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A password strength measuring library.

Project Description

A configurable, extensible password strength measuring library.

TL;DR

Install:

$ pip install passwordmeter

Use from within an application with the default factors:

import passwordmeter

strength, improvements = passwordmeter.test(sys.argv[1])

if strength < 0.5:
  print 'Your password is too weak.'

Use on the command line:

$ pwm 'password'
Password strength: 0.132549901057 (Extremely weak)
Possible improvements:
  - Use a good mix of numbers, letters, and symbols
  - Avoid using one of the ten thousand most common passwords
  - Use a good mix of UPPER case and lower case letters

Overview

The main function provided by the \(passwordmeter\) package is the Meter.test() method, which returns a tuple of (float, dict). The float is the strength of the password in the range 0 to 1 (inclusive), where 0 is extremely weak and 1 is extremely strong. The second parameter, which may be None, is a dictionary of ways the password could be improved. The keys of the dict are general “categories” of ways to improve the password (e.g. “length”) that are fixed strings, and the values are internationalizable strings that are human-friendly descriptions and possibly tailored to the specific password.

A password’s strength is determined by doing a weighted, skewed, curved average of a set of “factors”. The \(Meter\) constructor takes a \(settings\) dictionary that configures, customizes, and/or supplements the default set of factors.

The \(passwordmeter.test\) is a helper function that simply uses the default settings to test the strength of a password, and is effectively a shorthand for Meter().test(...).

For example, to use a custom selection of factors:

import passwordmeter

# use only the 'length' and 'charmix' factors
meter = passwordmeter.Meter(settings=dict(factors='length,charmix'))

strength, improvements = meter.test('s3cr3t p4ssW0RD!')

Settings

The \(settings\) attribute to the \(Meter\) constructor is a dictionary with the following keys:

  • factors:

    This is a comma-separated list of factors to use in calculating the strength of a password. Each element in the list is either the name of a known factor or a symbol-spec as defined by the asset module. See passwordmeter.DEFAULT_FACTORS for the default list of factors (and their names).

    For example, to use only the ‘length’ factor and a custom factor:

    import passwordmeter
    
    class SillyFactor(passwordmeter.Factor):
      category = 'silly'
      def test(self, value, extra):
        if value == 'silly':
          return (0, 'That is a silly password!')
        return (1, None)
    
    meter = passwordmeter.Meter(
      settings=dict(factors=['length', SillyFactor]))
    
    # or, same thing, but using an asset-spec:
    
    meter = passwordmeter.Meter(
      settings=dict(factors='length,mypackage.SillyFactor'))
    
  • factor.{NAME}.{ATTRIBUTE}:

    Set a factor’s attribute during initialization. If a setting in the form factor.{NAME}.class is specified for a factor not listed in the \(factors\) setting, the factor will be auto-added to the list of factors. This is the preferred mechanism to add a custom factor to the default list.

    The following attributes are “special” (all are optional):

    Attribute Interpretation
    factor.{NAME}.class Specifies the asset-spec for the factory that can generate a Factor of this type.
    factor.{NAME}.weight Specifies the relative weight of this factor (default: 1).
    factor.{NAME}.skew Adds the specified amount to factor score (default: 0).
    factor.{NAME}.spread Multiplies the factor score by the specified amount – similar to \(weight\), but is applied before clipping (default: 1).
    factor.{NAME}.clipmin Force a minimum score for this factor (default: 0).
    factor.{NAME}.clipmax Force a maximum score for this factor (default: 1.3).
    factor.{NAME}.category Override the default improvement category.

    The following example settings in an INI file will give the \(length\) factor additional weight as well as adding the “mypkg.MyFactor” custom factor (initialized with the parameter \(msg\) set to 'abort') to the meter’s list:

    factor.length.weight   = 2.5
    factor.cust.class      = mypkg.MyFactor
    factor.cust.msg        = abort
    
  • pessimism:

    The password strength engine weights low scores higher than high scores. The degree to which the engine weights low scores is set by the \(pessimism\) setting, which defaults to 10 – the higher, the more a low score will pull the average score down. For example, with the default pessimism of 10, the two scores 0.75 and 0.25 will be averaged to 0.4 (instead of the true average of 0.5).

  • threshold:

    Specifies the maximum score for which improvement messages should be returned. If not specified, all possible improvements will be returned, even if the relevant factor returned a perfect score (1.0 or greater).

Custom Factors

A custom factor should subclass \(passwordmeter.Factor\), implement the \(test\) method, and have a unique \(category\) (string) attribute.

The \(test\) method takes two parameters: the \(value\) to be tested, and an opaque \(extra\) parameter that is supplied by the calling application (and can be ignored if not needed). It should return a tuple of (float, str).

The first element (float) of the return tuple must be greater or equal to zero. Although it should generally not be greater than 1.0, a factor may return a greater value: this is used to artificially boost the strength of the total outcome relative to the other factors if applicable. Note, however, that the Meter class will always clip the final outcome to the inclusive range [0, 1].

The second element of the return tuple should be a string, which is a description of how to improve the provided password. This string can be None if no known way exists to improve this password for this specific factor. Note that Meter class will associate this description with the factor’s category in the final outcome.

Release History

Release History

This version
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0.1.8

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0.1.7

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0.1.6

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0.1.5

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0.1.4

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0.1.3

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0.1.2

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0.1.1

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0.1.0

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0.0.1

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