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Name: bandit
Version: 0.13.2
Summary: Security oriented static analyser for python code.
Home-page: https://wiki.openstack.org/wiki/Security/Projects/Bandit
Author: OpenStack Security Group
Author-email: openstack-dev@lists.openstack.org
License: UNKNOWN
Description: Bandit
======
A security linter from OpenStack Security
* Free software: Apache license
* Documentation: https://wiki.openstack.org/wiki/Security/Projects/Bandit
* Source: https://git.openstack.org/cgit/openstack/bandit
* Bugs: https://bugs.launchpad.net/bandit
Overview
--------
Bandit is a tool designed to find common security issues in Python code. To do
this Bandit processes each file, builds an AST from it, and runs appropriate
plugins against the AST nodes. Once Bandit has finished scanning all the files
it generates a report.
Installation
------------
Bandit is distributed on PyPI. The best way to install it is with pip:
Create a virtual environment (optional)::
virtualenv bandit-env
Install Bandit::
pip install bandit
# Or, if you're working with a Python 3 project
pip3.4 install bandit
Run Bandit::
bandit -r path/to/your/code
Bandit can also be installed from source. To do so, download the source
tarball from PyPI, then install it::
python setup.py install
Usage
-----
Example usage across a code tree::
bandit -r ~/openstack-repo/keystone
Example usage across the ``examples/`` directory, showing three lines of
context and only reporting on the high-severity issues::
bandit examples/*.py -n 3 -lll
Bandit can be run with profiles. To run Bandit against the examples directory
using only the plugins listed in the ``ShellInjection`` profile::
bandit examples/*.py -p ShellInjection
Usage::
bandit -h
usage: bandit [-h] [-r] [-a {file,vuln}] [-n CONTEXT_LINES] [-c CONFIG_FILE]
[-p PROFILE] [-l] [-f {txt,json,csv,xml}] [-o OUTPUT_FILE] [-v]
[-d]
targets [targets ...]
Bandit - a Python source code analyzer.
positional arguments:
targets source file(s) or directory(s) to be tested
optional arguments:
-h, --help show this help message and exit
-r, --recursive process files in subdirectories
-a {file,vuln}, --aggregate {file,vuln}
group results by vulnerability type or file it occurs
in
-n CONTEXT_LINES, --number CONTEXT_LINES
max number of code lines to display for each issue
identified
-c CONFIG_FILE, --configfile CONFIG_FILE
if omitted default locations are checked. Check
documentation for searched paths
-p PROFILE, --profile PROFILE
test set profile in config to use (defaults to all
tests)
-l, --level results severity filter. Show only issues of a given
severity level or higher. -l for LOW, -ll for MEDIUM,
-lll for HIGH
-i, --confidence confidence results filter, show only issues of this
level or higher. -i for LOW, -ii for MEDIUM, -iii for
HIGH
-f {csv,json,txt,xml}, --format {csv,json,txt,xml}
specify output format
-o OUTPUT_FILE, --output OUTPUT_FILE
write report to filename
-v, --verbose show extra information like excluded and included
files
-d, --debug turn on debug mode
Configuration
-------------
The Bandit config file is used to set several things, including:
- profiles - defines group of tests which should or shouldn't be run
- exclude_dirs - sections of the path, that if matched, will be excluded from
scanning
- plugin configs - used to tune plugins, for example: by tuning
blacklist_imports, you can set which imports should be flagged
- other - plugins directory, included file types, shell display
colors, etc.
Bandit requires a config file which can be specified on the command line via
-c/--configfile. If this is not provided Bandit will search for a default
config file (bandit.yaml) in the following preference order:
GNU/Linux:
- ./bandit.yaml
- ~/.config/bandit/bandit.yaml
- /etc/bandit/bandit.yaml
- /usr/local/etc/bandit/bandit.yaml
- <path to venv>/etc/bandit/bandit.yaml (if running within virtualenv)
Mac OSX:
- ./bandit.yaml
- /Users/${USER}/Library/Application Support/bandit/bandit.yaml
- /Library/Application Support/bandit/bandit.yaml
- /usr/local/etc/bandit/bandit.yaml
- <path to venv>/bandit/config/bandit.yaml (if running within virtualenv)
Exclusions
----------
In the event that a line of code triggers a Bandit issue, but that the line
has been reviewed and the issue is a false positive or acceptable for some
other reason, the line can be marked with a ``# nosec`` and any results
associated with it will not be reported.
For example, although this line may cause Bandit to report a potential
security issue, it will not be reported::
self.process = subprocess.Popen('/bin/echo', shell=True) # nosec
Vulnerability Tests
-------------------
Vulnerability tests or "plugins" are defined in files in the plugins directory.
Tests are written in Python and are autodiscovered from the plugins directory.
Each test can examine one or more type of Python statements. Tests are marked
with the types of Python statements they examine (for example: function call,
string, import, etc).
Tests are executed by the ``BanditNodeVisitor`` object as it visits each node
in the AST.
Test results are maintained in the ``BanditResultStore`` and aggregated for
output at the completion of a test run.
Writing Tests
-------------
To write a test:
- Identify a vulnerability to build a test for, and create a new file in
examples/ that contains one or more cases of that vulnerability.
- Consider the vulnerability you're testing for, mark the function with one
or more of the appropriate decorators:
- @checks('Call')
- @checks('Import', 'ImportFrom')
- @checks('Str')
- Create a new Python source file to contain your test, you can reference
existing tests for examples.
- The function that you create should take a parameter "context" which is
an instance of the context class you can query for information about the
current element being examined. You can also get the raw AST node for
more advanced use cases. Please see the context.py file for more.
- Extend your Bandit configuration file as needed to support your new test.
- Execute Bandit against the test file you defined in examples/ and ensure
that it detects the vulnerability. Consider variations on how this
vulnerability might present itself and extend the example file and the test
function accordingly.
Extending Bandit
----------------
Bandit allows users to write and register extensions for checks and formatters.
Bandit will load plugins from two entry-points:
- `bandit.formatters`
- `bandit.plugins`
Formatters need to accept 4 things:
- `result_store`: An instance of `bandit.core.BanditResultStore`
- `file_list`: The list of files which were inspected in the scope
- `scores`: The scores awarded to each file in the scope
- `excluded_files`: The list of files that were excluded from the scope
Plugins tend to take advantage of the `bandit.checks` decorator which allows
the author to register a check for a particular type of AST node. For example,
::
@bandit.checks('Call')
def prohibit_unsafe_deserialization(context):
if 'unsafe_load' in context.call_function_name_qual:
return bandit.Issue(
severity=bandit.HIGH,
confidence=bandit.HIGH,
text="Unsafe deserialization detected."
)
To register your plugin, you have two options:
1. If you're using setuptools directly, add something like the following to
your ``setup`` call::
# If you have an imaginary bson formatter in the bandit_bson module
# and a function called `formatter`.
entry_points={'bandit.formatters': ['bson = bandit_bson:formatter']}
# Or a check for using mako templates in bandit_mako that
entry_points={'bandit.plugins': ['mako = bandit_mako']}
2. If you're using pbr, add something like the following to your `setup.cfg`
file::
[entry_points]
bandit.formatters =
bson = bandit_bson:formatter
bandit.plugins =
mako = bandit_mako
Contributing
------------
Contributions to Bandit are always welcome! We can be found on #openstack-security
on Freenode IRC.
The best way to get started with Bandit is to grab the source::
git clone https://git.openstack.org/stackforge/bandit.git
You can test any changes with tox::
pip install tox
tox -e pep8
tox -e py27
tox -e py34
tox -e cover
Reporting Bugs
--------------
Bugs should be reported on Launchpad. To file a bug against Bandit, visit:
https://bugs.launchpad.net/bandit/+filebug
Under Which Version of Python Should I Install Bandit?
------------------------------------------------------
The answer to this question depends on the project(s) you will be running
Bandit against. If your project is only compatible with Python 2.7, you
should install Bandit to run under Python 2.7. If your project is only
compatible with Python 3.4, then use 3.4. If your project supports both, you
*could* run Bandit with both versions but you don't have to.
Bandit uses the `ast` module from Python's standard library in order to
analyze your Python code. The `ast` module is only able to parse Python code
that is valid in the version of the interpreter from which it is imported. In
other words, if you try to use Python 2.7's `ast` module to parse code written
for 3.4 that uses, for example, `yield from` with asyncio, then you'll have
syntax errors that will prevent Bandit from working properly. Alternatively,
if you are relying on 2.7's octal notation of `0777` then you'll have a syntax
error if you run Bandit on 3.4.
References
==========
Bandit wiki: https://wiki.openstack.org/wiki/Security/Projects/Bandit
Python AST module documentation: https://docs.python.org/2/library/ast.html
Green Tree Snakes - the missing Python AST docs:
http://greentreesnakes.readthedocs.org/en/latest/
Documentation of the various types of AST nodes that Bandit currently covers
or could be extended to cover:
http://greentreesnakes.readthedocs.org/en/latest/nodes.html
Platform: UNKNOWN
Classifier: Environment :: OpenStack
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: System Administrators
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Security
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