A security linter from OpenStack Security
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.
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
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
test config file, defaults to /etc/bandit/bandit.yaml,
or./bandit.yaml if not given
-p PROFILE, --profile PROFILE
test set profile in config to use (defaults to all
tests)
-l, --level results level filter
-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
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. Bandit will use bandit.yaml in the following preference order:
- Bandit config file specified with -c command line option
- bandit.yaml file from current working directory
- bandit.yaml file from ~/.config/bandit/
- bandit.yaml file in config/ directory of the Bandit package
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 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.
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.
Bandit allows users to write and register extensions for checks and formatters. Bandit will load plugins from two entry-points:
bandit.formattersbandit.plugins
Formatters need to accept 4 things:
result_store: An instance ofbandit.core.BanditResultStorefile_list: The list of files which were inspected in the scopescores: The scores awarded to each file in the scopeexcluded_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:
-
If you're using setuptools directly, add something like the following to your
setupcall:# 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']} -
If you're using pbr, add something like the following to your
setup.cfgfile:[entry_points] bandit.formatters = bson = bandit_bson:formatter bandit.plugins = mako = bandit_mako
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
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.
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