Dockerfile | ||
fuzzer.go | ||
gauges.go | ||
main.go | ||
README.md | ||
watch.go |
afl-prom
What?
afl-prom exposes AFL's fuzzer_stats
files to be collected by Prometheus
Why?
Monitoring your fuzzers is an important task to stay up-to-date with the progress of your fuzzers - which means: time consumed and money spent.
While many users do this by running afl-fuzz in tmux
or screen
and attach to them every now and then, I don't think that this is a good monitoring. Neither does it scale well, nor does it allow the creation of histograms or cool graphs.
This is the problem which afl-prom tries to solve.
It exposes the stats which are reported on the afl-fuzz status screen and written in the fuzzer_stats
file of each fuzzer.
In combination with Prometheus and Grafana, this allows state-of-the-art monitoring of all of your fuzzers.
How?
Install Golang, then run
go get github.com/maride/afl-prom
After that, you can run afl-prom
, like this:
afl-prom --scan-delay 30 -- /path/to/fuzzer1 /path/to/fuzzer2
This exposes an HTTP server on port 2112
. Have a look at the /metrics
subpage.
Set up a Prometheus instance to grab these metrics. See the example configuration below.
scrape_configs:
- job_name: 'afl-prom'
scrape_interval: 5s
static_configs:
- targets: ['127.0.0.1:2112']
Then, set up a Grafana instance instance and use Prometheus as a data source.
You're done! Have fun with your new graphs.