mirror of
https://github.com/AFLplusplus/AFLplusplus.git
synced 2025-06-08 00:01:33 +00:00
144 lines
4.5 KiB
Markdown
144 lines
4.5 KiB
Markdown
# Remote monitoring with StatsD
|
|
|
|
StatsD allows you to receive and aggregate metrics from a wide range of application and retransmit them to the backend of your choice.
|
|
This enables you to create nice and readable dashboards containing all the information you need on your fuzzer instances.
|
|
No need to write your own statistics parsing system, deploy and maintain it to all your instances, sync with your graph rendering system...
|
|
|
|
The available metrics are :
|
|
- cycle_done
|
|
- cycles_wo_finds
|
|
- execs_done
|
|
- execs_per_sec
|
|
- paths_total
|
|
- paths_favored
|
|
- paths_found
|
|
- paths_imported
|
|
- max_depth
|
|
- cur_path
|
|
- pending_favs
|
|
- pending_total
|
|
- variable_paths
|
|
- unique_crashes
|
|
- unique_hangs
|
|
- total_crashes
|
|
- slowest_exec_ms
|
|
- edges_found
|
|
- var_byte_count
|
|
- havoc_expansion
|
|
|
|
Compared to the default integrated UI, these metrics give you the opportunity to visualize trends and fuzzing state over time.
|
|
By doing so, you might be able to see when the fuzzing process has reached a state of no progress, visualize what are the "best strategies"
|
|
(according to your own criteria) for your targets, etc. And doing so without requiring to log into each instance manually.
|
|
|
|
An example visualisation may look like the following:
|
|
|
|
|
|
*Notes: The exact same dashboard can be imported with [this JSON template](statsd/grafana-afl++.json).*
|
|
|
|
## How to use
|
|
|
|
To enable the StatsD reporting on your fuzzer instances, you need to set the environment variable `AFL_STATSD=1`.
|
|
|
|
Setting `AFL_STATSD_TAGS_FLAVOR` to the provider of your choice will assign tags / labels to each metric based on their format.
|
|
The possible values are `dogstatsd`, `librato`, `signalfx` or `influxdb`.
|
|
For more information on these env vars, check out `docs/env_variables.md`.
|
|
|
|
The simplest way of using this feature is to use any metric provider and change the host/port of your StatsD daemon,
|
|
with `AFL_STATSD_HOST` and `AFL_STATSD_PORT`, if required (defaults are `localhost` and port `8125`).
|
|
To get started, here are some instruction with free and open source tools.
|
|
The following setup is based on Prometheus, statsd_exporter and Grafana.
|
|
Grafana here is not mandatory, but gives you some nice graphs and features.
|
|
|
|
Depending on your setup and infrastructure, you may want to run these applications not on your fuzzer instances.
|
|
Only one instance of these 3 application is required for all your fuzzers.
|
|
|
|
To simplify everything, we will use Docker and docker-compose.
|
|
Make sure you have them both installed. On most common Linux distributions, it's as simple as:
|
|
|
|
```sh
|
|
curl -fsSL https://get.docker.com -o get-docker.sh
|
|
sh get-docker.sh
|
|
```
|
|
|
|
Once that's done, we can create the infrastructure.
|
|
Create and move into the directory of your choice. This will store all the configurations files required.
|
|
|
|
First, create a `docker-compose.yml` containing the following:
|
|
```yml
|
|
version: '3'
|
|
|
|
networks:
|
|
statsd-net:
|
|
driver: bridge
|
|
|
|
services:
|
|
prometheus:
|
|
image: prom/prometheus
|
|
container_name: prometheus
|
|
volumes:
|
|
- ./prometheus.yml:/prometheus.yml
|
|
command:
|
|
- '--config.file=/prometheus.yml'
|
|
restart: unless-stopped
|
|
ports:
|
|
- "9090:9090"
|
|
networks:
|
|
- statsd-net
|
|
|
|
statsd_exporter:
|
|
image: prom/statsd-exporter
|
|
container_name: statsd_exporter
|
|
volumes:
|
|
- ./statsd_mapping.yml:/statsd_mapping.yml
|
|
command:
|
|
- "--statsd.mapping-config=/statsd_mapping.yml"
|
|
ports:
|
|
- "9102:9102/tcp"
|
|
- "8125:9125/udp"
|
|
networks:
|
|
- statsd-net
|
|
|
|
grafana:
|
|
image: grafana/grafana
|
|
container_name: grafana
|
|
restart: unless-stopped
|
|
ports:
|
|
- "3000:3000"
|
|
networks:
|
|
- statsd-net
|
|
```
|
|
|
|
Then `prometheus.yml`
|
|
```yml
|
|
global:
|
|
scrape_interval: 15s
|
|
evaluation_interval: 15s
|
|
|
|
scrape_configs:
|
|
- job_name: 'fuzzing_metrics'
|
|
static_configs:
|
|
- targets: ['statsd_exporter:9102']
|
|
```
|
|
|
|
And finally `statsd_mapping.yml`
|
|
```yml
|
|
mappings:
|
|
- match: "fuzzing.*"
|
|
name: "fuzzing"
|
|
labels:
|
|
type: "$1"
|
|
```
|
|
|
|
Run `docker-compose up -d`.
|
|
|
|
Everything should be now setup, you are now able to run your fuzzers with
|
|
|
|
```
|
|
AFL_STATSD_TAGS_FLAVOR=dogstatsd AFL_STATSD=1 afl-fuzz -M test-fuzzer-1 -i i -o o ./bin/my-application @@
|
|
AFL_STATSD_TAGS_FLAVOR=dogstatsd AFL_STATSD=1 afl-fuzz -S test-fuzzer-2 -i i -o o ./bin/my-application @@
|
|
...
|
|
```
|
|
|
|
This setup may be modified before use in production environment. Depending on your needs: addind passwords, creating volumes for storage,
|
|
tweaking the metrics gathering to get host metrics (CPU, RAM ...).
|