-
Notifications
You must be signed in to change notification settings - Fork 21
Update FAQ #33
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
base: main
Are you sure you want to change the base?
Update FAQ #33
Changes from all commits
File filter
Filter by extension
Conversations
Jump to
Diff view
Diff view
There are no files selected for viewing
| Original file line number | Diff line number | Diff line change |
|---|---|---|
|
|
@@ -15,13 +15,14 @@ We know that JupyterLab is where many data scientist experiement and prove out t | |
|
|
||
| Yes, you can run NB Defense in your CI pipline using the [NB Defense CLI](./getting-started/cli.md)! Use the CLI in your CI pipelines to scan repositories, or multiple notebooks at a time. | ||
|
|
||
| ### What is special about NB Defense when many security tools offer similar functionality? | ||
| ### What is unique about NB Defense when many security tools offer similar functionality? | ||
|
|
||
| NB Defense is special because it allows you to scan Jupyter Notebooks. We provide both a [JupyterLab Extension](./getting-started/jupyter-lab-extension.md) that you can use to scan notebooks while you're working, and a [CLI](./getting-started/cli.md) that you can use to scan groups of notebooks or repositories. Using both of these tools, you can scan your notebooks for personally identifiable information (PII), secrets, common exposures and vulnerabilities (CVEs), and non permissive licenses. | ||
|
|
||
| NB Defense allows you to scan Jupyter Notebooks. Currently most security tools do not support Notebook `.ipynb` formatted files. NB Defense fills this gap. We provide both a [JupyterLab Extension](./getting-started/jupyter-lab-extension.md) that you can use to scan notebooks within Jupyterlab environment, and a [CLI](./getting-started/cli.md) that you can use to scan groups of notebooks or repositories. Using both of these tools, you can scan your notebooks for personally identifiable information (PII), secrets, common exposures and vulnerabilities (CVEs), and non permissive licenses. | ||
|
|
||
| ### Does NB Defense JupyterLab Extension run in my kernel? | ||
|
|
||
| We recommend that you isolate NB Defense from the kernel that you are using for your notebook. If you have installed NB Defense into a separate python environment, it will not run in your kernel. We do use your active kernels python path to determine which third party dependencies are installed, so we can scan them for CVEs and licenses. | ||
| No. We recommend installing NB Defense Jupyterlab extension outside of Kernel specific environment. NB Defense runs its code on the Jupyter Server instead of Notebook specific Kernel(s). We do use your active kernels python path to determine which third party dependencies are installed, so we can scan them for CVEs and licenses. | ||
|
Member
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. CurrentWe recommend installing NB Defense Jupyterlab extension outside of Kernel specific environment. RecommendedWe recommend installing NB Defense JupyterLab extension outside of a kernel-specific environment. Also, we should add an apostrophe for kernel's and capitalize Python in |
||
|
|
||
| ## Found A Bug? 🐞 | ||
|
|
||
|
|
||
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Current
that you can use to scan notebooks within Jupyterlab environment
Recommended
that you can use to scan notebooks within a JupyterLab environment
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Perhaps instead of saying they don't support .ipynb files, state that they aren't rendering findings in a way that a Jupyter user understands. Specifically they will report an issue on a line of a JSON file, not within a specific cell or output.