Sunday, June 9, 2019

Be the CFP review you want to be reviewed by

There are lots of infosec conferences which means lots of CFPs and lots of talks reviewed. I participate in several and figured I would share some of the lessons I've learned.  A caveat: This is highly opinionated.  It's my experience so probably doesn't apply to everyone.  I mostly do small, specialized tracks and conferences so reviewing dozens of talks, not hundreds.


Set yourself up for success.  There are probably 5 things you need to ask for in addition to the speaker info.  If you don't ask for them, you'll end up asking later:
  1. A title
  2. An abstract. Make it clear you'll be printing the abstract!
  3. A bulleted outline. If you don't ask for it in the CFP, you'll end up asking those who don't supply it anyway.
  4. What attendees will gain.  This could be processes, tools, knowledge.  But it's the 2nd most common question I have to ask after asking for an outline.  It also helps distinguish between vendor pitches and useful talks.  Vendors will often speak about how _they_ did something but not necessarily how attendees can do it.
  5. An attachment field.  This will let people share slides, longer outlines, detailed explanations of the talk, etc.  It's important for people who want to answer your specific questions but feel they have more they need to share.

The rating

Set your raters up for success.  You can ask your reviewers to answer lots of questions about talks, but the reality is only a few will be used.  I'd recommend 3 (stolen from bsidesNash:
  1. Content (0-5). How good is the content and the speaker's likely ability to give it.
  2. Applicability (0-5). How applicable is the content to the conference/track/interests of attendees/etc.
  3. Comments/notes to submitters.
Most other questions will likely be another way of asking all or a portion of either question one or question 2.  For example, asking "Has this speaker done a good job in previous talks?" is really just a question to help predict the quality of the content.

1 and 2 could be combined into a single accept-reject range of 0-5.  I like the two as neither I nor other raters I've worked with have had trouble answering both questions for all talks.  Also, they are orthogonal with very little affect of one on the other.

I also recommend 0-5.  Honestly, it can be 0 to anything.  The goal is simply to have a range that normalizes to 0%-100% easily.  1-5 does not.  Is 1-5 20%, 40%, 60%, 80% and 100%?  is it 0%, 25%, 50%, 75%, 100%? It's unclear how it maps out. Terms are even worse. "really bad", "bad", "ok", "good", "really good"?  Is that 0/25%/50%/75%/100%? If so, just use those numbers.  0-5 is easily 0/20/40/60/80/100%.  You could also simply provide a slider from 0 to 1 to allow people to provide the granularity they want.

Every rater should leave some note that can be passed to the submitter.  They may be passed directly, summarized, or aggregated, but you'll need those notes.

Each rater will probably also keep their own notes that do not get shared with the submitter.  It's honestly never clear to raters which comment field will or won't be seen by the submitter in the online review system so you might as well have a single one that will be shared and tell raters to keep private comments offline.  It also helps the raters think about how to communicate their feedback positively.

I'd also recommend making raters provide a rating before seeing the submitter.  Even if they can go change their score after the fact, it helps remove implicit bias based on the submitter. It's ok if a rater rates something, sees the submitter and updates their opinion based on the additional information about the org, previous talks be the speaker, etc that they can clearly articulate.  But you don't want the information about the submitter, their company, experience, other submissions, etc influencing the rating implicitly and you don't want submitter ethnicity, gender, sexual orientation, etc influencing it at all.


There are two things you should do as soon after CFP submission closes as possible, even before rating the talks.
  1. Identify talks that should be moved to another track/reviewer.  
  2. Identify talks where you need to ask the submitter a question to accurately review the talk.
These two things are impossible to accomplish late in the review process.  The first only really applies if you have multiple tracks with multiple raters.  But if you wait to move a submission, more than likely the receiving rater will already be done and won't be interested in another talk.  

For questions, it often only takes minutes, hours or a day to get an answer back, but if the review team is all on the phone making selections, that answer will be too late.  Even if it's to ask for an outline, a more detailed explanation of the submission, or what attendees can expect to learn, most submitters have an answer and can get it to you quickly.

Try to do a pass through the submissions before reviewing and identify any submissions that fall into either category.  Addressing it up front will lead to better outcomes for everyone at review time.

The review

After the ratings are in, it's time to review them to pick the talks:
  1. Start with some mathematical analysis of your talks.  I do it with two scores in this blog, but it works just as easily with a single rating per talk.  Being able to visually check a talk's scores is strikingly helpful.  I've watched it save CFPs that were completely off track, take review meetings that were going no-where and turn them around, and half the time reviewing takes.
  2. Start with the talks that everyone rated perfect or near perfect.  If everyone agreed they're good, don't waste time rehashing it.  Mark these "accept".
  3. Then go to the bottom of the list and work your way up.  Basically, if no-one is willing to fall on their sword for the talk, "reject" it or mark it on the bubble.  (We tend to use "bubble up" or "bubble down".  Up for talks you'd accept if you could.  Down for talks you'd only take if you have to.)  
  4. At some point you're going to get to talks that people liked, but had some flaw.  Raters will be saying "I liked this one, but..." That means you're now into the middle section of the talks.  Go back to the top, after the talks you've already accepted, and work your way down marking "accept", "reject", "bubble up", or "bubble down".  Be biased against accepting.  It's easier to go to the bubble to add talks than to accept more talks than you can take and cut again
  5. Identify backup speakers.  How many is up to you, but I like 1 per track per day.  (Add at least one extra if international speakers are accepted as many things can prevent them from speaking.) I also like to identify someone on staff that will 'just be there' who can be easily found and give a talk (rather than having an empty room) if anything goes wrong.
Also, we tend to give reviewers one veto each; usually a talk they absolutely want, that they can use to overwrite the prevailing opinion of the group.

The notification

Now the part no CFP organizer likes, notifying people (particularly the non-acceptances).  This happens in a few stages:
  1. Notify all of the accepts.  You need all of them to confirm that they can still make it.  Until they confirm, you don't have a talk.  That said, this normally happens pretty quickly.  Accepted people are exciting and generally respond fast.
  2. Notify the bottom 3/4ths of the non-accepts.  You can't notify all because you may have some accepts that can no longer make it and so some of the non-accepts may turn into accepts.
  3. Once you have all the accepts complete, notify the backups and get their confirmation. (Note that if some of your accepts didn't confirm, you may need to move a backup to an accept and a bubble-up to a backup.)
  4. Finally notify any non-accepts that have not been notified.
All non-accepts deserve some feedback on why they weren't accepted.  It could be that the content wasn't the right fit, that the talk felt too complex or not complex enough.  it could be that the reviewers felt attendees wouldn't take a lot away from the talk.  It could be there were grammatical errors in the abstract.  It could simply be there wasn't enough information for raters to be confident it would be a good talk.  But all non-accepts deserve to hear from you.

And the rest of it

At this point, it turns into a speaker management job.  Making sure they have everything they need, know where to be and what to do.  That lasts until the speaker has completed their talk, but that's a subject for another post.

Friday, September 7, 2018

Data Driven Security Strategy

I presented on building a data driven security strategy at RSA this year.  You can find the video here and the slides here.

If there's one thing to take away it's this:
"Strategy is HOW YOU CHOOSE plans to meet your objectives, not the plans you choose. Those plans must be in the context of the rest of security and your organization. And a data driven security strategy is using MEASURES TO CHOOSE."

Data Analysis Template

This is just a quick blog to share my jupyter notebook analysis template.  I analyze a lot of different datasets in a short period, so having the analysis consistent is very helpful.  I'll walk through the sections quickly to share a bit about my process.

Title Section

In the title section, I have a block for any ideas to explore, specific things I intend to do, anything I need to request to be updated in the data, and any notes about the data.  These are all bulleted text boxes.

This section is VERY helpful for working on multiple datasets.  it's easy to forget what you were going to do or what you've done and the summary up front helps get you back in place.


next is preparing the data.  No data comes ready for analysis.  Here I have blocks to read in the data, clean the created dataframe, save it to an R data (Rda) object on disk, and then, the next time I need it, I just load the Rda and skip the cleaning.


The analysis section is basically filled with mini experiments.  each chuck is one.  As such, it's important that each have a bit of information in comments at the top of it:

  1. A description of the hypothesis being tested or explored.  Something like "looking at the distribution of the periodicity of events".
  2. Once it's done, describe the results.  Yes, the results should describe the results but you'll thank past you if you write down what you got from the analysis when you did it.  Something like "it looks like the periodicity is bimodal with one mode representing X and another representing Y."
  3. Add a comment with a UUID.  Seriously.  Every. Single. Block.  If it's something interesting you're going to put it in a document or a blog or something.  You want to be able to track it from beginning to end.  (Ours track from the report, through several drafts of the report, through drafts of the sections, to a figures rmarkdown file that generates all the figures, to an exploratory report where we created the original analysis.)  Seriously.  If you like it then you shoulda put a UUID on it.
  4. Now you can actually write the analysis code


This is where I put all of the extra stuff.


I always have a testing block.  Throughout the analysis, you'll spend a lot time testing stuff to make it work, (or simply looking up things like the dimensions of your data and the column names).  Putting those in a testing block keeps you from coming back later and wondering what the block in your analysis was there for.


Sometimes you have big, ugly, lookups.  putting them at the top clogs the Preparation section, so I tend to put them at the bottom.  You'll remember you forgot to run them when your analysis fails.


Really a parking lot for anything you don't want in another section, but don't want to delete.

Ultimately, if I were doing full modeling, I'd probably want a template that follows the process outlined in Modern Dive.  However, for someone just getting into analysis, hopefully this helps!

Sunday, August 19, 2018

Game Analysis of the 2018 Pros vs Joes CTF at BSidesLV


Capture the Flag (CTF) contests are a staple of security conferences and BSides Las Vegas is no exception.  However the Pros vs Joes (PvJ) CTF I help support there is a bit unique.  Not only is it a blue vs blue CTF with red aggressor and gray user teams, but the game dynamics are a fundamental development point for the CTF team. (There's a lot more to it such as it's educational goal or that we allow blue teams to attack each other on the second day.  You can read more about it at

Game Dynamics

When we say 'game dynamics', we mean a couple of things.  First we mean what's scored and how much.  In our case that is currently four things:

  • hosts (score given to teams for maintaining service availability)
  • beacons (score deducted when the red team signals a host is compromised)
  • flags (score deducted when the red team breaches specific files)
  • tickets (score deducted when the gray team is not being appropriately supported)

At a more fundamental level though, we mean the scenario the CTF is meant to represent.  As a blue team CTF, we try and simulate the real world.  As such, starting last year, we began to transition our game model to simulate an economy.  Score is not granted so much as transferred.  For example, the gold team pays the gray team for accomplishing some task, then the gray team pays a portion of that score to the blue team for maintaining the services necessary to accomplish that task.  Alternately, when the red team (or another blue team) installs a beacon, the score isn't lost, but instead transferred to the team that placed the beacon.

Beginning with last year,  we have started to then simulate the way we expect the game to run.  This year we have also captured detailed scoring logs.  This blog is about our analysis of the score from this year's game and how it helps us plan for the future.


The first thing we do is create a game narrative and scoring profile for the game.  The profile is the servers that will come online, go offline, and how much they will be scored per (5 minute) round.  It is picked to produce specific outcomes such as inflation (to decrease point value early in the game when teams are just getting going and to allow dynamism throughout the game).

We then try and build distributions of how likely servers will be to go offline, how likely beacons will be and how long they will last, and how many flags will be found.  This year we used previous years simulations and logs as well as expert opinion to build the distributions.   The distributions we used are below:

### Define distributions to sample from
## Based on previous games/simulations and expert opinion
# H&W outage distributions
doutage_count <- distr::Norm(mean=8, sd = 8/3)
doutage_length <- distr::Norm(mean=1, sd = 1/3)
# flag distributions
dflags <- distr::Norm(mean=2, sd= 2/3) # model 0 to 4 flags lost with an average of 2
# beacon distributions
gamma_shapes <- rriskDistributions::get.gamma.par(p=c(0.5, 0.7), c(0.75, 4)) # create a gamma distribution to draw number of tickets from
dbeacons_length <- distr::Gammad(shape=gamma_shapes['shape'], scale=1/gamma_shapes['rate']) # in hours
dbeacon_count <- distr::Norm((4-3)/2+3, (4-3)/3)
Based on this we ran Monte Carlo simulations to try and predict the outcome of the game.

First, we analyzed the expected overall score.

 Next we wanted to look at the components of the score.

Finally we wanted to look at the distributions of potential final scores and the contributions from the individual scoring types

The Game

And then we run the game.

The short answer is, it's VERY different.  We had technical issues that prevented starting the game on time.  We were not able to complete some development that prevented automatic platform deployment, some hosts were not available, and some user simulation was also not available. This is not a critique of the development team who did a crazy-awesome job both rebuilding the infrastructure for this game in the months leading up to it as well as dynamically deploying hosts during the game.  It's just reality.  The scoring profile was built for everything we want.  I am pleased with how much of it we got on game day.

The Scoreboard

The Final Scoreboard

You can find the final scoreboard and scores here.  It gives you an idea of what the game looked like at the end of the game, but doesn't tell you a lot about how we got there.  I'm personally more interested in the journey than the destination so that I can support improving the game narrative and scoring profile for the next game.

Scores Over Time

The first question is how did the scores progress over time?  (You'll have to forgive the timestamps as they are still in UTC I believe.)   What we hoped for was relatively slow scoring the first two hours of the game.  This allows teams the opportunity to make up ground later.  We also do not want teams to follow a smooth line or curve.  A smooth line or curve would mean very little was happening.  Sudden jumps up and down, peaks and valleys,  mean the game is dynamic.

What we see is a relatively slow beginning game.  This is due to beacons initially being scored below the scoring profile and one of three highly-scored puzzle servers being mistakenly scored lower from it's start late in day 1 until it was corrected at the beginning of day 2.

We do see an amount of trading back and forth.  ForkBomb (as an aside, I know they wanted the _actual_ fork bomb code for their name, but for this analysis text is easier) takes an early lead while Knights suffer some substantial losses (relative to the current score).  Day two scores take off.  The teams are relatively together through the first half of day 2, however, Arcanum takes off mid-day and doesn't look back.

The biggest difference is that when teams started to have several beacons, as part of their remediation they tended to suffer self-inflicted downtime.  This caused a compound loss of score (the loss of the host scoring they would have had plus the cost of the beacons).  We did not account for this duplication in our modeling, but plan to in the future.

Ultimately I take this to mean scoring worked as we wanted it to.  The game was competitive throughout and the teams that performed were rewarded for it.

It does leave the question of what contributed to the score...

Individual Score Contributions

What we expect is relatively linearly increasing host contributions with a bit of an uptick late in the game and linearly decreasing beacon contributions.  We also expect a few significant, discrete losses to flags.

What we find is roughly what we expected but not quite.  The rate of host contribution on day two is more profound than expected for both Paisley and Arcanum suggesting the second day services may have been scored slightly high.

Also, no flags were captured.  However, we do have tickets which were used by the gold team to incentivize the blue teams to meet the needs of the gray team.

The biggest difference is in beacons.  We see several interesting things.  First, for a period on day two, Knights employed a novel (if ultimately overruled) method for preventing beacons.  We see that in the level beacon score for an hour or two. We also see a shorter level score in beacons later on when the red team employed another novel (if ultimately overruled) method that was significant enough that had to be rolled back.  We also see how Arcanum benefited heavily from the day 2 rule allowing blue-on-blue aggression.  Their beacon contribution actually goes UP (meaning they were gaining more score from beacons than they were losing) for a while.  On the other side, Paisley suffers heavily from blue-on-blue aggression with significant beacon losses.

Ultimately this is good.  We want players _playing_, especially on day 2.  Next year we will try to better model the blue-on-blue action as well as find ways to incentivize flags and provided a more substantive and direct way for the gray team to motivate the blue team.

Before we move on, two final figures to look at.  The first lets us see individual scoring events per team and over time.  The second shows us the sum of beacon scores during each round.  It gives an idea of the rate of change of score due to beacons and provides an interesting comparison between teams.

But there's more to consider such as the contributions of individual hosts and Beacons to score.


The first thing we want to look at is how the individual servers influenced the scores.  What we want to see is starting servers contributing relatively little by the late game, desktops contributing less, and puzzle servers contributing substantially once initiated.  This is ultimately what we do see.  (This was the analysis, done at the end of day 1, that allowed us to notice puzzle-3 scoring substantially lower than it should.  We can see it's uptick on day 2 as we correct it's scoring.)

It's also useful to look at the score of each server relative to the other teams.  Here it is much easier to notice the absence of the Drupal server (removed due to technical issues with it).  We also notice some odd scoring for puzzle servers 13 and 15, however the contributions are minimal.

More interesting are the differences in scoring for servers such as Redis, Gitlab, and Puzzle-1.  This suggests maybe these servers are harder to defend as they provided score differentiation.  Also, we notice teams strategically disabling their domain controller.  This suggests the domain controller should be worth more to disinsentivize this approach.

Finally, for the purpose of modeling, we'd like to understand downtime.  It looks like most servers are up 75% to near 100% of the time.  We can also look at the distributions per team.  We will use the distribution of these points to help inform our simulations for the next game we play.  We are actually lucky to have a range of distributions per team to use for modeling.


For the purpose of this analysis, we consider a beacon new if it misses two scoring rounds (is not scored for 10 minutes).

First it's nice to look at the beacons over time.  (Note that beacons are restarted between day 1 and day 2 during analysis.  This doesn't affect scoring.)  I like this visualization as it really helps show both the volume and the length of beacons and how they varied by team.  You can also clearly see the breaks in beacons on day two that are discussed above.  

The beacon data is especially helpful for building distributions for future games.  First we want to know how many beacons each team had:

Day 1:
  • Arcanum - 17
  • ForkBomb - 24
  • Knights - 18
  • Paisley - 21
Day 2:
  • Arcanum - 13
  • ForkBomb - 17
  • Knights - 29
  • Paisley - 34

We also want to know how long the beacons last. The aggregate distribution isn't particular useful. However the distributions broken out by teams are interesting.  They show substantial differences between teams.  Arcanum had few beacons, but they lasted a long time.  Paisley had very few long beacons (possibly due to self-inflicted downtime).  Rather than be a power law distribution, the beacons are actually relatively even with specific peaks.  (This is very different from what we simulated.)


In conclusion, the take-away is certainly not how any given team did.  As the movie "Any Given Sunday" implied, sometimes you win, sometimes you lose.  What is truly interesting is both our ability to attempt to predict how the game will go as well as our ability to then review afterwards what actually happened in the game.

Hopefully if this blog communicates anything, it's that the scoreboard at the end simply doesn't tell the whole story and that there's still a lot to learn!

Future Work

This blog is about scoring from the 2018 BSides Las Vegas PvJ CTF so doesn't go into much detail about the game itself.  There's a lot to learn on the PvJ website.  we are also in the process of streamlining the game while making the game more dynamic.  As mentioned above, the process started in 2017 and will continue for at least another year or two.  Last year we added a store so teams can spend their score.  We also started treating score as a currency rather than a counter.

This year we added additional servers coming on and off line at various times as well as began the process of updating the gray team's role by allowing them to play a puzzle challenge hosted on the blue team servers.

In the next few years we will refine score flow, update the gray team's ability to seek compensation from the gray team for poor performance, and additional methods to maximize blue team's flexibility in play while minimizing their requirements.  Look forward to future posts as we get the details ironed out!

Sunday, July 22, 2018

A Year Not Drinking

With Blackhat, Defcon, and BSides Las Vegas coming up, it seems like an appropriate time for a quick blog on alcohol.  In 2017, for my birthday I took a year off drinking.  Now that my birthday is past, I figured I'd share a bit about it.


Honestly, I felt I was drinking too much.  There was always an excuse to drink. It was a holiday.  Friends were over.  My wife and I wanted to go out.  There was something interesting to taste. etc.

Also, it became an end-of-day thing.  Have a beer to relax after work.  Just adding that up alone becomes a number not to be proud of.

I also wanted to see if it changed how I felt.  Would I feel more healthy? Would I feel smarter?  Since alcohol is a depressant that can last a week+ in your brain, would I be in a better mood?

And I wanted to try and save some money.

It also helped that I read a book where the main character didn't drink.  I think it provided subconscious acknowledgement that it could be done as well as giving some ideas as to how.

What it took

It was easy.  much easier than I expected. My goal wasn't to avoid alcohol like an allergy, but just not to have a full drink.  It also helped to have a goal.  "I'm not going to drink a full drink until at least X."  I could easily tell people "I'm taking a year off drinking" and didn't get much pressure to drink after that.  

To make it work, I had to have something else to drink though.   (I drink a LOT of fluids.  2-4 liters of hot tea during the work day.) I don't like sweet drinks or fruity drinks.  I also need variety and don't drink caffeine after like 7 at night, so that kinda limits my options.  What I did find was:
  • Herbal Tea - TONS of variation here. Better during the winter when warm drinks are nice. I wish someone would make condensed herbal tea similar to what's available for ice tea.
  • Bitters and Tonic - This was my go-to.  I have about 20 bitters of various flavors and a soda stream (modded w/ a real CO2 tank) now.  I can drink these for ever and a day with a ton of variation.
  • Water with sliced fruit, then carbonated - It turned out this was great too.  Cut a cucumber and a grapefruit into the water and let it sit a day.  Then bottle it up and carbonate it.
  • La-croix - Not sweet and great flavors

Positive Impacts

First, I did feel like it was easier to solve complex challenges.  The mental gymnastics just seemed a bit easier.  Plus, it saved a BUNCH of money (minus stocking up the bitters).  I'm sure the long-term effects of not poisoning myself regularly are good though I haven't quite termed long enough to find out.

Another interesting impact was social interactions were more productive.  Instead of meeting over beer at the end of the day in a dark, loud place, I'd meet people in the morning or mid-day over tea.  We tended to get a LOT more done.

Negative Impacts

On the other hand, there's a LOT less to do. A lot of the things that seem like fun (many times vague 'going out somewhere' concepts) just aren't exciting if you aren't drinking.  Going downtown is now kinda 'bla'. Going out to bars is pretty much out of the question. (You could, but why?)  So now when my wife and I try to find something to do on a free night, we actually have some trouble figuring it out. (That said, it may also be that because we have kids and so free nights are so rare we're not sure what to do with them.)

More stress.  The reality was drinking was relieving stress. (Obviously not in a good way, but it was.)  Life not drinking is much more stressful.

Also, I consumed a LOT more sugar.  Probably linked to the last point about stress frankly.  Instead of drinking alcohol, easting sweets became a way of dealing with stress, which I'm pretty sure is also not healthy.

When I drink

A side affect of this is it became very clear _when_ I drink.  
  • First was after work to relieve stress.  
  • Second were social events, basically as something to do when meeting people.  
  • Third were celebrations.  These tended to be heavier drinking.  The problem is that the world makes sure there is always something to celebrate.

Going Forward

So my plan going forward.  I don't plan on not drinking at all but I do plan on drinking less.

I plan to pick the days to drink in celebration way ahead.  Probably my birthday and my wife's birthday, but likely nothing else.  I think it's very important to do this ahead of time so that I have an idea how often it's happening throughout the year.  It's very easy to impulse-celebration-drink and if I don't think about the year ahead, looking back on the year it's easy to find out I drank way more than I would have if I'd planned ahead.

Socially, I think I'll only drink in rare cases.  And when I do, only make it one drink.  Last year, I wish I'd had a drink of scotch with my father and brothers at home at Christmas.  On the other hand, I probably won't drink when meeting up with people in Vegas.  Those will be tea or tonic and soda type things depending on the time of day.

I'm not going to swear off tastings, particularly when offered.  But on the other side, I'm not going to take an entire drink just to taste it.  It's silly not to try interesting things, but it can't be an excuse to drink more.

My plan is to completely stop drinking after work.  It's just too much of a slippery slope.  Instead i plan to get out to the gym more and meditate (I pray, but you do you) to relieve stress.


So as you prepare for Vegas, drink the amount you want.  But don't feel it's something you have to do.  Many people don't and everyone I've spent time around has been understanding.  And recognize that drinking won't make you cooler/more of a hacker/give you a fuller experience.

Now to figure out what to do about the sweets.

Wednesday, June 20, 2018

Good Blackhat/Defcon/BSides Las Vegas Advice

Every year new people come to Las Vegas for the triumvirate of conferences, Blackhat, Defcon, and BSidesLV, better known as hacker summer camp.  If you've never been, it can be an intimidating experience.  To help those who might be interested in some suggestions, I've compiled the list below from my own experience (starting with Defcon 13).

  1. Think about what you want to get out of it. BH and DC are BIG. You can easily spend the entire time just wondering. You'll learn a lot about the conferences, but not necessarily security.  Plan half a day to walk around and just see things, but have a better plan after that. Pick a few talks to go to (and wait in line for).  Pick a village to sit in all day (I'm partial to BSidesLV Ground Truth as I help run it).  Schedule to meet people (something I do a lot).
  2. Thursday is a down day.  The schedule says there's stuff going on, but not a lot.  DON'T plan to wonder on Thursday.  Nothing will be ready.  Plan to do something on the schedule. Meet up with people.  Volunteer. Visit the Grand Canyon.  But don't just assume you'll have stuff to do.
  3. Wear shorts. Most people will be in black t-shirts. You don't have to. a t-shirt, polo, or even short sleeve button-down is fine. Just don't do slacks and long sleeves. it's HOT.
  4. Wear comfy shoes but don't stress over it. Whats comfortable at home will be comfortable there. I wear a pair of dock shoes (sparreys).
  5. Don't rent a car unless you'll be driving out away from las vegas (to the grand canyon or such). Instead get a week ticket for the Deuce (double decker bus on the strip) 
  6. Don't worry about your electronics. I can't find documentation of a single breach related to a compromise at BH/DC. The BH/DC noc operators have been doing it longer than those trying stuff and are generally safe. Still, patch all your stuff before going and try to use a VPN for all communication including mobile. (There will be lots of fake cell towers though the police have been cracking down on it a bit I think.)
  7. I prefer to get a microwave and get some food, especially breakfast food, to eat in my hotel room. Food tends to be a huge portion of the cost of going and eating a bagel and some fruit and yogurt in your room for breakfast can help keep you grounded.
  8. Speaking of being grounded, Las Vegas is a city of haves and have nots. You'll be living the good life, pampered by vendors, etc. Consider giving to those who don't have by volunteering at or donating to the Las Vegas Rescue Mission ( or such.
  9. Speaking of parties, go to one, but most are going to be either loud, over-crowded, and obnoxious or hard to get into and pretentious. (There are a very few that facilitate socializing like the bsides las vegas pool party.) Better though to go to bed early and try and have breakfast with new people each day.  I generally follow groucho marx's rule for parties.
  10.  Go to some talks. Lots of people put a lot of work in to talk about lots of things. And not just the big showie talks. Those tend to be spectacle. Instead find lesser known people talking about their passion. And plan to get in, talks have waiting lines that can be LONG. Especially at defcon.
  11. And see a show or two. Go to the day-of discount booth and get tickets to some big show (Every casino has one) but also to the little lounge shows (Burlesque, Hypnotist, Comedy, etc). Ask the hotel what smaller shows they have and what others are around. 
  12. don't bother gambling. Your time around many of the best security professionals in the world is limited. Don't waste it on throwing your money away. You can do that any time. 
  13. Don't plan to go back to your hotel room. Put everything you need for the day in a bag and go (water, snacks, clothes, batteries, etc). That includes electronics, extra power, water, and clothes if changing for the evening, (whether an extra t-shirt to replace your sweaty one or your slacks for a nice evening out).  It can take you an hour to get back to your hotel and back out again and you don't want to waste that.
  14. Take one set of nice clothes (business casual, maybe a tie and jacket, in case you want to go somewhere nice one night. Make SURE to bring close-toed shoes. Some nice restaurants will refuse you in sandals. (goes for women too). 
  15. Bring extra power. The wireless environment is FLOODED. it will DRAIN all your devices. I can drain the battery in every device I bring 2-3 times a day. USB batteries are a MUST and if you don't need the wifi on on your device, just leave it off.
  16. Read this blog: How to Converse Better in Infosec and this one: How to Handle Being Questioned on asking & receiving questions.
  17. Bring a big, boxy suitcase so if you find cool stuff you can bring it back.  (I've flown servers back before.)
  18. Remember that blocks in Las Vegas are about a mile.  Don't look at google maps and think "it's only one block".
  19. If you see someone you recognize in infosec (a speaker you look up to, a company CEO, etc), walk up and say "Hi.  I'm <your name>.  I love your work. I'm curious about what you're interested in these days."  If they excuse themselves, that's fine.  They may be in between things. (I've heard of people taking an hour or more to get from the hotel lobby to their room because they meet so many people that know them along the way.)  If they mumble something, that's ok.  After talks particularly speakers are worn out mentally.  If they tell you off, that's ok.  Some people are jerks.  But none of those things cost you anything and the potential for a good conversation is HUGE.
  20. If you see someone you _don't_ recognize, say "Hi.  I'm <your name>.  What brings you here?"  Again, they could not talk to you for any number of reasons, but I have met all sorts of super interesting people just being willing to meet with whoever is willing to meet with me.
  21. Lots of people like badges.  Some are super cool.  I'll be honest, all my old badges, electronic or not, are hanging in my closet taking up room I need for other things.  If you want a fancy defcon badge, get a badge early as they tend to run out and then hand out paper.  If I get a fancy badge and they run out, I tend to trade it to someone whose there for the first time who doesn't have one.  I've got enough badges and your first defcon badge is special.
  22. The minimum rule is 1 shower, 2 meals, and 3 hours of sleep.  Personally, I get a full nights sleep, I eat all my meals, and of course shower and use deodorant.
I'm sure there's much more I'm forgetting.  I'll update it if I think of anything else.  

Also, you can search twitter for #gooddefconadice (or #baddefconadvice) but take it with a grain of salt.

Wednesday, April 25, 2018

Presentation timing like a BOSS


This year as I prepared for my RSA talk, Building a Data-Driven Security Strategy, I decided to do something slightly different. I modeled my timing practice after video game speedrunners. Ultimately it was a good experience that I plan to repeat. Here's the story.

What is a speedrun?

One thing I do to relax is watch video game speedruns. This is when people try and complete a video game as quickly as possible. (It’s so competitive that on some improvements in records are measured in terms of frames and some players spend months or even years, playing hundreds of thousands of attempts, to try and beat a record.)

One thing they all have in common is they use software to measure how long the attempt (known as a run) takes. Most break the runs down into sections so they can see how well they are doing at various parts of the game. To do this, they use timing software which measure their time per section, and overall time. Additionally, each run is individually stored and their current run is compared to previous runs.

Speedrunning for presenting

This struck me as very similar to what we do for presentations, and so for my presentation, I decided to use a popular timer program, livesplit (specifically livesplit one) to measure how well I did for each practice run of my presentation. Basically, every time I practiced my presentation, I opened the timer program and at each section transition, I clicked it. While the practice run was going, the software would indicate (by color and number) if I was getting close to my comparison time (the average time for that section). Each individual run was then saved in a livesplit xml file (.lss). I’ve attached mine for anyone that wants to play with it here.

Figure 1

The initial sections analysis (Figure 1) showed some somewhat dirty data. First, there probably shouldn’t be a run -1. Also, runs 4 and 5 look to not be complete. So we’ll limit our analysis to runs 7 to 20. For some reason, The introduction section in runs 9, 14, and 18 seems to be missing, so we’ll eliminate those times as well. It’s worth noting that incomplete runs are common in the speedrunning world and so some runs where no times are saved will be missing and other runs where the practice was cut short will exist as well. It’s also relevant that ‘apply’ and ‘conclusion’ were really mostly the same section and so I normally let ‘apply’s split run until the end of the presentation, making ‘conclusion’ rarely occur at all.


Figure 2 and 3 look much better. A few things that start popping out. First, I did about 20 practice runs though the first several were incomplete. Looking at Figure 2, we see that some sections like ‘introduction VMOS and Swot’, ‘apply’, and ‘data driven strategy’ decrease throughout the practice. On the other hand, ‘example strategies’ and ‘example walkthrough’ increased at the expense of ‘define strategy’. This was due to pulling some example and extra conversation out of the former as feedback I got suggested I should spend more time on the latter. Ultimately it looks like a reduction of about 5 minutes from the first runs to the final presentation on stage (run 20).

The file also provides the overall time for each time. Figure 4 gives a quick look. We can compare it to Figure 3 and see it’s about what we expect. A slight decline from 45 to 40 minutes in runtime between run 7ish to run 20.

Figure 4

Figure 5

We can also look at actual practice days instead of run numbers. Figure 5 tells an interesting story. I did some rough tests of the talk back in December. This was when I first put the slides together in what would be their final form. Once I had that draft together, I didn’t run it through January and February (as I worked on my part the DBIR). After my DBIR responsibilities started to slow and the RSA slide submission deadline started to come up, I picked back up again. The talk was running a little slow at the beginning of march, however through intermittent practice and refinement I had it down where I wanted it (41-43 minutes) in late March and early April. I had to put off testing it again during the week before and week of the DBIR launch. After DBIR launch I picked it up and practiced it every day while at RSA. It was running a little slow (2 runs over 43 minutes) at the conference, but the last run the morning of was right at 40 minutes with the actual presentation coming in a little faster than I wanted at 39 minutes.

We can take the same look at dates, but by section. Figures 6 and 7 provide the story. It’s not much of a difference, but it does put into perspective the larger changes in the earlier runs as substantially earlier in the development process of the talk.


Ultimately I find this very helpful and suspect others will as well. I regularly get questions such as “how many times do you practice your talk?” or “how long does it take you to create one”. Granted it’s a sample size of 1, but it helps give an idea of how the presentation truly evolved. I can also see how the changes I made as I refined the presentation affected the final presentation. Hopefully a few others will give this a try and post their data to compare!

Oh, and for those adventurous types, you can see the basic analysis I did in my jupyter notebook here