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Benford && CVSS

Index

Who

@kopolindo
@giorgiofox (original idea)

Thanks to

Alex Ely Kossovsky for the awesome statistical review of Chi-Square vs SSD on Benford distributions.

Reason

We are trying to understand if security assessment results are Benford-like.
If they are then we can judge security assessment outcomes (big big big numbers must be involved).

How

  1. Generating CVSS score based on CVE Details Distribution
  2. Normalizing them with exponential function
  3. Calculating SSD (Sum of Squared Deviations). Chi-square is not compatible with Benford distributions, as explained here by Alex Ely Kossovsky (:beer:)
  4. Iterating this process on and on, to collect more and more data

Expectations

True, false, blah, not important, hackers gonna hack, just "fun'n'profit" ;)

Program

Choice: go
Why: concurrency
Result: go...home Alex... :(

HowTo

Build

Testing race conditions

$ make race It creates a benford executable in the same src folder.
Limitation 8192 concurrent goroutines.

Actual execution

$ make build
It creates a benford executable in the same src folder

Install

$ make install
It creates a benford executable in $GOPATH/bin/

Uninstall

$ make uninstall

Use

$ ./benford -h
Usage of ./benford:
  -chart
        Create a scattered chart in output folder
  -csv string
        CSV Output filename
  -human
        Human readable vs CSV readable
  -iterations int
        Number of iterations (default 1)
  -max-sample int
        Finish with this sample size (default -1)
  -min-sample int
        Start from this sample size (default -1)
  -sample int
        Size of the sample to be generated
  -verbose
        Verbose, print compliancy
  -version
        Print version

Flag explanation

-iterations is the (int) number of actual runs for the program (default: 1)
-sample is the (int) number of the vulnerabilities among which distribute the scores
-min-sample minimum of the sample set if use case is to range over multiple sample sets. It excludes -sample
-max-sample maximum of the sample set if use case is to range over multiple sample sets. It excludes -sample
-verbose print also additional messages (e.g., compliancy of computed SSD)
-version print the version and build of the program
-chart generates chart(s) in output folder
-human print in human readable format
-csv output results in output folder, with provided file name

Examples

Example 1

Run 200 times iterations (each iterations returns one SSD)
Samples spanning from 10000 (vulnerabilities scores) to 20000 (vulnerabilities scores)
Output: - one csv file containing: sample, min, max, average, devstd values - one line chart plotting min, max, average (three series overs Y axis) behavior versus sample (X axis)

$ ./benford -min-sample 10000 -max-sample 20000 -iterations 200 -chart -csv test.csv
Samples   0% |                                        | (78/10001) [1m9s:2h27m11s]

Output:

$ ls output
'SSDs result distribution vs samples_line.html'   test.csv

$ head output/test.csv
sample,min,max,average,devstd
10002,52.43,79.79,65.85,4.51
10006,54.42,75.33,65.21,4.11
10003,55.12,77.19,65.32,4.32
10004,57.28,79.51,65.82,4.26
10001,55.52,75.95,65.55,4.18
10005,51.90,78.48,65.46,4.12
10034,52.73,77.86,65.70,4.67
10007,53.30,76.37,65.46,4.63
10008,50.76,75.98,65.41,4.30