De-Coder’s Ring

Consumable Security and Technology

Tag: taxii

Tackling Expensive and Complicated Information Security

Information Security:  It doesn’t have to be so expensive (or complicated!)

 

The Bad News

For Small/Medium Businesses (SMBs), you can’t approach information security the same way your bigger brothers do.  Face it, Capital One has a much larger information security (infosec) budget than the Downtown Credit Union in Powhatan, VA.   Small companies don’t have the same staffing models, technology expertise or highly specialized analysts that focus solely on protecting data.   Sure, there are free and open source tools, for example, but they still require expertise and time to get them up and running, not to mentioned tuned, maintained, updated, etc!

 

Here’s another challenge.  A good information security practice relies on intelligence about threats, attacks, vulnerabilities, etc.  There are open source data sets that can help your SMB know what to look for in network scans, packet matching signatures and queries in your SIEM, but that open source data tends to be stale.  Don’t get me wrong, it’s table stakes.  You NEED to be on the lookout for what Emerging Threats has, but it’s not sufficient.  That data will protect you, but it’s a tiny part of the known bad things out there.

 

Ok, one more ‘bad news’ comment.  There are vendors out there that will sell you cyber threat intelligence (CTI) data.  Some aggregate data from intelligence providers; they’re called TIPs, Threat Intelligence Platforms.  They provide tools and technologies to help you get known intelligence data.  Others research, probe and monitor the internet/private networks looking for ‘things’ that are bad.  They’ll either sell you the data or sell it to an aggregation company who will sell it to you.  They provide a great service, and deserve to be paid for the work they do, but again, this may be pricey and out of your budget.

 

The Good News!

There is a new reality out there.  There are sharing communities being formed to share this threat intelligence data (ISACs and ISAOs).  These groups are focused around specific industries (Health Care, Financial Services, Aviation, etc) and allow a platform to share more RELEVANT data.   This is data that affects your industry, and therefore has a much higher chance of being relevant to you company.   Their cyber intelligence data is target to their industry and typically much more relevant than the data served from large repositories.

 

Size doesn’t always matter.  With finite resources, both technical and human, it’s nearly impossible for SMBs to look out for all the bad things; and why should they?  A bank doesn’t care about a command and control channel for a botnet that is targeting manufacturing equipment.

 

Sharing communities are becoming the KEY source of threat intelligence data for small to mid-size business.  It’s putting the control of the infosec spend back into their hands.

 

By leveraging shared community data as the primary (but still not only!) source of intelligence, we substantially reduce the cost of a comprehensive cyber intelligence and threat mitigation plan.  Once we embrace this new world of industry-specific, relevant cyber intel, we’ll have new ways to connect in a USABLE way.   What’s “usable”?  In order to reap the benefits of your sharing community memberships, you need readily tools that:

  • Don’t require a skilled analyst behind the dashboard 24×7.
  • Don’t require a SIEM to use it.
  • Doesn’t require a knowledge of code.
  • Doesn’t require more than a basic understanding of CTI (STIX, TAXII) terminology

 

Now What

Who’s going to provide a tool like this?  Ha!  I’m not good at keeping secrets, but I’m working on something that will help bring the promise of a sharing community to reality.

 

Stix, Taxii: Understanding Cybersecurity Intelligence

Cyber Intelligence Takes Balls

Cyber Intelligence Takes Balls

Introduction
I spent years building a packet capture and network forensics tool. Slicing and dicing packets makes sense to me. Headers, payloads, etc.. easy peasy (no, it’s not really easy, but like I said, years). Understanding complex data structures comes with the territory, and so far, I haven’t met a challenge that took me too long to understand.

Then I met Taxii. Then Stix. I forgot how painful XML was.

Taxii: Trusted Automated eXchange of Indicator Information

STIX: Structured Threat Information eXpression

FYI:  All the visualizations and screen shots are grabbed from Neo4J. The top rated and most used Graph database in the world.  My work has some specific requirements that I think are best suited with nodes, edges and finding relationships between data, so I thought I’d give it a shot.  Nice to see a built in browser that does some pretty fantastic drawing and layouts without any work on my part.  (Docker image to boot!)

Background
TAXII is a set of instructions or standards on how to transport intelligence data. The standard (now an OASIS standard), defines the interactions with a web server (HTTP(s)) requests to query and receive intelligence. For most use cases, there are three main phases of interactions with a server:

  1. Discovery – Figure out the ‘other’ end points, this is where you start
  2. Collection Information – Determine how the intelligence is stored. Think of collections as a repository, or grouping of intelligence data within the server.
  3. Poll (pull) – (or push, but I’m focusing on pull). Receive intelligence data for further processing. Poll requests will result in different STIX packages (more to come)

I’m not going to go into details on the interactions here, but the python library for TAXII does a good enough job to get you started.  It’s not perfectly clear, but it helps.

STIX defines some data structures around intelligence data.   Everything is organized in a ‘package’.  The package contains different pieces of information about the package and about the intelligence.  In this article, I’ll focus on ‘observables’ and ‘indicators’.  The items I won’t talk much about are:

  • TTPs:  Tactics, Techniques and Procedures.  What mechanisms are the ‘bad guys’ using.  Software packages, exploit kits, etc.
  • Exploit Target:  What’s being attacked
  • Threat Actor: If known, who/what’s attacking?
  • TLPs, Kill chains, etc

Observables

Observables are the facts.  They are pieces of data that you may see on your network, on a host, in an email, etc.  These can be URLs, email addresses, files (and their corresponding hashes), IP addresses, etc.   A fact is a fact.  There’s no context around it, it’s just a fact.

A URL that can be seen on a network

A URL that can be seen on a network

 

Indicators

Indicators are the ‘why’ around the facts.  These tell you what’s wrong with an IP address, or give the context and story about an email that was seen.

Context around an observable

Context around an observable

In the above pictures, you’ll see a malicious URL (hulk**, seriously, don’t follow it).   The observable component is the URL.  The indicator component tells us that it’s malicious.  The description above tells us that the intelligence center at phishtank.com identified the URL as part of a phishing scheme.

Source of data

All security analysts are well aware of some open source intelligence data. Emerging Threat, PhishTank, etc.  This data is updated regularly, and provided in their own format.  Since we’re talking about using TAXII to transport this data, we need an open source/free Taxii source.  Step in http://hailataxii.com

When you make a query against Hailataxii’s discovery end point, you learn the collections and poll URLs.  Additionally, the inbox URL, but we’re not using that today.  (Coincidentally, HAT’s URLs are all the same)

Once you query the collection information end point, you see approximately 11 (At the time of writing) collections.  I will list those below.  From there, we can make Poll requests to each collection, and start receiving (hundreds? Thousands?) of STIX packages.

STIX Package

Since I’m a network monitoring junky, I want to see the observables I can monitor.  Specifically IPs and URLs.  Parsing through the data, I find some interesting tidbits.  Some packages have observables at the top level, and some have observables as children of the indicators.  No big deal, we’ll keep it all and start storing/displaying.

Once it’s all parsed using some custom python (what a mess!), I’m able to start loading my Nodes and edges.  Straight forward, I build nodes for the Community (Hailataxii), the Collection, the Package, Indicators and Observables.  The observables can be related to the Indicator and/or the Package.

Community view from the top down

Community view from the top down

Yellow circle is the community, green circle is the collection, small blue circle is the package (told you it could be hundreds), purple is the indicator and reddish is the observable.

Indicators and Observables

Indicators and Observables

That’s about it!  Don’t forget to check out my last post on Suricata NSM fields to see how some of these observables can be found on a network.

Suricata NSM Fields

Please leave feedback if you have any questions!

 

 

 

 

 

 

 

Collections from Hail  A Taxii:

  1. guest.dataForLast_7daysOnly
  2. guest.EmergingThreats_rules
  3. guest.phishtank_com
  4. system.Default
  5. guest.EmergineThreats_rules
  6. guest.dshield_BlockList
  7. guest.Abuse_ch
  8. guest.MalwareDomainList_Hostlist
  9. guest.Lehigh_edu
  10. guest.CyberCrime_Tracker
  11. guest.blutmagie_de_torExits

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