feat: Apply Risk scores to devices #1020
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carverauto/serviceradar#1020
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Imported from GitHub.
Original GitHub issue: #2821
Original author: @mfreeman451
Original URL: https://github.com/carverauto/serviceradar/issues/2821
Original created: 2026-02-13T06:45:55Z
Is your feature request related to a problem?
A little bit more about the event stream integration, this will go into a new GH issue, but right now UniFi is sending us syslog messages when the IDS blocks threats, currently its picking up ServiceRadar trying to do a portscan on a bunch of internal LAN devices, blocks it, generates the log, we create an event and then an alert. We should be able to automatically mark a device at risk if we can match the alert to a device kinda thing. Same thing with the AlienVault stuff and NetFlow, and any future integrations like falco or trivy, should have same capability, so we need to create some kinda framework here to handle all of this that can be used throughout the entire system, will probably live in the Elixir world.
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Imported GitHub comment.
Original author: @mfreeman451
Original URL: https://github.com/carverauto/serviceradar/issues/2821#issuecomment-3895211880
Original created: 2026-02-13T06:46:34Z
@marvin-hansen you might have some ideas around this as well I imagine?
Imported GitHub comment.
Original author: @marvin-hansen
Original URL: https://github.com/carverauto/serviceradar/issues/2821#issuecomment-3895269726
Original created: 2026-02-13T07:07:06Z
Yea,
Let's build a multi layer compliance score based on the OECD
recommendations for financial risk scoring.
KYC - Know your crap
AML - Anti Machine Laundery Score
And then just use these as pretext to blanket ban entire countries you
don't like for some reason and only whitelist those who are tagging along .
In all seriousness, what would actually be effective is a real time
contextual risk mitigation system. Instead of scoring, you monitor device
clusters and isolate them the moment anomaly behavior starts...
And again, your contextual hyper graph becomes invaluable here to detect
temporal pattern e.g. a spread out port scan that would otherwise evade
detection and spatial patterns e.g. multi host try a coordinated breach...
These are my two cents.
On Fri, Feb 13, 2026 at 14:46 Michael Freeman @.***>
wrote:
Imported GitHub comment.
Original author: @marvin-hansen
Original URL: https://github.com/carverauto/serviceradar/issues/2821#issuecomment-3895317825
Original created: 2026-02-13T07:17:37Z
The other thing you want to consider is a pre-incident graph that tracks anomalies that may not fit an active threat but fall outside the established pattern. This might be an out of the blue ping into a unknown network range, aborted tcp handshakes etc. One graph per detected device. As these build up over time, and an incident happens you can then extract the pre-required behavior and convert them into new IDS rules to isolate devices before they become active threats. This target specifically ATP scenarios were keep alive or CC packages flow before an attack starts.