Metricon: Automated Incident Reporting

Speaker: Juhaniu Eronen

“The Autoreporter Project” – Background

Goal: make finland mostly harmless to the rest of the internet

(that’s actually in the law – Protection of Privacy in Electronic Comms/Finland)


/me: I’ll need to put some verbiage around this tonight to give you a good picture of what Juhaniu was conveying…really good description of their charter, goals, challenges, successes


What’s a “finnish” system:

  • any autonomous systems in finnish soil, operated or owned by finnish orgs
  • .fi .ax domains
  • +358 telephone prefix
  • other networks owned by finnish orgs
  • finnish banks/brands/CC


Telcos mandated to report infosec incidents as well as major faults affecting users, networks or provider ability to operate



Regulation for finnish security providers: Basic security of facilities & processes, Business continuity, spam blocking

  • Setup mandatory reporting for ISPs
  • Establish CERT-FI



Problem: Finland cleans up its own house, but they still end up getting attacked!

Problem: Most incidents are out of scope in mandated reporting

Problem: Establishing CERT-FI – no ownership or visibility of network; 3 ppl that in theory are expected to be there 7×24!

Huge increase in incidents [reported] from 2002-2006. It’s a pretty graph, but it really shows that the CERT-FI workforce increased and that processes were honed


How many incidents affect finnish networks?

How are we compared to neighbors (would love to take a data-driven jab at swedes).


So, workforce, regulatory and other constraints & need for actionable data == make automated system.


2006: created automated system to capture incident reports (mostly malware) from various monitoring projects around the globe.

Daily reports, e-mailed, CSV format pre-defined agreed-upon subjects. digitally signed. reported incidents in body.


How CERT-FI handles abuse:

  • detection
  • reports (e-mail/phone/fax) – Funny story: one woman printed out all the spam she received and sent to CERT-FI, until asked not to anymore.
  • Scraping feeds, normalizing/correlating data
  • Finding owners
  • -Map bad events to netblocks
  • -maintain contact list (& contact prefs!)
  • -manage customer expectations
  • Report out stats, trends, chronic cases
  • Assist in incident response


There are dozens of projects, data sources, blacklists etc but they vary in format (even timestamps), purpose, channel (IRC, http, ftp)

  • data is frequently missed due to downtime, system availability
  • info integrity is difficult to gauge
  • bugs in feeds data & reporting
  • wildly differing frequency of updates (realtime to monthly)
  • taxonomies are diverse
  • detail level not discrete


Ensuring Focus of CERT-FI

  • What are we not seeing?
  • What should I prepare for?
  • Who is the target of damage & who is just collateral
  • Can the data/sources be trusted?


[side-talk: CERT-FI manages intake and the privacy laws make it difficult to delegate collection to the ISPs]

[side-talk: 5.5 mill population of finland, very high # of folks with internet access, everyone has a cell phone. internet considered a basic human right]


CERT-FI shows ISP incident graphs in comparison to other ISPs. /me: the embarrassment factor is a good motivator

interesting: conficker is still a problem

CERT-FI autoreporter can actually report out incidents per broadband customer (trending)



Abuse Helper is toolkit for CERT and Abuse teams. It is a modular, (hopefully) scalable and robust framework to help you in your abuse handling.

With Abuse Helper you can:

  • Retrieve Internet Abuse Handling related information via several sources which are
    • near-real-time (such as IRC)
    • periodic (such as Email reports), or
    • request/response (such as HTTP).
  • You can then aggregate that information based on different keys, such as AS numbers or country codes
  • Sent out reports in different formats, via different transports and using different timings

Abuse Helper features include:

  • Fully modular (you can utilize different readers, parsers, transports, splitters, combiners in a pipe-like manner)
  • Scalable: you can distribute the work to different machines and different geolocations
  • Observable: you can use your favourite XMPP client to observe the bots at work


Great overall presentation for the rationale to report incidents outside your org

Cover image from Data-Driven Security
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