What can you do with an enriched SBOM? A parlay quickstart guide
2023年6月7日
0 分で読めますWe just released parlay, a new open source tool that can enrich SBOMs with additional information. You can read more in the announcement blog post. In that post, we briefly mentioned why this is important for decision-making based on SBOM data, but thought a few quick examples might be interesting.
parlay can add a lot of extra information to an SBOM, and we can use that information to write more powerful policies. While lines of JSON aren’t a perfect barometer, you can see in this particular example that the SBOM grew by more than 400% — which opens up lots of use cases.
1$ snyk sbom --format cyclonedx1.4+json | jq | wc -l
2 262
3$ snyk sbom --format cyclonedx1.4+json | parlay e enrich - | jq | wc -l
4 1169License policies
An SBOM with just the minimum elements won’t have information about the licenses that apply to the included packages. Let’s use Parlay and the Ecosyste.ms data to add that information.
snyk sbom --format cyclonedx1.4+json | parlay e enrich -Now that we have a richer SBOM, we can write more powerful policies. For this example, we’ll use Open Policy Agent and its powerful Rego programming language. Here we create two lists of policies, one to deny and one to warn on.
1package main
2
3name = input.metadata.component.name
4
5licenses_to_deny = [
6 "LGPL",
7]
8
9licenses_to_warn = [
10 "MIT"
11]
12
13deny[msg] {
14 component := input.components[_]
15 expression := component.licenses[_].expression
16 startswith(expression, licenses_to_deny[_])
17 msg := sprintf("%s is using %s which is licensed with an %s license", [name, component.name, expression])
18}
19
20warn[msg] {
21 component := input.components[_]
22 expression := component.licenses[_].expression
23 startswith(expression, licenses_to_warn[_])
24 msg := sprintf("%s is using %s which is licensed with an %s license", [name, component.name, expression])
25}Let’s continue our love of Unix pipes and use Conftest to apply that policy to the enriched SBOM.
snyk sbom --format cyclonedx1.4+json | parlay e enrich - | conftest test -In the example project, this issued a series of warnings about certain packages using indicated licenses.
1WARN - - main - snykit is using diff-lcs which is licensed with an MIT license
2WARN - - main - snykit is using mustermann which is licensed with an MIT license
3WARN - - main - snykit is using nio4r which is licensed with an MIT license
4WARN - - main - snykit is using puma-metrics which is licensed with an MIT license
5WARN - - main - snykit is using rack which is licensed with an MIT license
6WARN - - main - snykit is using rack-protection which is licensed with an MIT license
7WARN - - main - snykit is using rack-test which is licensed with an MIT license
8WARN - - main - snykit is using rake which is licensed with an MIT license
9WARN - - main - snykit is using rspec which is licensed with an MIT license
10WARN - - main - snykit is using rspec-core which is licensed with an MIT license
11WARN - - main - snykit is using rspec-expectations which is licensed with an MIT license
12WARN - - main - snykit is using rspec-mocks which is licensed with an MIT license
13WARN - - main - snykit is using rspec-support which is licensed with an MIT license
14WARN - - main - snykit is using sinatra which is licensed with an MIT license
15WARN - - main - snykit is using tilt which is licensed with an MIT license
16
1716 tests, 1 passed, 15 warnings, 0 failures, 0 exceptionsVulnerability policies
Let’s try something a bit more complicated. Let’s write a policy to flag vulnerabilities over a certain CVSS score in direct dependencies. This is a good example of when you need package data, dependency data, and vulnerability data.
1deny[msg] {
2 vulnerability := input.vulnerabilities[_]
3 rating := vulnerability.ratings[_]
4 rating.source.name == "Snyk"
5 rating.score > max_cvss_score
6 component := input.components[_]
7 bom_ref = vulnerability["bom-ref"]
8 component["bom-ref"] == bom_ref
9
10 root = input.metadata.component["bom-ref"]
11
12 dependency := input.dependencies[_]
13 dependency.ref == root
14
15 direct := dependency.dependsOn[_]
16 direct == bom_ref
17
18 msg := sprintf("%s version %s has a vulnerability with a CVSS score of %s", [component.name, component.version, round(rating.score)])
19}
20
21round(n) = f {
22 f := sprintf("%.2f", [n])
23 contains(f, ".") # Ensure that it was a float
24}
25
26round(n) = f {
27 not contains(sprintf("%.2f", [n]), ".") # Test if it wasn't a float
28 f := sprintf("%v.00", [n]) # Fudge the decimals for integer values
29}We can then generate or take our SBOM, enrich it using the Snyk vulnerability data, and then apply our policy using Conftest.
1snyk sbom --format cyclonedx1.4+json | parlay s enrich - | conftest test -
2FAIL - - main - puma version 4.2.1 has a vulnerability with a CVSS score of 9.10
3
43 tests, 2 passed, 0 warnings, 1 failure, 0 exceptionsHere we see it reporting on one vulnerability that matched our criteria.
Remember, this is just an example. The Rego language used by Open Policy Agent can be used to describe complex logic if required. And if you prefer another policy tool, that should work too.
Who is the author of this software?
One last quick example. The following example uses parlay to enrich our SBOM, and then uses jq and awk to output some useful information. In this case, we’re pulling out the named author of each package. Again, this information is often not in an SBOM with the minimum elements.
1$ snyk sbom --format cyclonedx1.4+json | parlay e enrich - | jq -r '(.components[] | [.name, .author]) | @tsv' | awk '{print $1; $1=""; print}'
2nio4r
3 Socketry
4puma
5 Puma
6prometheus-client
7 Prometheus
8puma-metrics
9
10rack
11 Official Rack repositories
12rack-test
13 Official Rack repositories
14rake
15 The Ruby Programming Language
16rspec-support
17 RSpec
18rspec-core
19 RSpec
20diff-lcs
21 Austin Ziegler
22rspec-expectations
23 RSpec
24rspec-mocks
25 RSpec
26rspec
27 RSpec
28ruby2_keywords
29 The Ruby Programming Language
30mustermann
31 Sinatra
32rack-protection
33 Sinatra
34tilt
35 Jeremy Evans
36sinatra
37 SinatraThere are lots more things you can do with richer SBOM data, and lots more data that would be useful to enrich SBOMs with as well. Let us know what you’d like to see, and please share examples of your experiments with parlay.