vimp
Compare data from multiple vulnerability scanners to get a more complete picture of potential exposures.
vimp
CLI currently supports output from common oepn source vulnerability scanners like grype, snyk, and trivy. The CLI also comes with an embedded data store (sqlite
) and support for other databases, like BigQuery. Alternatively, vimp
can also output to local file (JSON
or CVS
) or stdout
.
Usage
Start by using a container image, tor example, the official Redis image in Docker Hub:
export image="docker.io/redis@sha256:7b83a0167532d4320a87246a815a134e19e31504d85e8e55f0bb5bb9edf70448"
Next, generate vulnerability reports using any number of one supported OSS scanners:
grype --add-cpes-if-none -s AllLayers -o json --file report.json $image
snyk container test --app-vulns --json-file-output=report.json $image
trivy image --format json --output report.json $image
Then, import each one of the resulting reports into the supported target stores (use vimp import -h
for more information):
vimp import --source $image --file report.json
Note, by default, vimp
will store the imported data in Sqlite DB (.vimp.db
) in your home directory. You can use the --target
flag to save it to another location (e.g. sqlite://data/vimp.db
).
The output for the above command should look something like this:
INF found 78 unique vulnerabilities
Once you data is imported, you can then run queries against that data. The default query against the same data will provide summary of all the data in your store:
vimp query
Note, by default, vimp
will query (.vimp.db
) in your home directory. You can target different database using the --target
flag (e.g. sqlite://data/vimp.db
).
After importing data for one image from three sources the response will look something like this:
INF found 1 records
{
"https://docker.io/redis": {
"versions": {
"sha256:7b83a0167532d4320a87246a815a134e19e31504d85e8e55f0bb5bb9edf70448": {
"exposures": 240,
"sources": 3,
"packages": 73,
"high_score": 10,
"first_discovered": "2023-04-05T19:29:16Z",
"last_discovered": "2023-04-05T19:41:11Z"
}
}
}
}
To dig deeper into the data for that image, you can list all the vulnerabilities found that image across all of the sources:
vimp query --image https://docker.io/redis \
--digest sha256:7b83a0167532d4320a87246a815a134e19e31504d85e8e55f0bb5bb9edf70448
The results for that query should look something like this:
Notice the differences in severity
and score
reported by the different scanners:
{
"image": "https://docker.io/redis",
"digest": "sha256:7b83a0167532d4320a87246a815a134e19e31504d85e8e55f0bb5bb9edf70448",
"exposures": {
"CVE-2005-2541": [
{
"source": "grype",
"severity": "negligible",
"score": 10,
"last_discovered": "2023-04-05T19:40:42Z"
},
{
"source": "snyk",
"severity": "low",
"score": 9.8,
"last_discovered": "2023-04-05T19:29:16Z"
},
{
"source": "trivy",
"severity": "low",
"score": 10,
"last_discovered": "2023-04-05T19:41:11Z"
}
],
"CVE-2007-5686": [
{
"source": "grype",
"severity": "negligible",
"score": 4.9,
"last_discovered": "2023-04-05T19:40:42Z"
},
...
],
}
}
There will be a lot of commonalities in the data returned by each one of the scanners. You can append the --diffs-only
flag to highlight only the data where the exposures are not the same across all of the sources.
To drill into the packages impacted by each vulnerabilities you can use the additional --exposure
flag:
vimp query --image https://docker.io/redis \
--digest sha256:7b83a0167532d4320a87246a815a134e19e31504d85e8e55f0bb5bb9edf70448 \
--exposure CVE-2005-2541
The result should look something like this:
INF found 3 records
{
"image": "https://docker.io/redis",
"digest": "sha256:7b83a0167532d4320a87246a815a134e19e31504d85e8e55f0bb5bb9edf70448",
"exposure": "CVE-2005-2541",
"packages": [
{
"source": "grype",
"package": "tar",
"version": "1.34+dfsg-1",
"severity": "negligible",
"score": 10,
"last_discovered": "2023-04-05T19:40:42Z"
},
{
"source": "snyk",
"package": "tar",
"version": "1.34+dfsg-1",
"severity": "low",
"score": 9.8,
"last_discovered": "2023-04-05T19:29:16Z"
},
{
"source": "trivy",
"package": "tar",
"version": "1.34+dfsg-1",
"severity": "low",
"score": 10,
"last_discovered": "2023-04-05T19:41:11Z"
}
]
}
Data Store
The schema created by vimp
in the target DB will look something like this (adjusted for DB-specific data types):
image TEXT NOT NULL
digest TEXT NOT NULL
source TEXT NOT NULL
processed TIMESTAMP NOT NULL
cve TEXT NOT NULL
package TEXT NOT NULL
version TEXT NOT NULL
severity TEXT NOT NULL
score FLOAT NOT NULL
fixed BOOL NOT NULL
See sql/query.sql for examples of queries against the imported data.
See https://github.com/mchmarny/artifact-events for how to set up vimp
as an import for all new images in GCR or AR on GCP.
Installation
You can install vimp
CLI using one of the following ways:
See the release section for vimp
checksums and SBOMs.
Go
If you have Go 1.17 or newer, you can install latest vimp
using:
go install github.com/mchmarny/vimp@latest
Homebrew
On Mac or Linux, you can install vimp
with Homebrew:
brew tap mchmarny/vimp
brew install vimp
New release will be automatically picked up when you run brew upgrade
RHEL/CentOS
rpm -ivh https://github.com/mchmarny/vimp/releases/download/v$VERSION/vimp-$VERSION_Linux-amd64.rpm
Debian/Ubuntu
wget https://github.com/aquasecurity/vimp/releases/download/v$VERSION/vimp-$VERSION_Linux-amd64.deb
sudo dpkg -i vimp-$VERSION_Linux-64bit.deb
Binary
You can also download the latest release version of vimp
for your operating system/architecture from here. Put the binary somewhere in your $PATH, and make sure it has that executable bit.
The official vimp
releases include SBOMs
Disclaimer
This is my personal project and it does not represent my employer. While I do my best to ensure that everything works, I take no responsibility for issues caused by this code.