.com/PyCQA/bandit rev: 1.7.7 hooks: - id: bandit args: ["-c", "pyproject.toml", "-r", "."] additional_dependencies: ["bandit[toml]"]

On the other hand, Bandit is a dedicated security scanner designed to target critical security concerns such as SQL injection and cross-site scripting exploits. It meticulously scrutinizes the codebase to identify and alert developers about possible security breaches or vulnerabilities, thus fortifying the code against potential exploitation.

Bandit: is a tool designed for Python applications to analyse your code for potential security issues like insecure use of functions, hardcoded password and much more.

Bandit (for Python, open-source and free)

Add security checks (Bandit) and dependency checks (safety)

bandit

flake8-bandit which uses bandit for security linting.