After action reviews and lessons learned

Useful for analyzing the outcome of conflicts, even info war

thaddeus t. grugq
Dec 3, 2018 · 3 min read

Infowar is open to analysis. There are well known guidelines for effective offensive information warfare, and if there’s sufficient historical data the attacks can be measured for effectiveness. For example, if a threat actor used information warfare against a US election there would be an excellent historical record of the impact of info ops on the population. It is called polling, and it literally measures the impact of information on public sentiment. Polls provide us with a proxy metric for measuring the impact of various information warfare events on the election (to some degree.)

Using what we know about how to wage effective information warfare, we can examine operations and make educated guesses about their impact. If there is polling data available, we can even measure our guesstimates of efficacy against real world impact. This is about as close as we can get to measuring the impact of infowar, and— due to the extensive public documentation — there is no better target for open source analysis than the US election.

There is a perfect case study, the US 2016 presidential election. There is loads of data about information operations, polling for almost everything imaginable, and a huge volume of knowledge on how to conduct proper information war.

First thing we do, let’s skip Lessons Learned & AAR

There are important questions to address when dealing with a lost battle, like “what should we do to prevent a repeat?” One place to start is asking “what went wrong for us, and right for them?”, a good SWOT analysis wouldn’t be the worst idea either. We can get more specific as well:

  • What was the adversary’s most effective strategies, tactics, and tools?
  • Where should we invest resources to mitigate their strengths?
  • Where should we invest resources to address our weaknesses?

This is just a high level preliminary analysis approach, and already it is clear that the 2016 election provides plenty of data for addressing exactly these sorts of questions.

If only someone were actually asking those questions.

At least try to determine the biggest threat before plunging into developing counter threat studies. It’s not soft science subjective impressions, it’s data analytics — the thing computers are good for!

Info war rule 1: best msg + best channel = best shot

There is little mystery to information warfare, it’s about humans and humans have been pretty consistent for thousands of years. The specifics of any information operation are unique, but the foundational logic is universal. Generally speaking it’s pretty much axiomatic that: the best technique is to present the most persuasive message to the target audience over their most credible channel. The devil is in the details, of course, but it’s our starting point.

Knowing that this is the best technique, analyzing the US from the point of view of an info war threat actor we can work out the best messaging, the target audience(s), and their most credible channels. This is literally what political campaigns do.

I’ll leave this as a thought exercise for the reader. Red team the elections from the POV of an attacker.

To test the concealment or otherwise of your position, look at it from the enemy’s point of view. — lesson 19, Defense of Duffer’s Drift

Who needs evidence when we have feelings?

The rush to lay the credit for the results of the the 2016 election directly on social media, and to immediately start developing counter techniques, is premature. I’m just spitballing here, but… maybe figure out what the problems actually were before trying to fix them?

thaddeus t. grugq

Written by

Information Security Researcher :: :: ::

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