0:53

How's it going , Jackie ? It's great to get you

0:55

on the podcast finally . I feel

0:57

like it's been a while , but I'm

0:59

really excited for our conversation today .

1:02

Yeah , super happy to be here . It's

1:05

beautiful out in Arizona , so it's

1:07

a nice day . I'm in a good mood .

1:10

Oh , I know , A good friend

1:12

of mine moved to Arizona maybe

1:15

a year and a half ago and now he

1:17

always gives us updates like oh

1:19

, it's a little bit chilly , today it's 60

1:21

degrees . You know , like

1:24

man , you can leave me

1:26

alone , it's negative 20 where

1:28

I'm at .

1:31

I grew up in New Hampshire . For the first

1:33

10 years I lived in New Hampshire I lived in a little town

1:35

called Berlin , which is about 45

1:37

minutes in Canada . So I have definitely

1:40

walked to school in like

1:42

10 , negative 15 times a week before

1:44

I empathized with you .

1:46

Yeah

1:50

, when I was in college actually

1:52

, you know , I worked for the police

1:54

department , the campus police department , and

1:57

it was like negative 40 . And

2:00

I was one of like five

2:02

or 10 people that had to actually

2:04

go in as like a central personnel and

2:07

which was crazy , because they had a

2:09

student be an essential personnel and

2:13

the police chief actually sent a squad

2:15

card to my dorm to pick me

2:17

up because he said that it was too unsafe

2:19

for me to walk a quarter of a mile .

2:22

Yeah , yeah . I believe

2:24

that the thing that finally

2:26

broke me was we had an ice storm in 2008

2:29

in New Hampshire that left an inch and a half of

2:31

ice on everything in New Hampshire

2:33

and I didn't have power for six

2:35

or seven days . I lived in Manchester

2:38

. I didn't live in like nowhere in New Hampshire . I lived in

2:40

the biggest city in New Hampshire

2:42

and I was just like this place is not inhabitable

2:44

. Nobody should live here , and I literally

2:46

just sold all of my stuff and moved to California

2:49

. I've never been there . I didn't know anything

2:51

about it . I found a roommate on a

2:54

forum for motorcycles and I

2:56

ride motorcycles on my way there and I was just sort

2:58

of never living anywhere that does this .

3:01

Wow , that is so

3:03

crazy An inch and a half of ice

3:06

.

3:08

It was insane . I've never seen anything

3:10

like that before . It was so crazy

3:12

.

3:14

Yeah , I would move too At that

3:16

point . I would move too my gosh

3:18

, but

3:22

it's in Arizona today . So I'm

3:24

happy . Yeah , it's

3:27

very tempting to go to Arizona . My

3:31

wife and I we like

3:33

colder weather I

3:36

wouldn't say insanely cold weather

3:38

, but we prefer a good

3:42

variation in the seasons and

3:44

whatnot . My buddy was telling me that Flagstaff

3:46

Arizona is a good

3:49

mix of the seasons , and

3:51

so now I'm

3:53

on the mission of convincing my wife . Hey

3:56

, we should go check out Flagstaff Arizona

3:59

and see how it is . Now I'm

4:02

on that 10-year mission .

4:04

I can see snow from where I'm standing , so

4:06

there's a mountain outside . I live in

4:08

Tucson . There's a mountain just outside Tucson called

4:11

Mountain Lemon . It actually is a ski area . You

4:13

can ski for a couple months out of the

4:15

year and I can see it from like . So

4:18

it's less than an hour from my house to the

4:20

mountain , so you can get to

4:22

call by there if you really

4:25

want to , you just don't have to live in

4:27

it . I hate scraping my windshield . It's

4:31

one of those stupid things that you're like it's such a small

4:33

thing to be like , so it's not , but

4:35

it's just one of those things that it's like

4:37

7.15 in the morning and you're exhausted

4:40

and you only had a cup of coffee and you're trying to get

4:42

to work and you're just like I

4:44

hate this , I hate everything . But then again

4:46

, I've never burned my ass on

4:48

a frozen windshield In

4:51

Arizona . Half a year I literally have

4:53

to keep a towel on my car seat so

4:55

that I don't get second degree burns on my butt

4:58

.

4:58

So just straight out to everything

5:00

. Yeah , yeah

5:03

, absolutely . Well , jackie

5:05

, I'm really interested in

5:07

hearing about how you got an IT

5:09

, what made you want to go into IT

5:12

overall and then what made you want

5:14

to maybe make a I guess

5:16

maybe a slight switch into

5:19

security and focus more on security

5:21

.

5:22

Yeah , so I had a really weird , like

5:24

meandering career . I've dropped out of college

5:26

three or four times at

5:28

least .

5:29

Oh geez .

5:30

Yeah , so I started with psychology and

5:33

dropped out because I was poor and

5:36

poor to afford tuition . And I actually did

5:38

a stock broker when I was 20 . So I

5:40

went through an interview about higher class

5:42

edelides . I worked as a stock broker

5:44

through the financial crisis , moved

5:47

over to SVB and managed

5:50

cash for companies , and

5:52

so it was like I

5:54

had kids and I was doing the whole like quarter-life

5:56

crisis thing everybody does and like doing

5:59

psychedelics and like questioning mindsets

6:01

on the planet . And I

6:04

got an economics and finance degree because

6:06

I was working in finance and

6:08

I really wanted to learn how to write Python . So

6:10

I was like , well , what was the easiest way to work , how to write Python

6:12

? I was like , well , I already understand economics and

6:15

statistics , so maybe data science

6:17

would be a good idea . It seems to be an

6:19

up and coming field right now

6:21

. This is like 2017

6:24

. It was like you know , also

6:26

, it would be applying Python to something I already

6:28

understand . So I did a data science boot count

6:31

and I pushed my final

6:33

project in my GitHub and

6:36

it's got me jumped and he said hey , I am

6:38

the data science person at this sim

6:41

startup and we're looking for somebody

6:43

to write algorithms for like anomaly detection

6:46

and user behavior analytics

6:48

, are you interested ? And I

6:50

really thought about working in cameras

6:52

security , which is weird because

6:55

I was always like my mom used

6:57

to drop me off at Radio Shack when she grocery

6:59

shopped . So I've never had to use a computer

7:01

since I was like three and I

7:03

always like I don't know , it's so strange , and

7:05

like I actually grew up in the military on

7:07

a couple of intelligence phases , so

7:09

I've always been kind of weirdly adjacent

7:11

to security , those types of things

7:14

. That's how I initially got into it

7:16

and then I

7:19

think , personally , one

7:22

of the things I love about security is , well

7:25

, the gender disparity isn't a good thing

7:27

. The bathrooms are always clean for me and there's

7:29

never a line , so like that's a good . No

7:32

, no , I find more

7:34

than anything , more than any industry I've worked

7:36

in , security is very much a meritocracy

7:39

, right , it is a hundred percent a meritocracy

7:41

and it's a really interesting industry

7:43

and that people don't actually need to like

7:45

you , they just need to trust you . And

7:47

so you have all of these crazy like neurodivergent

7:50

, like not necessarily super socially

7:52

adept people . But

7:54

I did like it , just felt

7:56

like home as soon as I went to my first

7:58

like DEF CON . You know my first DEF

8:01

CON was mind blowing . It was like , oh my God , these are my

8:03

people Like , and it's

8:05

that everybody kind of wants to solve the same problems

8:08

and I've

8:10

always had problems in regular industries

8:12

where people think I'm crazy because

8:15

I don't think the way that neurotypical

8:17

people think , whereas in security people are

8:19

like , oh , your brain works differently than mine

8:21

. Come help me with this problem , because between the

8:24

way your brain works so it just seems

8:26

to be an industry that's significantly

8:28

more open to like

8:30

everybody brings their own special talents

8:33

. Yeah , and so I ended

8:35

up moving from the

8:38

random elementary school in my living

8:40

room during the pandemic because I have three kids

8:42

. And then after that I was like

8:44

you know how do I combine cybersecurity

8:46

with my finance background ? And

8:49

they ended up becoming an industry analyst . So I covered , like

8:51

Sims or XDR , all

8:53

those kind of like analytical platforms for

8:55

S&P slash

8:57

survival research , and that was

9:00

how critical found me is . They pitched

9:02

the companies to me and I was like I love

9:04

this . So I hate regex

9:06

. It's like a beta by existence , because

9:08

when I became a data scientist nobody told

9:10

me that before you can write an algorithm , you

9:12

have to get this like beast

9:15

of assist along file into something that you

9:17

can actually use , and there were no good tools

9:20

for doing that at the time . So I literally spent like

9:22

weeks on regex when I was a data

9:24

scientist . So when I saw Kerbal I was

9:26

like this is amazing . But at the time they

9:28

were kind of calling it an observability pipeline

9:31

, which is what it was it's great for

9:33

, but I was like I don't know , I'm sorry , but he really needs

9:35

a looking security the

9:39

thing we see like other people know

9:41

exactly how important their jobs

9:43

are to security . But security people are

9:46

trying to work observability .

9:49

Isn't that like right ?

9:51

Yeah , so , but so I thought it was

9:53

a very long-winded story , but I think it's important

9:55

because I have not met many people in

9:57

security who came here directly , right

10:00

, like , we all have these like weird backgrounds

10:02

and like the diversity of background is

10:04

usually what makes you good in

10:06

security , because when you're dealing

10:08

with , say , like , a financial services client

10:11

, you need to have some background in that to

10:13

really understand the nature of the threats that you're dealing

10:15

with .

10:15

So , yeah , yeah , it's

10:18

a really good point . You know I

10:21

have a lot of people reaching out to me , you

10:23

know , constantly asking me you know how

10:25

do I get into security and that

10:27

sort of thing , right , and they kind of want that

10:29

you know , 12 , 18 month path

10:32

into security . And

10:35

you know I always tell them you

10:37

don't want that path because security

10:39

is so stressful and it requires so

10:41

much context outside of security

10:44

that you just simply

10:46

wouldn't get . You know

10:48

, if you went straight into security , yeah

10:51

, you

10:54

know , like you said , right , you kind of have to know

10:57

how the financial industry works

10:59

, the kinds of systems that they have

11:01

in place , the methods and all

11:03

that to really , you

11:05

know , kind of understand

11:08

like , oh okay , we're going to do security

11:10

this way because we

11:12

have this huge compliance standard with

11:14

NYDFS that just came out , that

11:17

you know they're going

11:19

after companies for it , right ? So , like this is

11:21

a hot priority item

11:24

. You know we need to get through it like this

11:26

rather than this other , you know

11:28

, industry recognized method that we've done

11:30

forever . You know .

11:32

Yeah . Yeah , I think my job is to be

11:34

able to actually underwritten . I understand

11:36

the statistics that an actuary uses

11:39

. You know and I can form opinions

11:41

about this is the way the market is going

11:43

. You know right now we're underwriting enterprise value

11:45

. I actually think we're going to go to a model where we

11:47

underwrite the value of the actual data

11:49

that they've risked and

11:52

part of that is bringing that back . And I

11:54

agree like I always tell people like you're

11:56

not the non security background

11:59

that you bring is what's really important and

12:01

I think we in the security profession to do

12:03

a lot better job of building those bridges . Because

12:05

I agree with you , I hate the like . Here's your

12:07

18 month old print into a

12:10

tier one analyst rule . That's going to suck

12:12

your soul out of you , right

12:14

? Because , like , that path

12:16

is not going to get you into a really cool , interesting

12:19

security game . It's going to get you into a tier

12:21

one socket , which is not

12:24

the best way to start out in

12:26

security is . A lot of times those are kind of burn

12:28

assured roles . They're

12:30

really stressful . Yeah , like

12:33

how many you can be like . Okay , well , I come

12:35

from a you know a manufacturing

12:39

background , right , but I really understand

12:41

the physical security aspect of manufacturing

12:43

. That's an entire like subset

12:46

of security that is actually desperately

12:48

in need of monetization . So

12:51

go go into it that way , you know

12:53

, develop opinions on it , like in that

12:55

I think a lot of times people are afraid to

12:57

have an opinion , but that's gotten me most of the

12:59

best jobs I've ever had , right Is having

13:01

like a contrary

13:03

opinion on something .

13:06

Yeah , I feel like that's a that's

13:08

a pretty common , you

13:10

know , attribute of security professionals is

13:13

having an opinion on something that isn't

13:15

isn't the norm , isn't the

13:18

expected , you know opinion

13:20

and you know

13:22

I . I kind of go back to like

13:24

when my wife and I we were building

13:27

our house and you know figuring

13:29

out where we wanted the rooms and everything like that

13:31

, right , she

13:33

wanted to have a more open , you

13:35

know , floor plan and I'm thinking to myself

13:37

, well , like that makes things too easy , you

13:39

know , for for a potential attacker

13:41

, right . Like I'm thinking from a physical security perspective

13:44

and I'm thinking like you

13:46

know , oh , I don't want a wall here because I want to put

13:48

a camera there so I can have a wider view of range

13:51

, right , Like like all

13:53

of these things . And you know , when we're finally

13:55

in the house , she's like oh well , I like

13:57

you know , no , like

14:00

no shades on the on the window because it blocks

14:02

the natural sunlight from coming in , and whatnot

14:04

. Like one . We live in Chicago , so we

14:06

get natural sunlight like four months

14:08

of the year . And two , you

14:10

know , we're just opening our windows to attackers

14:13

. And she's like where do we live ? Like we

14:15

live in a place that has literally

14:17

zero crime ? Yeah , who

14:19

are we protecting from you know

14:21

? But like , my mind works totally different

14:23

. My mind is like like no , you

14:26

know , worst case scenario , we already expect

14:28

them to be here , you know that sort of thing . And

14:31

she has to like dial me back .

14:33

Yeah , it's interesting to think about , like

14:36

how we think about security because

14:38

, like what you're talking about , like some

14:40

of that , is such an actual

14:43

security . It's so good to secure a theater

14:45

and it's really interesting to think about it like a post-911

14:48

world , right , like a lot of people under

14:50

. It's so crazy . I think people under 25

14:52

have never known a world without security

14:54

theater , I mean you didn't use to have a lot

14:56

of that , and so I think some of that is like

14:58

there are things you do because they actually

15:01

make you more secure , and then there are things

15:03

you do because they present the illusion

15:06

of security right , like

15:08

she is a security theater

15:10

, because , realistically , if someone

15:12

wants to run straight through those parachutes

15:14

with something , they can and

15:17

you know I didn't so , but I it's interesting

15:19

to think about that because we're in the same position and like

15:21

I shouldn't say that I

15:24

might not lock my doors at night . Yes

15:26

, yeah . Because

15:28

I think it like I've had . I've tied my car . So

15:31

, for example , I used to have a convertible right . I

15:33

had my caribled three weeks in South

15:35

Salem that it would just tie the barry out , but

15:38

I'm supposed to be kept at top and broke into

15:40

it and it's like a two brand for a new

15:42

convertible top . So you know what I started doing

15:44

. I just didn't lock my doors . I

15:46

just left my car . I locked all the time , but

15:49

anything really important in the trunk is , I figured

15:51

you know like , and the top never

15:53

got caught again . It's

15:56

interesting to think about , like what things are actually

15:58

secure , what things are and

16:01

I had a kid that I was reading a book the other

16:03

day about also like our perception

16:05

of security and how much

16:07

more dangerous the roles become

16:09

and actually statistically the world's become quite

16:11

a bit safer , you know , and that they fit

16:14

a more dangerous person than they used to be , or things

16:16

like our diets .

16:18

Yeah , yeah .

16:20

So it's like I don't know we let their kids watch school

16:23

. Yeah , there's this perception

16:25

that like there's all these people out there

16:27

who are going to snatch your kids , but realistically

16:30

, kidnapings are like are down

16:32

by more than 50% since 25 years

16:34

ago . So , it's a

16:36

yeah , but I mean the same thing

16:38

in cybersecurity . Right , it's like people

16:41

we spend all spend billions

16:43

of dollars on all this AI

16:45

and sophisticated detection and

16:47

it's literally just some dude in your mailroom that

16:49

clears from the wrong link that call . Or

16:52

your your HVAC system

16:54

. You're using the default password for

16:56

the system that operates all on your air and

16:58

somebody gets it . It's

17:00

like you can sit all the time in the world

17:02

and you're spending all this money on stuff , but

17:04

the end of the day , it's usually the little things

17:06

that you're going to get that

17:08

screw you over .

17:10

Yeah , you know

17:12

, that reminds me of , like the

17:14

Octa breach that recently , apparently

17:17

recently , happened right , where you

17:19

know someone just dialed into support or

17:22

you know whatever it was the help desk and

17:24

they got access via that

17:26

. And you

17:28

know , octa was infamous

17:31

for having top notch

17:33

security never really dealt with

17:36

a breach like this before

17:38

you know , or anything like that . And

17:41

I think that they I think they handled

17:43

it fairly well right , because

17:46

I felt like I was getting the information

17:48

, like I felt like I was getting the updates

17:50

as they were getting them . You know , like , oh

17:52

, we just found out 100%

17:54

was breached . Yeah , Sorry

17:57

, yeah , you know , we just learned of it . You

17:59

know , not like a whatever

18:02

, whatever breach that was last

18:04

pass right , that like , yes , really

18:07

frustrated me . Yes , where it's like oh

18:09

, you know , they don't have anything . They got

18:11

in , but they didn't get anything . Oh

18:14

well , I got some stuff . You know

18:16

, some of the stuff is unencrypted somewhere

18:18

. Right , they got some stuff , but you're fine . Oh

18:21

, it turns out they got everything and

18:23

your master password to your , you

18:25

know , to your vault . Like guys , you

18:27

should have told me this six months ago .

18:30

Yep , yeah , how do you handle a data breach

18:32

is a lot like obviously , the kind

18:34

of data that's breached is really important , but

18:36

how you handle it Like I think about

18:38

this going through me you know

18:40

breach , and I think that's

18:42

kind of like on the polar opposite end where

18:44

I haven't really heard a whole lot from them and

18:47

I just keep , like you know , to

18:49

your point . I said well , the last pass . It's like I haven't

18:51

heard anything from them , like all I've

18:53

the only thing I've seen in the press from them

18:55

is that they still think they can be profitable

18:57

as a company and I'm like how do you know if you could

18:59

be profitable ? I want to cover my

19:01

DNA .

19:03

Right yeah .

19:06

You know I so I actually wrote when I was

19:08

in industry at all this a couple of years ago I wrote

19:11

a paper on my paper on

19:13

zero shots and that , like zero

19:15

stress is still you're creating a single

19:17

point of failure . And that's

19:19

like it's we

19:21

, it's these first pull forces

19:24

of convenience and security . Right , everybody

19:27

wants to be super secure , but also

19:29

we can't inconvenience people , because if you inconvenience

19:31

people with security measures , they finally circumvent

19:34

them . So it's this constant

19:36

battle of like and octasease

19:39

like a great idea , right Cause it's like , oh , it's

19:41

all encrypted , but again , single

19:44

point of failure . And so you know

19:46

it's . I see

19:48

these things and I think this I assume this

19:50

is most recent

19:52

kind of takedown of loft bit . If

19:54

you've read through any of the documents about the

19:57

US it's . They're basically like , hey

19:59

, the US has single points of failure

20:01

all over infrastructure . The

20:03

AT&T outage the other day really kind of

20:05

drove that home for me , you

20:08

know , because it wasn't just AT&T , because it's

20:10

an AT&T downlink satellite area , it's

20:13

all self providers Block . People

20:15

don't realize that , like self

20:17

providers don't each have a tower , it's

20:19

like they kind of choose each other's and

20:21

yeah . So it's

20:24

a really interesting thing to think about and how we

20:26

go about managing that the kind

20:28

of trade off . And to me

20:30

I've always said you know , security is really a culture

20:33

, and so I think what we need to

20:35

focus a lot more on is how

20:37

to just build security practices

20:39

into your culture at your company . Because

20:42

I could talk smack about

20:44

that now because they would pay . Personally Can't

20:48

sue me , but I went from Fidelity

20:50

to SBB and Fidelity is one of

20:52

the most conservative financial companies that exists . Right

20:54

, they're boss and base

20:56

, they're super . It went here like your first day there

20:58

. They're like , hey , fyi , compliance

21:01

is your best friend . Like they are here to

21:03

save your ass , they are not here

21:05

to ruin your day and not here to make your job harder . And

21:09

at SBB it was kind of like compliance . Just

21:12

they had these two people running all of compliance and

21:15

when I got there , like lots of the stuff they were doing , I was like I

21:17

had a supervisor lessons and my supervisor

21:19

didn't , and so I was like we can't do

21:21

most of this stuff . But it was like a check the box in there . And

21:26

security is the same way . Security compliance can go hand

21:28

in hand , right , and it has to be a

21:30

culture , because

21:33

if it's not just baked into everything everybody at your company does

21:37

and if they don't unquestioningly

21:39

trust security to have their back and

21:42

to ask stupid questions , to be able to send efficient emails before

21:44

, like if I because a lot of times I think people make bad

21:46

decisions because they're straight to ask questions

21:49

. They don't want to look stupid or admit that they don't

21:51

know whether it's safe to click on an email or not , right

21:53

, and so maybe what we do look

21:55

at a lot more is like how do we make security

21:57

more accessible to non-technical people and

21:59

how we just bake it into the corporate culture

22:03

, and most of the time we're just like we need to make the culture in most places

22:05

where we focus more on like so

22:11

and this is , I have this argument of people a lot

22:13

if having security policies

22:17

in place Prevent you

22:19

from doing your job effectively , that's probably

22:22

a procedure . It should , not a policy issue . Right , like

22:24

, if the policy is really prohibitive , change the policy

22:27

, but usually it's the way the policy is being

22:29

implemented that people have a problem with . I'm

22:31

really focused on is how do we separate

22:35

policy from procedure and Acknowledge

22:37

that , yes , some of these things might add some more work

22:39

, but we can really optimize the procedure

22:42

by which we do that , so that the policy

22:44

is not prohibited to your day-to-day work . If

22:46

that makes sense and they think like we're

22:48

not design architects for security people , so we

22:50

don't think about these things , but they have to start

22:53

kind of going together the same way you would design

22:55

UI products To , because

22:57

it's it's not just technical people that

22:59

get hacked , right , oh , yes , yeah

23:03

, that's , um , that's .

23:04

It's an interesting balance that well

23:07

, one you probably wouldn't get if you

23:09

went directly into security , right . So it

23:11

kind of circles back to that , yeah

23:13

, but you know that that's . It's

23:15

a balance that actually I'm having

23:17

to deal with right now , right

23:19

, where I'm trying to deploy and enhance security

23:22

controls , and all in line

23:24

with security policies that my architects

23:26

have created , but at

23:28

the same time , I need

23:30

to not create something so

23:32

restrictive or

23:35

enforce something so restrictive within these

23:37

applications that my devs can't do their work

23:39

, and so I . I

23:41

have to actually work , you know , very

23:43

closely with the business , that

23:46

, with people that are much smarter

23:48

than me , that

23:50

you know , or languages , right , you know

23:52

like there's compliance , you

23:56

know , basically everyone . So just

23:58

to make sure that the organization is not just

24:00

secure but that everyone in the org

24:02

can do their job as they expect

24:04

to do it , you know , and that they've been doing it

24:06

that way , and so

24:08

it's a challenging balance

24:11

, for sure .

24:12

Yeah , do you find it also challenging

24:14

to have to tie this up here , doing till a broader

24:17

corporate initiatives To

24:19

keep yourself relevant .

24:21

Yeah , that's . You know

24:23

that . That's like , um , I guess

24:25

in my most recent role , you

24:28

know , that's been a more of a focus right

24:30

Of of me taking

24:32

more and more ownership of . I'm

24:35

basically a manager or director without

24:37

the title , right , like the

24:40

title is engineer . But all

24:42

the stuff I'm doing like my manager even

24:44

say , is like , yeah , all the stuff you're doing is , you

24:46

know , director level role stuff , right

24:48

, like I'm managing my budget , I'm

24:50

, you know , putting out , you know

24:52

company wide notifications and things

24:55

like that , right , all the people I'm communicating

24:57

with . And it's a learning curve for

24:59

sure , that is . I

25:01

mean I just spent like the last four , five

25:04

months trying to figure it out .

25:06

Yeah , yeah , and I think

25:08

that's kind of where you've . Everybody

25:11

, I think , who retires in their career

25:13

goes through this process , where all of a sudden you

25:15

realize that like you have to think like

25:17

the CEO , even if you're working

25:19

in , because if you want to get

25:21

something funded , if you want to get people

25:23

to pay attention to it , if you want you

25:25

know , if you wanted to be more than just your pet

25:27

project , like it has to tie into these

25:29

kind of broader company initiatives . And

25:32

so I was actually talking with one

25:34

of my friends about setting up like a CISO training

25:36

thing at one of our corporate

25:39

events that we're doing , and I said you know , I think

25:41

you should do improv comedy , like

25:44

do an improv comedy class , because one of

25:46

the things I find is that people in security are

25:48

really not that a problem speaking , and

25:50

so , like you not only have to be able to

25:52

understand what you're doing as

25:54

a security leader , you have to be able to articulate

25:57

it to vastly different

25:59

audiences . Right , the way you explain what you're doing to

26:01

the CFO is different than the CEO

26:03

, is different than the CTO . And

26:05

then you also have to be able to get up in front of people

26:07

who are going to pepper you with questions and

26:09

you'll answer those questions . And

26:11

I like I don't think that's necessarily something

26:14

that people anticipate when they go into security

26:16

that when you get to a certain point

26:18

in your career , all of a sudden it almost

26:21

seems like all of a sudden you have to become a significantly

26:23

more robust professional . And you

26:25

did when you were just doing like detection

26:28

response .

26:29

Yeah , yeah , it's a really

26:31

good point . You know , I

26:34

always talk about , or I try to

26:36

on this podcast , talk about the things

26:38

that kind of separate you right from from

26:41

other people . And the reason why

26:43

I do that is because those separation

26:46

, those I guess those separation points

26:48

, you know make you stand out more . And

26:51

when you stand out more , hopefully it's in a

26:53

good way . You know you get promoted , you

26:55

get the opportunities that others don't get and

26:59

that you know you approach different from

27:01

from . You know , let's do improv . To

27:03

me , improv would be very scary

27:05

. I think I'm a funny person but I'm

27:07

not improv funny , you know

27:10

. That would be terrifying

27:12

.

27:14

But anyway , just have a bunch of people

27:16

and like the people position crying on

27:19

stage .

27:19

Right , right , but

27:22

you know what one of you

27:24

said . You know they struggle with

27:26

public speaking , right

27:29

, or speaking to other people that they don't know

27:31

, or what . Right ? And

27:33

this was also an issue for me , you

27:36

know , several years ago , before I started this podcast

27:38

, and somehow I got this idea to start

27:40

a podcast and I could get it out of my head . So

27:43

here I am , right , like over 150

27:45

episodes in . And you

27:48

know you came on here , there was no prep

27:50

. It was like , hey , this person's name

27:52

is Joe , he runs this podcast

27:55

, you know . And then like the same thing for

27:57

me , like this person's name is Jackie

27:59

, she's from Cribble , this

28:01

is what they do , there's no questions

28:04

, you know anything like this . If you go

28:06

back five years ago , the

28:08

thought of this conversation taking place

28:10

would have given me a lot of anxiety , but

28:12

now you know it's

28:15

nothing right , like we're just having a conversation

28:17

.

28:18

No , it did muscle and that's like . So improv

28:21

was terrifying for me too , like when

28:23

I first did it . The number one

28:25

rule of improv is yes , and

28:27

which is basically no matter what

28:29

the person before you says , you

28:32

have to agree with it and

28:34

add to it . So , and it's actually

28:36

a really good lesson for how you should live your life , because

28:38

I do some crazy stuff in my life , like I

28:40

love music , festivals , traveling , and I've

28:42

done all kinds of crazy stuff on

28:44

purpose and accidentally , because when somebody's

28:46

like , hey , do you want to do this thing , I'm

28:48

like , yes , and we should also

28:51

do this , which would make it even more epic , right

28:53

, and so that's kind

28:55

of like I . So I'm in Cribble . We have

28:58

my team is very small , but with people who

29:00

make content . We call our own

29:02

team if it will do it live

29:04

, because same thing , like almost no

29:06

live streams . We do Like I'm usually finishing

29:08

the slides for whatever thing we're about

29:10

to do as we're starting the introduction

29:13

on the recording . But

29:15

I think to your point , it's a muscle and it's

29:17

a muscle you have to exercise . And

29:19

the other thing , like the thing to figure out , is that

29:21

we all , we all have this like critical

29:23

interior of failure and

29:26

I guess in my career I've been really fortunate

29:28

that I have screwed up so badly , so

29:31

publicly , a few times that

29:33

I have failed in the most epic ways you can imagine

29:35

. And it turns out that , like , none

29:38

of your family stops loving you , none

29:40

of your friends stop hanging out with you . No

29:44

, they think you're like , let me be true about

29:46

worthless person . So you

29:48

know , you fall on your face a couple of times and you're

29:50

like , oh , it's not that bad . You know this

29:52

podcast wasn't the best one I ever recorded , but maybe

29:54

next week's will be better . You know , like

29:56

everybody in your life is , like nobody

29:59

cares , and that's the kind of thing that I

30:01

figured out is like the

30:03

work you do is extremely important , right , having

30:05

this podcast , having a resource of people who really need

30:08

it , is both extremely important and

30:10

extremely important at the same time . So

30:14

I keep looking to figure that out . It makes life a lot

30:16

easier than that .

30:18

Right , yeah , you bring up

30:20

a lot of really good points there

30:22

. You

30:24

know , with having you

30:27

know , I feel like it's so important to have

30:29

I don't want to call it a safe space

30:32

, but you need to have a space where you can fail

30:34

constantly in tech . You

30:37

know , like one of my first jobs out of college

30:39

, I mean I dropped

30:41

a bank's database , like

30:44

I didn't even know the term

30:46

drop right , like I accidentally

30:49

deleted this customer's database and

30:51

they were a bank , and then I spent

30:53

the next you know two

30:55

days , right , fixing it and

30:57

restoring it from logs that

30:59

I didn't even know could be restored from , and

31:02

you know all this sort of stuff . They didn't lose any data

31:04

, they had no downtime , right

31:06

, but I still dropped their production database

31:09

and you know

31:11

in a lot of companies on a lot of teams . That's

31:13

like immediate termination . Like , okay , you don't know

31:15

what the hell you're doing , like , get out of here . You

31:18

know . But I was also very open in the interview

31:20

. Like , hey , I don't know what the hell I'm doing . Yeah

31:22

, like , I need to be taught , you

31:25

know , and that was a huge learning

31:27

moment . But like , and

31:29

that's just one of like

31:31

a hundred , you know situations

31:33

that I was in at that company alone , right

31:35

, and so I developed , you

31:38

know , the greatest troubleshooting

31:40

doc ever at that

31:43

company . It's literally still in use . Where

31:45

you know , when someone encounters a random

31:48

problem , they just go look at my

31:50

doc because I guarantee you I've

31:52

encountered it and there's a whole section of SE

31:54

Linux and before I encountered

31:57

SE Linux there , I never touched it

31:59

, I didn't know it existed , literally

32:02

. One of my customers was a federal agency and he

32:04

said , hey , we need to turn on SE Linux , you

32:07

know , on this server . And I was like , okay

32:09

, turn it on . What's the problem ? He goes

32:11

, no , it breaks everything . I was like , whoa

32:13

, that's weird , you know . And then I would . That

32:15

was rabbit hole for three months of

32:18

knowing way more about SE Linux

32:20

than I ever wanted to , you

32:22

know it's , it's

32:25

really interesting . And then you know you bring

32:27

up the the yes and perspective

32:29

from improv and I actually

32:31

do that with like all of my trips . You

32:34

know that I'm planning a trip to

32:36

London for my first time in

32:39

the fall and

32:41

I'm going with a friend . I'm bringing my

32:43

wife and my one year old , and

32:46

you know he

32:49

comes from a different background , I guess , of doing trips

32:51

right , where they kind of plan everything around food

32:53

and you know everything else

32:55

kind of like falls into place . I guess I

32:58

am the complete opposite . I am like

33:00

like no , like we're going

33:02

on this bus tour , we're going to get off

33:04

, we're going to go have drinks here , like

33:06

all of it . You know , because when I

33:08

go somewhere new it's like well , let's

33:11

do everything , like I'm

33:13

not here to sleep , like if they're

33:15

open at 4am , like let's go at 4am

33:17

, Like I do not care . You know , yeah

33:19

. It's the same thing I did with my Germany trip last

33:21

year was , you know , every day

33:23

was another adventure , like one day

33:25

we were in the mountains going through castles

33:28

for the entire day , walked an entire marathon

33:30

. I was dead tired

33:33

at the end of it . And you

33:35

know , the next day was a football game . Right

33:38

, like , went to the football game , did a full day of

33:40

drinking . You know , I got to see

33:42

my buddy not keep up . That was fantastic

33:44

, you know , like the

33:46

whole thing , you know it's . It's

33:49

that ability to just

33:52

want to keep going , you know , want to keep

33:54

exploring and pushing and seeing

33:56

what else is out there . I guess .

33:59

Yeah , yeah , and I just kind of always

34:01

done like that . I think some of it is that I grew

34:03

up super sheltered , so if

34:05

you were poor and I was homeless

34:08

when I was 19 , like I

34:10

, so I never got

34:12

to go anywhere . Like we went on like

34:14

two trips that I can remember as a

34:16

kid . So when I was finally an adult and

34:18

making a lot of good money because I was working in fine

34:20

ass , it was like I want to do all

34:23

the things , I want to do everything

34:26

, like there's no reason not to try

34:28

anything because I didn't get to do anything

34:30

when I was a kid and I

34:32

always had like I've always had health

34:35

issues , so I've also always had this

34:37

kind of like my clock might be ticking faster

34:39

than other people , so I need to do all the stuff

34:41

you know before you know

34:43

before I run out of time and health to do

34:45

it . So that I just I

34:48

feel like everybody's . So

34:50

one of the interesting things I've also found is that

34:52

, like I used to think that everybody's

34:55

idea of happiness was roughly the same

34:57

, and I think that as I've grown as

34:59

an adult , I figured out that we're

35:01

all wired completely

35:04

differently . Like everybody's brain is wired

35:06

differently about brings people happiness , and joy

35:08

is completely different from one person

35:10

to another . It's like growing up in New Hampshire

35:12

. It's a lot of friends who live within

35:15

10 miles of where we graduated from high school

35:17

. We were married to somebody that

35:19

we went to high school and you

35:21

know , they've literally never been . I have

35:23

a friend who's never been west of Tennessee because

35:26

they live in New . Hampshire like doesn't have a passport

35:29

but they're happy and

35:31

or ish and so

35:34

like , if I don't know , I just think that I

35:36

know I'm ADHD , I know I'm autistic

35:38

, so I know that my brain has like a 40%

35:41

higher need for stimulation and activity

35:43

in most people's . Yeah

35:45

, I'm all about like maximizing the hour

35:47

line for every moment I'm awake because

35:49

, like , I think that's just how ADHD

35:52

brains work . Right , we're much human optimization

35:55

machines .

35:57

Yeah , yeah , you got to . I

35:59

don't know like I'm , I don't know if

36:01

I'm ADHD , but you

36:03

know I find that I have to

36:06

at the minimum . I have to have a goal

36:08

, you know , at all times , right , and

36:10

I need to be making progress towards it

36:12

and I have different ways of kind

36:14

of tracking that progress and whatnot . Right

36:17

, because when I don't have that , I

36:19

start I don't know , I like

36:21

start going off the deep end , right , and I'm like

36:23

no longer focused . It's very easy for

36:25

me to get into that spiral , right

36:27

.

36:28

You don't know if you have ADHD right

36:30

, right .

36:31

You know , I guess I've

36:33

never been tested , or whatever .

36:36

I didn't get tested until like four years

36:38

ago . It was

36:40

crazy too , cause it's like a list of 45

36:43

things that you thought or like character flaws

36:45

about yourself , and all of a sudden

36:47

you find out like , oh , it's actually

36:49

not that I'm human garbage , it's

36:51

actually just that my brain is wired differently

36:54

than other people's .

36:57

Right , yeah , it's

37:00

interesting , I feel like , as , as

37:02

time goes on , I just figure

37:04

out how , or like

37:06

, different everyone is

37:09

, you know , and how different everything

37:11

is , you know , and how to appreciate that

37:13

it's . Um , it's

37:16

an interesting thing that I

37:18

kind of recently went down , I guess , but

37:22

you know , can we really ?

37:23

so it's really important with regard

37:26

to AI , to understand how different people are and

37:29

so to actually talk about something technical here

37:31

, one of the really interesting things I've been thinking and

37:33

researching a lot about

37:35

is diversity as it relates to artificial

37:38

intelligence and as it relates to technology

37:40

in general . Um , and so any

37:42

modern times that people and I'm going to go out

37:45

of kind of a tangent people take of DEI as like a

37:47

PR thing or like it's a moral

37:49

issue and like , yes , morally we should

37:52

all iron diversely and hire every candidate . But it's

37:54

actually also just a technology

37:57

usability issue , because

37:59

if you don't want a world that's primarily

38:01

built to serve mostly

38:04

male , mostly white men , then

38:06

you can't have mostly male , mostly white

38:09

men building all of the technology and

38:12

this . That sounds kind of , you know , like a political

38:14

stance , but it's really not in that

38:16

. So if you

38:18

take the politics out of pronouns

38:20

, right , and you don't like and we

38:23

ignore who you know , we want to

38:25

argue over whether there should be more than two pronouns

38:27

. Well , guess what , in the Thai language there's

38:29

like 20 something , because in the Thai

38:32

language your pronoun encompasses what you were born

38:34

as , what you currently identify , as

38:36

is who you like to date . And so we

38:38

were talking about something like generated AI

38:41

. When we're trying to talk about canonical

38:43

inferences and being able to understand

38:46

text , if we don't want generated

38:48

AI to only be a utility

38:51

and helpful for English speaking

38:53

people , then it can't just be

38:55

written by English speaking people . And

38:57

so another example is like English

39:00

and Spanish are both romantic languages

39:02

, but the way you say I love something and I have

39:04

something or the same in Spanish . So

39:06

this comes into play . When you're

39:08

talking to a generative , like I'm putting

39:10

props into gen AI . If

39:13

I say , let's say

39:15

, kiaro tacos , how does that

39:18

generate AI know whether I'm

39:20

giving it a piece of factual information ? And

39:23

saying I love tacos because

39:25

take Kiaro tacos means I love tacos

39:28

, romantically , right ? Or Kiaro tacos

39:30

meaning I want tacos , and

39:32

that actually makes a big difference to because one of those

39:35

is input and one of those is requesting

39:37

help , right ? If you say I want

39:39

this , you may be requesting to get that

39:41

thing back . So diversity

39:44

another place this comes into play

39:46

is hardware . So

39:49

hardware is predominantly built for male frames

39:51

. So when you think about something

39:53

like the Apple Vision Pro , causing a

39:55

lot of women and

39:57

smaller framed people massive migraines , it's

39:59

probably because the people who designed , built and

40:02

tested that we're all skewed

40:05

towards a specific population . So

40:07

this is one of the things I think is really

40:09

interesting to think about , in that diversity

40:12

in technology is not just important because

40:15

in a utopian world , that's

40:17

how it would be . It's important because it's

40:20

going to make , it's going to determine whether

40:22

or not technology is

40:24

only useful for a

40:26

small group of people , and that's important

40:29

, right ? So the hugging

40:31

face shout out . The hugging face is

40:33

a nonprofit . It's super dedicated to

40:35

democratizing machine learning and AI

40:38

and I'm like those

40:40

are things that are really passionate about , because we

40:44

have a technology that has the ability to fundamentally

40:46

transform the way humans live

40:48

and to provide benefits that a large

40:51

percentage of our population has never

40:53

had before . But we can

40:56

only get there if we build it so that it works for

40:58

all people , right .

41:01

Yeah , it's a really good point , and

41:03

I've had on , like AI

41:05

researchers before and

41:07

I talked about this where , like

41:11

, how do you ensure , right , that

41:13

the AI has enough diversification

41:16

of its data and how

41:18

it's making

41:20

its choices , and

41:23

if it hurts a certain group of people or just advantages

41:25

a certain group of people , or whatever

41:28

it might be right , like

41:30

, how do you protect against that and how do you

41:32

have , potentially

41:34

, I

41:37

don't know , like a base

41:40

set of language or a base AI

41:42

model , right , that this other

41:44

AI model can check itself against is like

41:46

, oh , did I make the right decision here ? Like

41:49

that's where the people come in , I guess . But it's

41:53

a really it's a fascinating area

41:56

because , as humanity

41:58

has evolved , we've never encountered something

42:00

like this before . It's never been

42:03

. It's never been a thing

42:05

that anyone ever really thought

42:07

about . It's never been a thing where

42:09

we thought about , like , is Google

42:12

serving me the right search

42:15

results , right , based on I

42:17

don't know where I live , or whatever , right , those

42:21

things have never come up before . It's really

42:23

interesting where we take it , because this

42:25

will , like you said , this will really

42:28

have the capability of advancing

42:31

civilization as a whole . This

42:34

can either go really well or it could probably go

42:36

really bad .

42:37

Hopefully , it goes really well . Yeah

42:40

, for sure , and that's it's something

42:42

that I think that I

42:45

don't tend to be as much of a doomsdayer as

42:48

a lot of

42:50

AI people are , that they do potential . I

42:53

do see the potential for things to get out of control

42:55

. But also , just like a bucket of water , right

42:57

, like there's

43:00

just a bucket of water on it . No

43:02

, but what I do ? I think it's

43:05

something that we

43:07

need to . There's this phenomenon

43:09

that I've always encountered in tech where everybody assumes

43:11

that somebody else smarter than them is focused

43:13

on this problem , on any problem

43:15

, on any equity problem that

43:17

you bring up in tech . Like I think most people

43:20

always assume there's someone else

43:23

who's gonna deal with that . Like

43:25

because somebody smarter has already thought

43:27

of that A lot of times . Like seriously

43:30

, nobody's brought it up . Like there are some large

43:32

technologies that have been released that people are

43:34

like , oh , what about this ? And oops

43:37

, like I remember the

43:39

it was the one of the Apple washes

43:41

that was released . Like the Apple wash , the

43:44

face of it was too big for like 40%

43:46

of women's wrists .

43:48

Yes .

43:49

And actually I have comically small

43:51

wrists anyway , but I haven't seen an issue with

43:53

like this is not what this wash was

43:55

intended to look like , right , so I really

43:58

have . But

44:00

yeah , I think everybody was assuming somebody

44:02

else is doing this and as the

44:04

world becomes more complex , that

44:06

phenomenon will probably increase . So I think

44:09

one of the big questions we have to have is how

44:11

do you put in place checks and balances

44:13

to make sure that someone actually

44:15

is thinking about these things , and

44:17

how do you try to control

44:20

like we're also trying to make regulations

44:22

at like a state and even country level

44:24

, and data and technology is

44:26

local . So the other thing is like there's all these

44:29

different NGOs that are trying to do things

44:31

. So we have to come to a place where we're

44:33

coordinating these things a lot more closely

44:35

so that everybody is kind of aware of the

44:38

state of technology , the ideals

44:40

, you know what we're working towards , cause it seems

44:42

like a lot of this stuff , some

44:44

of these decisions about you know , do we make it

44:46

more equitable , or do we make more profits

44:48

, or are being made behind closed

44:51

doors . So I think there needs to be clearer expectations

44:53

that for when one of these paradoxes

44:56

comes up that has the potential

44:58

to impact a large number of people . Those

45:00

decisions aren't just being made by a small

45:02

group of people , and they're being made

45:04

in a public way .

45:07

Yeah , I think you bring up a great point , right

45:09

Is that it's very easy

45:11

for us to kind of assume

45:13

or think that , you

45:15

know , someone has already thought

45:18

of this , they're already working on this , they're

45:20

already doing acts , right , which

45:23

really isn't always

45:26

the case , and it's probably

45:28

happening a lot less than what you would expect

45:30

. And the difference , right

45:32

, someone may even have the same exact idea

45:34

, but the difference is , if you act

45:36

on it , it's actually , it's if you actually

45:38

do something with it , and that's , you

45:40

know , that's the important part . That's

45:42

, honestly , that's what separates , you

45:45

know , I would say , you

45:48

know the people that you hear about . That's what

45:50

separates them from everyone else is

45:52

that they get an idea and then they find a way

45:54

to make it work . Like , however , whatever

45:56

that looks like , whatever that takes

45:59

, you know , they just find a way to make it work . And

46:02

I feel like , as technology professionals

46:04

, we kind of like got to get out

46:06

of our own heads , you know , with

46:08

that , because we're so analytical by

46:11

default , right , that you

46:13

know we'll overthink something for

46:15

years before actually moving , when it's

46:17

like , hey , you should have done this , like 10 years ago

46:19

.

46:20

Yeah , yeah , I mean like , how many times

46:22

does the technology come out ? You're like , oh man

46:24

, I had the idea for that like 10 years ago

46:26

and it's like , yeah , but you didn't do anything about it . It's a issue

46:29

, yeah , great , we

46:32

at Adobe always assume and that's like

46:34

people so many people underestimate their

46:36

power , and this is the thing when I so

46:38

when I came into security . Here's

46:40

the thing we're all talking about how

46:43

great it is to get into security from other

46:45

industries . But we should acknowledge

46:47

that when you do get into security

46:49

, if you're new in the industry , it's really

46:51

easy to feel like an imposter or feel like an

46:53

outsider or feel like you're faking it because

46:55

you're moving somewhere . But that goes

46:57

back to what I was talking about with insecurity

47:00

. I found that people don't really necessarily need

47:02

to like you . They just need to trust

47:04

you , and I've earned

47:06

a lot more respect from my peers by

47:09

being really clear on where my

47:11

skills end than

47:13

demonstrating those skills themselves

47:15

, because I come into a room full of security

47:17

engineers and these people can hack your router

47:20

in four minutes with a

47:22

fluke or zero . Like

47:24

. I'm not that . I'm a data scientist

47:27

and I only worked as a data scientist

47:29

applying it to security for a little over a year

47:31

, so but I know

47:33

that what I lack in

47:35

actual technical ability to pop

47:38

your Tesla's gas door , like

47:40

I made up for in my ability

47:42

to communicate , so , like

47:44

my superpower , is communication and translation . I

47:47

can take . I can sit down with your security engineers and

47:50

they can dump on me all the technical stuff that they're

47:52

doing and I can take that and make it into a store . You

47:55

can tell your customers . I

47:57

can make it into a store . You can tell your marketing team , your sales

47:59

team and so

48:01

like . There's a lot of different skills required

48:03

around security

48:06

to make a security program

48:08

successful . Like communication , like marketing

48:11

, like training , like cause . There's

48:13

a big difference between knowing how to do something

48:15

and knowing how to teach somebody else how to do

48:17

it . So I was a facilitator for a long time another

48:19

communication job , right . So

48:22

it's important for the knowledge that you

48:24

may feel like a fish out of water

48:26

if you get into security or you join

48:28

a new industry , but you need to understand

48:31

that , your ability to know

48:33

your limits and to say

48:35

, hey , I've actually never had experience

48:37

with that , but it's something I'd like to learn more about

48:40

. Where could I read about that ? Like people will

48:42

respect you 10 times more for doing that

48:44

than for immediately . Well , should they get an

48:46

answer , because you feel like you should have one .

48:49

Yeah , I've always found there

48:51

to be a lot of value when you're more

48:54

honest , more open , more upfront

48:57

about your own limitations . You

48:59

know , because people

49:01

will keep , I guess

49:03

, kind of drilling you or drilling

49:05

you , especially in security , in the security world

49:07

. You know , as soon as you

49:09

say like oh yeah , I've done this for

49:11

10 years , or I'm an expert in this

49:14

, I built this , I mean

49:16

in security , it's like okay , well

49:18

, guess what ? I understand what that is

49:20

and let's talk about it . You know , like

49:22

we're gonna talk about it at a level that like if you

49:24

didn't build it yourself , you're not gonna

49:26

know . You know , and

49:29

I've been on both sides

49:31

of that interviews , right when

49:34

I've said you know I'm an expert

49:36

in something and they just completely grill

49:38

me on it . And you know , thankfully , like I've

49:40

got him past it because you know

49:42

what I put on my resume is the stuff

49:44

that , like I have done . You know , I'm not

49:46

like bluffing it . I may use words

49:49

that I may like rarely use , you know

49:51

, because , like you know , you don't wanna use

49:53

the same like verb or adverb or whatever it is

49:55

. You know , agitate to describe

49:58

something right , but like when I

50:00

say like hey , I built this thing , it's like . No , I

50:02

actually built it , like you know , because

50:05

I really don't wanna be in a situation where

50:07

someone points out a point and I can't answer

50:09

it at length , you know .

50:11

Yeah , oh , we've all been through the experience

50:13

of seeing , like an ex-co-worker's LinkedIn

50:15

and seeing all the shit that we did that they're taking

50:17

credit for and you're like , oh really , you made that

50:19

happen , huh .

50:21

Yeah .

50:23

Yeah .

50:24

I know . I don't remember you on that project

50:26

.

50:27

Yeah , yeah , and

50:30

do you ever call that the George Santos effect

50:32

? Now , is that ? Yeah , I

50:34

mean , I think that's true Like there's a lot of

50:36

power in saying I don't know , like

50:39

there's a lot of risk in saying it if you're the one who's

50:41

supposed to know . But in a lot of circumstances

50:43

you're not the person who's supposed to know and

50:46

I'm , you know , like people aren't looking to

50:48

you to have all the answers , they're looking to you

50:50

to know where to go to find it . Yeah

50:53

, and that's the kind of what your

50:55

utility is , a security professional usually

50:57

is . It's like I don't know everything

50:59

, but I have a process that I can go through

51:01

or I can quickly get to the information

51:04

that I need , process it and get it back

51:06

in the form we can use .

51:10

Yeah , that's a key distinction there , you

51:12

know , being able to say I don't know and

51:14

then also following up with what I can find

51:17

out . Yeah , In

51:19

today's , you know , modern age

51:21

, right , 2024 , like , you

51:23

can absolutely find something out

51:25

. If you don't know it , you know , by a

51:27

simple Google search you don't have to go to the library

51:30

anymore and hopefully they have a book on

51:32

it , right ? So

51:34

, like , there's no reason why you can't , you

51:36

know , say that and actually follow up with it

51:38

with the real information . Well

51:41

, you know , Jackie , we've gone

51:44

this entire time and

51:46

definitely doesn't feel like 50 minutes , that's

51:48

for sure . But you know , I'm

51:50

I try to be very conscious of everyone's time

51:53

and you know I don't want to go over because I

51:55

know that we're all booked . You know , meeting after

51:57

meeting . So you know , before I let

51:59

you go , how about you tell my audience , you know where

52:01

they could find you , where they could find Cribble

52:03

, if they want to learn more and maybe they want

52:05

to reach out .

52:07

Yeah , absolutely . I've been on LinkedIn

52:09

, so LinkedIn slash Jackie's in security

52:11

Can interpret

52:13

that whichever way you want to . Yeah , and

52:18

Cribble . You know we love Cribbleio , or

52:21

you can also follow Cribble on LinkedIn . We

52:23

have a fantastic social media manager who

52:25

makes a pretty high quality means . You

52:29

know we didn't talk a ton about what Cribble

52:31

does , which is my preference

52:33

, because I think that it's a product

52:35

that is much better for people to do than use . But

52:38

if you have questions about moving

52:40

data , making use of data , any of those

52:42

things , you're more than welcome to reach out to

52:45

myself or anybody else on the Cribble team .

52:48

Awesome . Well , thanks everyone . I

52:50

hope you enjoyed this episode .