Visualize port scan results in a self-contained HTML file.
In short: We interpret a host as a point in a vector space with 2^17 dimensions over F_2. Each dimension corresponds to a TCP- or UDP-port and has either value 0 or 1, depending on its state. Then we apply a dimensionality reduction technique named UMAP to project the data onto two dimensions.
Each circle in the plot corresponds to one group of hosts. The size of the circle is related to the size of the group. Hosts with the same port configuration are grouped together. Similar groups should be close by. The colors mean nothing - except for gray: no open ports. The coordinates are also not meaningful and can change with a new run.
If you require instructions on how to install a standard Python package, I
recommend you use pipx
:
$ pipx install git+https://github.com/SySS-Research/Scanscope.git
Unfortunately, the requirements (in particular the machine learning
dependencies including numpy
and pandas
) are quite heavy with almost
600MB, so be prepared.
$ scanscope nmap_output.xml -o scanscope.html
Hint: The more ports you scan, the better this should work.
I recommend scanning at least the top 100 ports, so: nmap -T4 -sS -F -oX nmap_output.xml -iL input.txt
. Service scans or script scans do not help.
Scanning the top 1000 ports or even all ports however, does.
For more infomation, read the output of scanscope -h
.
MIT licensed, developed by Adrian Vollmer, SySS GmbH.