AI as a Report Writing Tool: Accuracy Enhancing or Recollection Poisoning?

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What's the real impact of AI on law enforcement documentation? Can digital forensics tools truly revolutionize our investigative processes? These are just some of the provocative questions we tackle in our season two premiere of Digital Forensics Now! Join us as we celebrate our one-year anniversary with reflections on the past year, exciting updates, and plans for the future. 

The episode takes a deep dive into the ethical and practical implications of AI in law enforcement, sparked by a recent AP News article on police officers using AI chatbots for writing crime reports. We express our skepticism about AI's accuracy and discuss the vital need for human oversight. Examining AI’s influence on officers' recollection of events, this episode scrutinizes the potential pitfalls and ethical concerns associated with AI in policing. We also humorously critique some AI-generated descriptions of our podcast, shedding light on AI's current limitations and biases.

Don't forget to vote for your favorite difference makers with the SANS Difference Maker Awards!

In the latter part of the show, we shine a spotlight on Recuperabit, a forensic file system reconstruction tool, and Lionel Notari's invaluable contributions on iOS log files. We tackle the challenges of modifying third-party tools and discuss the broader ethical concerns of reverse engineering. As we wrap up, we celebrate our anniversary by announcing the winners of our prize draw and featuring the "Meme of the Week," which humorously highlights the financial struggles in our field. Tune in for an informative and engaging episode!

Notes-
Local Storage and Session Storage in Mozilla FireFox Part 1
https://www.cclsolutionsgroup.com/post/local-storage-and-session-storage-in-mozilla-firefox-part-1

SANS Difference Maker Awards
https://www.sans.org/about/awards/difference-makers/

Police officers are starting to use AI chatbots to write crime reports. Will they hold up in court?
https://apnews.com/article/ai-writes-police-reports-axon-body-cameras-chatgpt-a24d1502b53faae4be0dac069243f418

Magnet Forensics acquires Medex Forensics
https://www.magnetforensics.com/news/magnet-forensics-acquires-medex-forensics-strengthening-video-evidence-integrity-with-detection-of-deepfakes-and-generative-ai/

RecuperaBit Forensic File System Reconstruction
https://www.forensicfocus.com/interviews/andrea-lazzarotto-digital-forensics-consultant-and-developer/https://github.com/Lazza/RecuperaBit

The Logs of the Week
https://www.ios-unifiedlogs.com/unifiedlogoftheweek

Episode Transcript

Speaker 1 (00:10):
Welcome to the Digital Forensics Now podcast,
season two, episode zero.
Of course, today is Thursday,august 29th 2024.
My name is Alexis Brignoni, akaBriggs, and I'm accompanied by
my co-host, the doctor of theproctors, the master tester that

(00:35):
doesn't let bugs fester, theone that needs to get in gear
with the things she needs toadhere to the one and only
Heather Charpentier.
The music is hired up by ShaneIvers and can be found at
silvermansoundcom.
Happy to get my butt in gear,huh.

(00:57):
I mean that and everything else.

Speaker 2 (01:00):
All right, all right.
Look, I just like that.

Speaker 1 (01:02):
it's like gear adhere , charpentier, it's kind of like
, kind of rhyming vibe there.

Speaker 2 (01:06):
Yeah, you've got the rhyming going tonight.

Speaker 1 (01:09):
What's going on, girl ?
What's happening to you lately?
What's the news in Hoover?

Speaker 2 (01:13):
Alabama and I am attending a training at the
National Computer ForensicInstitute, so I am coming to you
live from my hotel room.
Hopefully the internet willhold up and I won't disappear

(01:35):
during the podcast, but we'llsee.
We'll see.

Speaker 1 (01:38):
I don't think people want to just listen to me babble
for an hour.

Speaker 2 (01:42):
Well, if the internet fails, you just get Alexis
tonight.

Speaker 1 (01:47):
I'll cut it short.

Speaker 2 (01:50):
I'm sure you can do it on your own if you have to.

Speaker 1 (01:53):
Well, look it's sounding good.
It's looking good.
So, first of all, you can see Ihave my awesome glasses because
I got some brand new glasses,snappy glasses.

Speaker 2 (02:03):
Very nice, very nice, very nice.

Speaker 1 (02:06):
I also if Adam.
No, not if Adam will.
When Adam watches the show, hecan't talk smack anymore.
I got his shirt and it has abunch of ones and zeros and I'm
only going to say if you know,you know.
So.

Speaker 2 (02:19):
I'm sure it's about.
I should have worn mine.

Speaker 1 (02:23):
Well, yeah, we could have been twinsies, but you know
you, you play like that Iruined it.
I went all plain well, at leastthere's more lights and more
more uh frames behind you thanusually there is, yeah, less
neon lights, but so, yeah, so,so, yeah, so, um, I got my shirt
and also I just came in notjust came, but a few days ago I

(02:44):
was in sacramento.
Um, we had a little workshop, aday workshop, with the um htcia
northern california chapterthere in sacramento and what a
great turnout like 20 somethingfolks, folks from industry, like
private sector industry, someuh law enforcement from there,
and we talk about the LEAPs andmobile forensics data structures

(03:06):
.
We packed quite a lot Superactive chapter.
If you're in the Sacramentoarea, I would totally encourage
you to join the HTCIA chapterthere.
I'm also a HTCIA chapter member,but in Orlando, obviously,
where I live.
But great, really activechapter up there in california.
I highly recommend that youcheck that out.

(03:27):
Um, and they, they were so youknow a lot of hospitality.
They took me to dinner thenight before and they had to
wheel me out in a barrel, in awheelbarrow, from the restaurant
so did you have a little bitbetter flight than your last
trip, though?
well, first of all, this's likenow if I fly from the East Coast

(03:48):
to the West Coast.

Speaker 2 (03:49):
I'm like wow, it's a really short flight.
Didn't take you days.

Speaker 1 (03:54):
Yeah, when you have to fly across the world, just
flying across country feels likenothing.

Speaker 2 (03:58):
It's all relative baby.

Speaker 1 (03:59):
That's how it is, anyways, but it's really good.
Andrea Martinez is on the chatand jeremy's on the chat.
Good to see you, um.
So, yeah, no, it's been.
It's been a good time.
I got I'm looking forward to,uh a couple of online events.
I'll be speaking at infocomf inum, in argentina, in la matanza

(04:21):
, and, but not in person, sadly.
It it's going to be online.
And then everybody's gearing upfor the ICAC in the northwest,
I think right by SeattleWashington.
Actually, I think it's inRedmond this year, redmond.
So I'll be teaching a couple ofsessions on ILEAPS and also
participating in a panel thereabout mobile forensics and

(04:41):
different things.
So really excited about thatcoming up.
So, if you're all listening,you're going to be at the ICAC
meeting up there in Washingtonstate.
Hit me up, I'll bring somestickers, so say hi to me and I
give you a sticker again assupplies.
Last, if I run out.
I'm just going to give you ahearty handshake, Anyhow that's

(05:06):
what's going on.

Speaker 2 (05:07):
So also, we have a big anniversary this week, so on
Sunday the podcast actuallyturned one year old on Sunday.
We have now been doing this fora whole year.

Speaker 1 (05:19):
Can you believe it?

Speaker 2 (05:20):
It's crazy.
I cannot.

Speaker 1 (05:22):
How many episodes?
20, what?

Speaker 2 (05:24):
There were 20 somethings for the first season.
So now we're on to season two,starting today, but it's insane.

Speaker 1 (05:32):
And and I appreciate the folks that are alive, and
also if you're listening later,we appreciate you.
This podcast has been way moresuccessful than me or Heather
could have imagined.
You know wildest dreams.
Yeah, definitely, and Iappreciate, appreciate, we
appreciate the community beingbuilt around it, the
encouragement we received and,uh, and yeah, we look forward to

(05:54):
continue to build on thateffort and there's a way you can
do that, where you can actuallyproactively do that.
So we'll talk about that in inin a section a little bit later,
how you can support the podcastand make it available for more
folks.

Speaker 2 (06:10):
So last week we talked about CCL Solutions, mr
Skinny Legs script and ourplugins and tool.
I actually did a little livedemo on last time's podcast, so
if you didn't see that, check itout.
But I just wanted to quicklymention that that demo that I
gave the tool now has someupdates.
So there's now plugins forCoinbase, chatgpt, bing,

(06:34):
duckduckgo and Mozilla, and Alexwho created it tells me the
command line interface haschanged a bit and to check out
the readme, because there's beensome updates and changes to the
tool, there's also a new blogout by CCL Solutions, by Alex,
and it is about local storageand session storage in Mozilla

(06:59):
Firefox.
So it's part one of a two-partseries and it goes through in
detail the storage mechanism formozilla, just like he did with
the um, the chrome blogs, and itlays out how the data is
structured in those um filesthat you can find on on
computers yeah, I think, I thinkwhat you said, firefox right I

(07:19):
said yeah, firefox yeah, I meanthe.

Speaker 1 (07:22):
the world right now is Chrome-centric.
We know that even Microsoft'sbrowser is really Chrome Brave
and all the others, but Firefoxis still kicking it.
I'm still a Firefox user.
All habits die hard, but that'suseful.
You need to look at those.
And we have cases, reallywell-known cases, where the
examiner is focused on oh, thisWindows must be this browser.

(07:46):
It doesn't really delve intothe other ones and the data is
lost.
So the format is different in afew ways.
I haven't finished reading thewhole thing, but again, it's a
great resource.
The document is a resourcedocument you can use later.
Hey, I got a Firefox browser.
When you're going to delve indepth, then do that.
Most tools I'm not going to sayall, but most tools they're

(08:07):
oblivious to this type ofstorage.
If it's not SQLite history,they're like they ignore it.
And local sessions and localstorage and some of the
underlying structures, b-levelDB or whatever it is.
We need to consider those.
It's not if it's, we have youknow.

Speaker 2 (08:24):
Yeah, definitely so.
I'll put the link to the blogand the link to the Mr Skinny
Legs tool on GitHub up in theshow notes at the end.

Speaker 1 (08:36):
Yeah, always check the show notes.
We have a whole bunch of linksthere and some stuff that we
talked so you can follow up onyour own later.

Speaker 2 (08:43):
Another thing that was announced is the SANS
Difference Maker Awards stuffthat we talked so you can follow
up on your own later.
Um, another thing that wasannounced is the sans difference
maker awards.
So nominations for thedifference maker awards are open
now and it's going to be openthrough friday, september 13th,
at five o'clock eastern time.
Um, the finalists for theseawards will be announced in
mid-October and then theDifference Maker Awards will be

(09:06):
held at Washington Hilton inDecember, December 15th.
So there's some categories thatare open for these awards.
There's article or book of theyear, people's champion of the
year.
Diversity champion of the yearinnovation of the year so open
source.
Or product tool, podcast, livestream, video series of the year

(09:28):
innovation of the year so opensource.

Speaker 1 (09:31):
Or product tool podcast.
Live stream video series of theyear.
I knew you were going to dothat.
Oh, I got a cough.

Speaker 2 (09:36):
What was that again?
The what of the year again?
What category?
Podcast.
Live stream video series of theyear.

Speaker 1 (09:43):
I thought you were going to at least let me get to
the end of the list.
Oh no, no, I got some cough allof a sudden, but I'm good now
Go ahead, please continue.

Speaker 2 (09:49):
Rising Star, team of the Year, practitioner of the
Year, ciso of the Year,cybersecurity Company of the
Year and Lifetime AchievementAward.
So those are all of thedifferent categories.
You can go right over to theSANS website and I'll have the
link in the show notes as well,but it's up on the screen now so

(10:10):
you can go right over andnominate your favorite people
favorite podcast, if you want,right on that website.

Speaker 1 (10:17):
Look podcast and live stream.
You know, this just happens tobe both.
Look at that.

Speaker 2 (10:22):
I mean, what a coincidence.

Speaker 1 (10:28):
And all kidding aside , yeah, please, please, support
and I'm not ashamed to actuallyask folks, supporters of the
podcast, the listeners or theviewers, as yourself, to
nominate us.
Right, those nominations aregood, first of all, all because
they recognize the work that'sbeing done.
But, from from our perspectiveas podcasters, live streamers,

(10:50):
um, it's, it's a way of ofgetting more people involved,
right, if people know the showexists, that they can
participate, that we cancollaborate, be in the chat and
build more community, then it'sbetter for everybody, and and
and if not not only with withshow, but also make your own
shows.
I don't think there's enoughand you tell me what you think
about this, heather but I don'tthink there's enough shows that

(11:10):
are specific for digitalforensics, because the stuff
that I see is digital forensics,but it's more infosec, right,
or red teaming shows and what'sthe latest exploit or what the
ransomware?
This is specifically fordigital forensics and we give it
a little of a tinge of kind oflaw enforcement based, because
that's where our background is.
I mean, I think that would be areally good thing to develop

(11:32):
even more so.

Speaker 2 (11:33):
Yeah, definitely, I 100% agree with that.

Speaker 1 (11:36):
Yeah, so what do people need to do, Heather, to
support us in this way?
Tell?

Speaker 2 (11:41):
us With the difference maker with this.
Yeah, what they need to do oh,go right over to the website and
um just fill out the nomination.
I you have to go in and umchoose who, who you want to vote
for, obviously and then it asksyou why there's like a whole
section on on why, why we orwhoever you're nominating,
deserve the award exactly.

Speaker 1 (12:02):
I mean, you learned something new, you were able to
get answers, meet with people,do whatever it is, you put it
there and and hopefully thatwill get us nominated.
So thank you, thank you aheadof time, everybody um, all right
.

Speaker 2 (12:19):
So recently there was an article and I'm trying to
think I was in AP News and thearticle kind of summarized is
about police officers startingto use AI chat bots to write
their crime reports and chat GPT.
How there's actually an optionfor chat GPT to not just aid the
officer in writing the reportbut actually writes the report

(12:52):
for them.
So AI writes the report.
I see so many things wrong withthis, but I'm letting you go
first.

Speaker 1 (13:00):
Look, I mean so.
So I mean, let's be clear, theway they, the way they're
advertising it, is that the AAis helping, right, but in this
case, helping which you'recorrect, helping is like here's
your report, yeah, and the ideais that the officer will go in

(13:21):
and try to finish that reportand make sure it's good.
You have to give me a secondhere because I'm like halfway,
you can't speak.
Hold on, okay, can you?
Can you hear me still?
yes I'm sorry, everybody allright.
So it goes and writes the thing.
So literally what the tool isdoing is goes through that, that

(13:42):
video and whatever the toollistens to, we'll make some how
can I say this AI conjectures.
I'm going to call it conjecturebecause I'm being, I guess,
kind to the AI and putting itthere for you and I see a lot of
problems with that.
Right, Look, can I get in mysoapbox, Heather?

(14:03):
Is this my soapbox?

Speaker 2 (14:04):
moment.
It's your time, it's your time.
It's your time, your time toshine.

Speaker 1 (14:09):
Well, it's not so much shine, it's me.
Just, you know, I was going tosay something, but I'm going to
transcend from myself.
I'm going to say defilingsomebody's cornflakes, how about
that?
Making it undigestible?
Look, this is the deal, okay,Is it?
Look, I wear body cams, right,when I go out and do work, right
?

(14:29):
Is it cumbersome to go out afteryou're done with the op and
kind of have your recollection,look at the video and do your
report?
Yeah, it's cumbersome,especially and I don't use them
that much when you're an officerthat's on the road.
You're gonna be doing that alot, right, so it sucks.
I mean, did you get into thistype of law enforcement work to
write, uh, uh, body cam reports?

(14:52):
Of course not.
So, like I understand, likedon't get me wrong, um, but, but
this is a deal with this typeof stuff.
Uh, I'm gonna.
I'm gonna explain my thoughtprocess, or at least my opinion,
which, by the way, I mean weneed to say this the opinions
expressed in the show do notreflect the opinions or the
policies or or whatever of ouremployers.
Opinions are only our own andthey're subject to change at any

(15:14):
time.
okay, thank you everybody that'sour lawyers, and by lawyers I
mean, uh, ourselves, okay, so so.
So, after the disclaimer, thisis the thing I remember when I
was growing up and I used to bea church kid, right and in the
mid 80s, early 90s, when I wasgrowing up, there was this thing
about preachers taking rockmusic or heavy metal music and

(15:37):
they would play it normally andyou hit the guitars in the song
and then they would take it andplay it backwards and back in
the day.
For the kids that are maybelistening listening, there was a
thing called tapes and youremember the tapes you remember?
oh, I mean, of course you're,you're my age, yes, I know you.
I know you're in denial, butyes, you are.
So you will go.
And you could actually play thetape backwards, like and when

(16:00):
it goes backwards, you know itsounds like like the words
backwards, right and they wouldplay it to you and they were
like, do you hear that?
And I'm like, no, I heard somegarble.
No, no, listen to it.
What they recorded saying isand since it's like a religion,
they would say you know, thedevil is king or something like
nefarious about evil.

(16:20):
And you listen to it and you'relike play it again.
And then by the second or thirdtime you're like you know what?
I think?
Yeah, I think I hear it too.
You know, really, did youreally hear it?
Or or was your ear attuned tohear what they're telling you
that you need to hear?
Right, and and the article andwe're gonna put put that article

(16:41):
, the links in the show notesgives an example of how this
officer is saying this is agreat tool.
I was doing my report and atsome point an officer said I
think it's the vehicle is colorX, right, and he goes and this
isn't the article.
I did not even remember that.
It's right, he said that, so Iput in my report.
So, okay, you only knew itbecause you heard it later,

(17:04):
right, that that like, andthat's that's a hard thing,
because if you later come andsay I took this actions that you
see here based on things that Iheard, um, did you really hear
them?
Or was it because of therecollection, and not even
recollection because you werewatching the video?
It's because you're reading theAI transcript of the event,
right?
And that leads to my example asecond ago about sounds, human

(17:29):
nature and folks can look thisup.
There's a thing calledpareidolia Hopefully I said it,
pronounced it correctlyPareidolia.
What is that, heather?
Have you looked at the skiesand seen like a bunny and faces
at any point in your life, orseen, of course?
I mean, yeah, who hasn't?
Right?
We have evolved with a sense ofseeing meaning and patterns
where sometimes they're not, andthe reason for that?

(17:49):
It's pretty obvious and clear,right?
Imagine our ancestors, someprimates walking on the savanna,
and they come across somethingin the grass and they jump back,
you know, thinking it might bea snake.
And it happens not to be asnake, it happens to be a stick,
okay, well, okay, I mean, Ididn't need to jump, but I
jumped anyways because it mightbe a stick.

(18:10):
You know, I saw a stick wherethere was no stick.
But imagine if humanity didn'tdevelop that and they saw that
thing and didn't jump and ithappened not to be a stick.
You know, you know well theancestors that didn't have that
sensibility of seeing snakeswhen they were actually sticks.
They're dead, so they didn'tprocreate.

(18:32):
So us, the ones that see snakeswhere there's a stick, we're the
ones that got here.
Right, does that make sense?
But you can expand that to ourthought process.
It's part of our evolutionarybrain, our lizard brain.
We see patterns where there arenone right Now.
Imagine this Imagine that theAI listens to a sound and makes
a determination that the soundmeans X or Y, and then you

(18:53):
listen to the sound too, butthen you read the AI report and
you're like you know what?
I think the AI report?
Yeah, you know what?
Yeah, that's what it is.
Then whose recollection is thisright?
Is it the ai?
So is it yours?
Does that make sense, sense toyou?

Speaker 2 (19:07):
that definitely makes sense.
And then I mean, I know you'regoing to go here in just a
second, but whose is it andwho's testifying?

Speaker 1 (19:18):
I, I, I look.
I don't want to say like aluddite or luddite, I think
that's what it is.
It's our folks that were kindof anti-technology for different
reasons.
We're not going to go into theterm in detail, but I don't want
to sound like a Luddite orlooted Luddite, I think that's
what it is.
It's our folks that were kindof anti-technology for different
reasons.
We're not going to go into theterm in detail, but I don't want
to look, we're technologists,right, we love, we love our
computers, we love technology,we love all these things.
But also, as law enforcement,you know folks that work in this
field.
I'm really troubled by thattype of views where the AI will

(19:48):
go and listen or look at thevideo, look in quotes right,
they don't have eyes, but youknow what I mean Kind of look
through it and make somedeterminations and you say well,
the responsibility ofdetermining what's correct and
incorrect is going to be on theofficer or the agent that's
going through it.
But that's the thing, right,that AI or that video through
the AI is going's going toinfluence the investigator or
the investigator, but theofficer, not the other way
around, like there is nodiscussion with the AI.

(20:10):
I think you, you got it wrong.
Let's, let's have a, let's kindof go through it together.
This, that's not how it goes,and I think we're going to be
offsetting, not offsetting,that's not the word.
Offloading were offloading,sorry, offloading some of that
responsibility to theseautomated systems.
And you know it's like Iactually have a comment here in
the chat.
Can you read it, heather,please?

Speaker 2 (20:32):
But what if your recollection is correct, based
on the AI's conjecture?

Speaker 1 (20:37):
Well, it's correct, right, that's a good point, it's
correct and that's the wholething.
Some of the decisions that wemake as law enforcement officers
, they cannot be viewed with thelens of hindsight after the
event.
You have to look at the lens ofthe moment and when we're
actually doing this, we're doingit through a hindsight view to
kind of support X action we didat the moment, and hopefully

(21:00):
folks understand what I mean bythat.
If I make some decisions basedon some facts at the moment, it
should be understood and judgedby those facts Coming up later
and kind of like fixing thosesettings because I have more
data that I did not have at themoment.
To me it's troubling.
I mean, does that make sense?

Speaker 2 (21:18):
Yeah, definitely it's very troubling.
So I don't know if anybody sawour post from the podcast last
week, but we use AI to come upwith the description for what
the content of our podcast iseach week, and last week's AI
was so horrifically bad that Ijust left it because I thought

(21:38):
it was funny and put inparentheses that that is not our
description.
It was the AI's description,but some of it I don't even know
where it got some of the stuffit said.
Like seriously, it made nosense to me.
And then I was looking throughour old podcast for an example
to read here said I don't evenremember what you did actually
say, but the AI transcribed whatyou said as calling me a

(22:16):
proficient steed checker of toolperformance and the header of
the Utah 46 World B with caps.
I don't even know what you said.
It wasn't that.

Speaker 1 (22:26):
You aren't, are you sure?
I know you've been hanging outin Utah a lot.

Speaker 2 (22:30):
And I'm a steed checker, I mean I guess I have a
new job.

Speaker 1 (22:36):
Is that where people sit on horses?
Is that what it's called Asteed?

Speaker 2 (22:39):
I'm not 100% sure what it is.
I know you didn't say it,though.

Speaker 1 (22:49):
Look, half of those words are totally unknown to me.
I don't.
I don't think my accent wouldallow me to pronounce them
correctly anyways.

Speaker 2 (22:53):
So yeah, just just an example of how how it can get
it wrong.
I mean, I think I, my personalopinion is ai's got to get a lot
better and a lot more accuratebefore I would let it write any
reports for me.
And if I let it write a reportfor me ever, it would be checked
800 times before it went outthe door.

Speaker 1 (23:14):
Oh yeah, and again, it's tough because the AI will
influence us right, when weoffload some of that
responsibility to an automatedsystem, we're not checking the
automated system.
The human nature is to let theautomated system influence us,
because I believe that the waywe've been brought up, you know,
this system is really complex.
This system is really accurate.
It's because they're not goingto sell it as inaccurate,

(23:36):
they're not going to sell it ashey, you know what.
Ai sometimes has some crazyfantasies or illusions, you know
.
So just keep that in mind.
Nobody sells the product likethat you know, Right right.
And I want to go back a second.
So the chat is saying you know,the body-worn camera should not
be used for report writing.
It's solely based at the moment.
And I want to make some pointclear.

(23:56):
What I'm trying to say andagain, it's my opinion, not my
employers you take actions andthe body-worn cameras record
those actions and they standalone, right, and they're good
to record what happened at themoment.
What I'm mentioning is thatthen an AI comes and takes that
recording and those sounds andmakes an interpretation based on

(24:18):
its own model of what's saidand what's done.
And that's different Because,if I'm looking at and again,
body-worn cameras have somelimitations because body-worn
cameras have one angle.
Body-worn cameras are not 360.
They cannot get audio frommaybe at the other side of the
house or the room.
So this will always belimitations of what is being
recorded.
But that records what the anglecan see and what it can be

(24:41):
heard, and that's it what it canbe heard, and that's it.
Adding that extra level of AIto add interpretation or to
summarize it for you now, it'sdifferent.
We're not talking about what Ibelieve in the moment analysis,
but what the AI believes thatsomething was said or something
was heard or something was seenand I don't look.

(25:02):
How can I say this If humantestimony is not the most
reliable thing?
You know, I don't think AIinterpretation of audio or video
is any better.
And again, just off saying, well, let's have the AI give it a
crack, give a crack at it andthen have the human verify it,
I'm worried that our biases willcreep in, and that's something

(25:25):
I said before on the podcast.
We're so used to saying, well,we shouldn't have biases, and
that's a lie.
Everybody will have biases.
The question is, what biasesare we going to try to establish
for ourselves?
A bias in favor of truth?
A bias in favor of honesty?
A bias in favor of what thetruth is or not?
Right, because nobody'sunbiased.

(25:47):
We have to work on what ourbiases are and the rules I say
rules, but the procedures of ourfield guarantee that those
biases are kept in check.
Right, and that's why it's ascience, right, but I don't know
.
Again, this is a strong opinionnow.
Again, I can change tomorrow.
I'm open to change.
I'm open to change.
I'm open to being shown thatthis technology is different or

(26:10):
that there's some sort ofprocedural guardrails for it.
Right, some rules, someregulations.
Maybe this type of analysiscannot be used on
officer-involved shooting, maybeit can only be used on a car,
not even car stuff.
That's not a good example buton some maybe non-felony cases
again, I'm making this up youknow where the stakes are not
that high, and then maybe thatwould be a good tool for the

(26:33):
type of intervention or lawenforcement activity that's not
high stakes.
And what I mean by high stakesis, you know you're going to
really limit the freedom ofsomebody or, you know, maybe the
life of somebody in thatscenario.
So I don't know.

Speaker 2 (26:50):
I think the article did mention too that there's
like a, not a disclaimer, butlike a line in there that says
this report was writtenutilizing AI.
In the article, yeah, If Irecall correctly.
If I recall correctly, yeah.
So I mean, if I were a defenseattorney and the article or the

(27:10):
the report submitted to courtsaid that it was written by ai,
I mean I would have a majorproblem with that.
I would think the defense wouldhave a major problem with that.

Speaker 1 (27:17):
Like wait a minute but, but I think the disclaimer
is needed.
I think, what do you think?

Speaker 2 (27:22):
yeah, I think it's needed too.
Definitely, but I can see thatbeing challenged a bit and maybe
and maybe it should right umyeah yeah, the but disclaimer is
needed and it should be part ofdiscovery right in our field.

Speaker 1 (27:36):
we need to disclose and and I remember I remember
back in the day when disclosingour tools was kind of like, no,
we cannot do that because wedon't want the bad guys to know
what tools we're using.
But now the latest rules offederal procedure require you in
your documentation to list outall the tools and versions that
you use, and I'm sorry justhaving the AI go through it for

(27:57):
you.
That's a tool.
That is a tool and that needsto be disclosed, and disclosed.
In what capacity was this doneand how much weight that AI
model has in determining whatthe evidence was or what the
report said.
And we're blazing new ground inthat area.
I'm just worried that we'reblazing new ground as opposed to
slowly, methodically.

Speaker 2 (28:19):
Let's make sure it works.

Speaker 1 (28:21):
Yeah, we're going really fast.
Again, my opinion can change atany time.
I'm open to new ideas and newthought processes, and I love
being proven wrong.
I love being proven wrong.
The more wrong I am, thehappier I am, because that means
I learned something, that meansI grew, so I'm all for that.

Speaker 2 (28:40):
So other news Magnet Forensics has acquired MedEx
Forensics.
They've acquired anothercompany.
So if you don't know what MedExForensics is, it's a business
that's dedicated to verifyingthe authenticity of digital
media files, identifyingdeepfakes, synthetic media and

(29:00):
AI generative AI.
So MedEx is joining Magnet andthey will be building on their
existing partnership, becausethey already had an existing
partnership before theacquisition.
They are also going to havewell, magnet's going to have an
add-on where Med-X I believeit's going to be part of Magnet

(29:22):
Griffi, so there'll be an add-onwith Med-X's video
authentication platform inMagnet Griffi.
So there'll be an add-on withMedix's video authentication
platform in Magnet Griffi.

Speaker 1 (29:30):
Yeah, and that's something I.
I mean, we saw the writing onthe wall and usually what
happens with Magnet is they havea partnership with some company
and then a few months laterthey buy them out.

Speaker 2 (29:41):
Yeah.

Speaker 1 (29:43):
Or they're joined, like in the case of Greykey.
It wasn't so much they werebought out, but the parent
company, which is what's itcalled Teterabar Bravo, I think
it is.
Yeah, toma, I think Toma, sorry, toma, I got all my Greek
letters now.
Toma Bravo then decided to buythem both and then kind of put
them together Medics, and again,I haven't used their technology

(30:07):
, but I heard you know theirpresentations.
Always forget his name.
He's such a great dude, he's agreat great.

Speaker 2 (30:13):
Brandon Epstein.

Speaker 1 (30:15):
Yeah, Brandon Epstein .
He gave some awesomepresentations.
Basically how that technologyis used.
I like a lot how he mentionedthat, based on their study of
how media is generated byYouTube or Instagram or
different platforms, they canlook at a video that's been
shared or moved around, but bylooking at some embedded things,

(30:35):
it has and again, it's allproprietary, their own stuff and
they can tell you oh yeah, thiswas originated or encoded in
YouTube or in this otherplatform, and then you can go
into that and get moreinformation, possibly some
timestamps I say timestamps, butframes of reference of when
this happened.
It's pretty amazing technology.
I will say something it's got alittle mini soapbox.
This is good, this is needed.

(30:58):
I still believe, as of today,the big differentiator in the
field it's not so much theparsing, even though that's
important, it's the acquisitioncapabilities.
Uh, you wanna, you wanna be abig player in in this field.
You gotta, you gotta get thedata out, because, uh and we've
talked about this before 85, 95percent of our work alone it

(31:22):
comes from where heather yeah it, is it computers?

Speaker 2 (31:27):
sorry, you caught out for a second.

Speaker 1 (31:28):
I didn't hear what you said no, it's okay, our
workload, is it computers mostly, or what is it?

Speaker 2 (31:32):
oh yeah, no mobile devices.
It's mobile devices, right yeah?

Speaker 1 (31:35):
so if you have a company that does a parsing
product but you're notextracting out stuff, you're
gonna be behind.
All right, I say behind, butyou know you're not gonna be a
big player in the space and Iwould like to see players, big
players like them.
They are a big player, theyhave a great product.
But continue to focus on theextraction and accessing access

(31:57):
capabilities, because if we getto the data, then we can do
stuff with it in different ways.
Right, but if we don't get tothe data, then if I cannot pull
that deep possible deep fakefrom the device, then having
this capability does me no goodIf I cannot get to it to process
it right, yeah, definitely.
So I still believe that's a bigdifferentiator and more

(32:17):
companies should invest in that,because I believe again my
opinion there's not enoughcompetition and that's why
prices are going a little bit,getting a little bit out of hand
.

Speaker 2 (32:29):
Yeah, that's definitely definitely true.
So there's another tool,another new tool we read about
Recuperabit, forensic FileSystem Reconstruction.
So it's on a GitHub and it's Idon't know if it's Andrea or
Andrea Lazzarato, and I'll putthe link to the GitHub here, but

(32:56):
it's a software that attemptsto reconstruct file system
structures and recover files.
So the article says it'scurrently only supporting NTFS,
but it attempts to reconstructthe directory structure
regardless of missing partitiontable, unknown partition
boundaries, partiallyoverwritten metadata or quick

(33:18):
format.
I want to demo it on a futurepodcast.
So we'll definitely have to dothat.
I didn't have the timercapability while I'm down here
in Hoover, but I'm going to tryit out and demo it on a future
podcast and hopefully everybodywill go over to the GitHub and
give this new tool a try.

Speaker 1 (33:37):
Yeah, I'm looking forward to your testing.
I remember I mean, this type ofcapability is not new, right?
There's been products doingthis for over decades.
But I like that he's coming upwith a whole bunch of cool stuff
and again you can go look at itand get it and and download it.
It's in the GitHub.
So again, another tool in yourtoolbox, and I'm really
interested in seeing those andhopefully more support for

(33:58):
different file systems.
So again, the work that he'sdoing and this open source space
, I appreciate it.
It's a good, good, good, good,good, good work 100%.

Speaker 2 (34:12):
So we've talked about Lionel Montari's work on the
podcast many times.
I'm going to go with, like theking of the logs, of the log
files.

Speaker 1 (34:22):
He has tons of blogs on the log files, the iOS log
files.
You have tons of blogs on thelog files, the the ios log files
, folks so this is a reallyspecific sub sub uh genera of
logs yes, the ios.

Speaker 2 (34:32):
Sorry, let me add that the ios log files, um,
actually, somebody asked me justthe other day for um an answer
to something about the ios logfiles and I just sent over the
the link to lionel's blogsbecause they're excellent.
But he's going to start doingblogs of the week and the first
one dropped on Monday and it wasiOS Unified Blogs Save your

(34:53):
Conversations with Siri.
So we'll put up a link to thatlog of the week, but definitely
check out his full page becausethere's a ton of good material
on that blog.

Speaker 1 (35:06):
I mean people ask me, what are the unified loves good
for?
I mean, like, well, you want toknow, there's a big resource,
and that's something I reallylike.
I love when people specializelike that because it becomes a
resource for the whole community.
It's like the francis cooterright, he's really focused, like
like doggedly focused onphotossqlite, and that's amazing

(35:26):
because then we go there, usethat, validate and we're like 20
steps ahead.
Right, we don't, we don't allhave to reinvent that wheel
because there's there's, we gotsomebody that specializes in
that.
Now we have here a specialist.
Lionel is a specialist on iosunified logs and he shares that
with the community.
So now we go use it, wevalidate it and everybody

(35:47):
quickly grows and I wasn't awareof how useful those logs were.
I mean, I kind of knew a fewthings, but his specialization
on them has been for lack of abetter term a blessing for
everybody.
So there's a lot of, like Kevinis saying in the chat, there's
a lot of goodies there in thatUnified logs.
So if you're doing iOSforensics, you should definitely

(36:08):
definitely look into that, andthere's different ways of
getting those logs out,different tools for doing that,
so you don't have to have areally expensive tool set to get
the benefit of working withthose unified logs.
So it's pretty amazing.

Speaker 2 (36:24):
All right, I'm going to attempt to share a photo, but
I only have one screen, so bearwith me.

Speaker 1 (36:30):
um it has not when.
When we travel, that's whathappens.

Speaker 2 (36:34):
We can't carry our reminders with us my testing on
this earlier was not going well,so let's see here.

Speaker 1 (36:42):
Uh, okay we had to press send button.

Speaker 2 (36:46):
There we go there we go, boom, take it away so what
was it last week?

Speaker 1 (36:53):
I think a week ago.
So Jen.
Kaiser, he's such a good guy.
He has actually sent or made acouple of artifacts for one of
the leaps or a couple of theleaps, I think it's iOS.
So he's a collaborator.
So I appreciate him, you know,collaborating to the community.
He does that and he was talkingabout how he was.
Uh, he developed a system tomake a third party well-known

(37:20):
tool in the space better, right,and making that those changes
we, which he thought were needed, and I believe it as well.
The post is there on the screenbut I'm not going to read it.
The point is that, for his usecase, the tool was not doing the
best job it could, so he madesome changes to make it do what
he needed the tool to do right.
And that's a benefit, a benefitfor everybody, a benefit for

(37:42):
the community.
Well, for lack of a better term,this company, which will go
unnamed, decided to be a bullyand reached out to his employer
and said either you take thisout of your repo and take it out
forever or we're going tocancel the licensing agreements
for the whole company.
And this company is a worldwidecompany and the company put

(38:04):
pressure on Jan and uh, thecompany, you know, put pressure
on, jan told him hey, you needto take this down, and he did,
which, again, of course, he didright, um I, why I would?
I would have done the samething now, um I I.
This example is one company,but let's be real, uh, I I want
to talk about this because Ithink it's emblematic of the on
the industry as a whole and I Ithink it's really, uh, sad and a

(38:26):
little bit maddening.
It makes me a little bit madBecause, look, the whole space
is based.
Maybe you can get the otherpicture out.
I made a post giving somethoughts about this event.
I didn't link them together atthat point, but I'm linking them
now.
I made a post with a littlememe about describing this

(38:51):
situation that we're in, whereyou have these companies that
work in the space and you seesomebody working with your tool
to make it better or dosomething with it, and you
immediately see it as a threat,right, and the meme shows a
little flower, kind of smiley,happy, saying, like a little
face, saying making products forprofit by reverse engineering

(39:12):
others' intellectual property,and they're really happy, right,
and then the next image is theflower screaming and mad saying
when someone does the same toyour product to make it better
for free.
And look, the space is built onthese vendors and there's more

(39:32):
than one, obviously, and justthis scenario is for one, but it
applies for everybody when youtake iOS and you reverse
engineer it and you get stuffout of it or you literally
exploit it, and then you look atthe contents of that product
and then you try to make senseof it within your tool or
Android.
At least with Android you cansay Android is a little bit more
open source type of thing, so Iguess you can kind of you know

(39:56):
that's not us, but Appleproducts.
You reverse engineeringintellectual property that
belongs to somebody else, butthen you want to say that people
shouldn't work with your tooland do stuff with it for free,
when you're taking some otherproduct as a base and making
money out of it, a profit out ofit, right, and that kind of
bothers me a little bit.
I mean, do you think I'm offbase by this type of situation

(40:19):
or what?

Speaker 2 (40:19):
No, I definitely don't think you're off base.
I think I mean, if he createdsomething that makes a tool
better, call him and say, hey,can we use this?
Can we work this in some way?
It's not like he was.
He was making money off of it.
It was out there for free andit made the tool better.
So I don't understand.

(40:40):
I don't really understand.

Speaker 1 (40:41):
Yeah, it's not like he's making profit by reverse
engineering their tool rightlike, like they do when they
they I mean the industry.
When the industry reverse,reverse engineers ios and makes
money out of it.

Speaker 2 (40:52):
Yeah, and it's a bad look yeah, if there's something
out there that can make it makeit look better or make it work
better for everybody, get a holdof them and let's work together
.
I don't know, just my thoughton that.

Speaker 1 (41:05):
I don't like bullies.
I do not like bullies, I'msorry, I don't like bullies and
I think the industry needs to dobetter.
Some other vendors in the spacetry to do that consistently
reach out to the community,reach out to open source
projects and try to bring themin in different ways.
And again, I understand there'salways some limitations.
It's a business.
They need to protect theirintellect, their own

(41:26):
intellectual property, and weunderstand that.
Um, but you don't to go and bea bully, um, I I don't.
I don't appreciate that.
And this is the thing at somepoint you might be able to to
bully clients around because youare pretty much irreplaceable
in some sense.
But there will be a day whenyou might not be irreplaceable.

(41:47):
And then what Brands are built?
Not so much on the product, butthey're built on what the
product makes the user feel, howthe user feels about the
product, and this is as clear asday.
People buy overpriced Macs, notbecause there's no other
computers in the world, notbecause they're necessarily

(42:08):
better.
It's because a Mac sayssomething about you and about
how you work, and maybe you'rejust used to that right.
Just used to that right.
But if Apple started to taketheir brand and take their
clients for granted and bullyingthem.
People will look for optionswhen they feel that they're not
being a pre.
What they feel is not how theywould like to feel.

(42:29):
Does that make sense?
And it might sound silly andmaybe it is, but what the tool
does sometimes is not asimportant as how you feel.
By the use of the tool andbullies.
At some point karma is going toget you.
And again, again, again, again,again.
This is spoken to the wholeindustry.

(42:49):
This is the one company thatwill be on mention spurred the
topic, but this applies to allindustries in the field and
everybody needs to look insideand say am I being a bully with
developers?
Am I being a bully with myclients In order to get an
advantage, a temporal advantage,over the competition?
Am I sacrificing my position inthe future?

(43:11):
Am I sacrificing my goodwillwith my vendors and users and
industry observers in months andyears ahead?
Right, that is just asimportant as the one little
thing that you're trying toprevent or to allow.
I think Look, too manysoapboxes today.

Speaker 2 (43:31):
So many soapboxes I put too many into one show, huh.

Speaker 1 (43:37):
It's your fault, you know it's your fault.

Speaker 2 (43:39):
A little bit, a little bit.

Speaker 1 (43:41):
You're triggering me every five minutes.
I tend to do that, yes.
Thank you, heather.

Speaker 2 (43:50):
Well, we can move on to what's new with the leaps.
What do you have that's newwith the leaps for this week?

Speaker 1 (43:55):
Yes, so, yeah.
So let me share something, andwe talked about this briefly, I
think.
Last episode Heather Barnhart,she and her colleagues, the good
people at Celebrite and somepeople that work there.
They came out with a blogtalking about message retention

(44:17):
and for the longest, messageretention in iOS was contained.
It's a little bit of arefresher from last week.
They are contained in thecomapplemobilesmsplist with that
capital M, Believe it or not.
There's one with lowercase m,Okay, and it was kept within
that plist in a key called keepmessages for days and depending

(44:40):
on what the value was, it couldbe forever, a year or 30 days,
right or never, okay.
Well, interestingly enough, iniOS 17, that changed.
Those entries might still bethere, but they're not valid.
They're not considered anymore.
You have to look and go andfind the SS keep messages key to

(45:02):
look for those values.
And I was kind of strugglingwith some of that code but
thankfully, kevin Pagano he's inthe chat and again, he's one of
my right-hand mans and I'm soglad that I have a couple of
right hands now.
Really good people dedicated.
But Kevin is one of the OGs,right.
He came out with some code totake into consideration.

(45:25):
It's really nice because nowiLeap shows look, if it's iOS 16
or below, it's going to bethese values that you need to
consider.
If it's iOS 17, it's going tobe these values to consider.
So we give you both and you canmake those determinations based
on that.
I'm always, I'm always.
I want to see more rather thanless, and the way he approached

(45:45):
it.
Yeah, within the code.
I think it's pretty good.
So thank you, kevin, you knowwe love you.
Yes, thank you, kisses to thenewborn and you're doing a good
job, man.
I appreciate you.

Speaker 2 (45:59):
There's another new one too in the ALEAP, so Yogesh
actually added SMS backup andMMS backup files for an ALEAP.
The Android backup now usesthis format for storing SMS and
MMS data, so that has been addedto ALEAP.

Speaker 1 (46:17):
And if you're going to talk about OGs, jokesh is the
OG of the OGs Because thisproject I started it and he
actually became a co-author ofthe project and he's been really
busy.
He's a really in-demandinformation security specialist
in Australia.
He's killing it.

(46:38):
So he hasn't had the time toreally kind of delve with the
community as he used to do, um,but his work, uh, you know,
lives on through these projectsand also every so, every so
often he goes and he's so kindthat you know my assumption is
he had a need for it and hedecided to share through the
leaves to the tool.
So, uh, so you'll get you.
We also appreciate you.
The project wouldn't existwithout you.

(46:58):
I wouldn't have learned so manythings without your tutoring,
your mentoring.
So I, I I appreciate your guysto pieces.
Uh, lots of respects and, youknow, hopefully at some point he
can come back and be as activewith the community as as as he
used to be.
But again, he has a lot ofstuff going on.
So it's totally understandableand, as always, wish him even

(47:21):
more success.

Speaker 2 (47:23):
Kevin's working on stuff right now.
It looks like Another updatefix coming tonight, so we have
more things to look forward toin the leaves.

Speaker 1 (47:33):
It's a project of love.
It's a project that, geez, wetalk about it in every episode,
but I'm not going to stoptalking about it because I was
at the Sacramento and peopletold me yeah, we use the tooling
, we use it in these cases.
We had a case where the turn byturn of the Google Maps, not

(47:53):
Google Maps, but yeah, Maps yeah.
Turn by turn.
It was made a big difference inmy case.
In front of the jury and givingme all these examples or
discussing how can we give somesupport now for things they need
, and what a great platform,what a great community.
So thank you.

Speaker 2 (48:08):
Yeah, the students down here will be installing it.
I'm not sure if they're doingit tomorrow or next week on the
second week of the class, butthey'll be installing it and
trying out the leaps down heretoo.
So you'll have some, some newusers, and one of my favorite
things about the leaps is if youfind something and you need it
supported, it can be supportedwithout waiting for some you

(48:30):
know big a release of the tool.
You just add the support.

Speaker 1 (48:34):
That's my favorite thing look, I, I want to believe
that us, I say us, thecommunity, developing these
tools, we are um changing the,changing the, the space.
And I say that because recentlywe're talking with, with josh
he made me aware, josh hickman,again great friend, he works at
celebrate, great subject matter,expert on mobile devices ios

(48:55):
and android.
What a beast.
He's great.
He was telling me hey, look,now in celebrate, what we're
doing is we are, instead ofwaiting for the big release, all
the supports we have, like somelike incremental releases that
will be coming out more often,right?

Speaker 2 (49:08):
Oh, I love that.

Speaker 1 (49:09):
Yeah, it's good.
So now the coding engine, orhowever they call it, will allow
these updates as they come outand you don't have to wait for a
big release at the end of thequarter or whatever the release
schedule is.
And and kevin was saying we'rehaving this conversation and
kevin was saying, whoa, justlike the leaps, like we
incrementally add stuff.
So I'm like you know what?
I think the community shouldtake credit for that pushing the

(49:31):
vendors to yeah, send those.
If you got, you got somethinggood, send it out.
Right, don't wait to have 10,20 things.
Send it out.
Make it incremental, so sopeople can benefit from that.
And uh, I think the speed ofthe community doing that is
pushing the space to also dothat.
And if if that's the case, isthat, is that were the case?
Uh, I'm happy about it.
If that was not the case butit's still happening, I'm also

(49:52):
happy about it, so that's a goodthing I like this comment too.

Speaker 2 (49:57):
Too.
Ian Whiffen, the dude overCelebrate Decoding in PA, is a
monster.

Speaker 1 (50:04):
Ian has the respect of this podcast and the respect
of us as individuals.
I was listening some time agoto him testifying at a court and
I couldn't get.
I could hear that testimony 20times.

Speaker 2 (50:17):
Yeah, it was really good you have another update to
the leaps right Meta.

Speaker 1 (50:24):
Yes and no.

Speaker 2 (50:26):
I'll say why.

Speaker 1 (50:30):
Yeah, so, as you all know, so we got RLEAP and I was
surprised how popular RLEAP hasbecome.
We don't mention it a lotbecause RLEAP is really more law
enforcement centric.
What RLEAP does is returns.
If you're law enforcement andyou have a search warrant for
cloud data or for Snapchataccountancy Snapchat is an
example Instagram the vendorwill provide you that data in

(50:53):
whatever format.
It could be JSON, it could beHTML, which I hate.
It could be a PDF, which I alsohate, but the problem is that
it changed constantly heather.
I had just finished doingupdating all the meta insta
parsers and like in two weeksthey changed it and I'm like all

(51:15):
the hours I spent and it's HTML.
So I have to ingest thishumongous HTML and start effing
with it.
And when I had it in a prettygood spot, they changed it.
And I'm like you crazy people,you know how about you give me
some JSON instead?
You know what I mean.
So yeah, it broke, but not onlyus, it broke for everybody.

Speaker 2 (51:38):
It'll be back after a lot more hard work.

Speaker 1 (51:40):
Oh, my goodness, I don't have sample data now.
I need to get some.
Actually, that's not true.
I think an examiner in front ofme in my agency kind of pointed
me into some.

Speaker 2 (51:50):
Now I need to get time.

Speaker 1 (51:51):
Yeah, but yeah, I also need time.

Speaker 2 (51:52):
Yeah, you don't have any extra time.

Speaker 1 (51:59):
Well, I feel discouraged because I just spent
so many hours doing it and thenit all went down the drain in a
matter of two weeks and that iskind of like I need to kind of
rebuild my batteries.
Yeah, take a minute to mybatteries to charge and give it
another go, because, oh mygoodness, but that's the reality
of this field, which alsoguarantees that we will never be
out of work that's true, itwill change and we need to fill
the gap.

(52:19):
Us as examiners I say us, I meaneverybody that's listening and
or watching we fill those gapsbetween what's coming out new
and when vendors actually catchup to all those things.
So that's good stuff.

Speaker 2 (52:32):
Yeah, so we are almost to the meme of the week,
but oh wait, ian's listening.
Thank you, I'm listeningintently, but also shoveling
rock.
Okay, a whole project.
Are you in?

Speaker 1 (52:47):
prison.
You know, like back in the oldmovies they were kind of cutting
rocks and I'm kidding.
Ian, I'm kidding Ian.
Actually, the fact that Ian islistening is again it's.
How can I, how can we say this,heather?
I have a sense.
Actually, the fact that Ian islistening is again it's.
How can we say this, heather?

Speaker 2 (53:01):
Thank you, yeah, it's a surprise.
Thank you, man.

Speaker 1 (53:04):
I appreciate you listening to our humble podcast,
man.

Speaker 2 (53:06):
Yeah, definitely.

Speaker 1 (53:08):
Actually Ian's listening, Let me tell him I was
in my class the class inSacramento, Ian, I was actually
using your tool to look at levelDBs with the class and people
were really blown out by yourtool Mushi, Mushi.
I want to say Mushi, but no,it's no S in it, it's Mushi.
So we're using Mushi to look atsome of the level DBs and going

(53:29):
through how that works and Idon't think there is any other
free tool with a good GUIbecause most folks like
graphical user interfaces that'saccessible and so useful as as
mushy on that.
So if folks are not familiarwith mushy, it's a great tool
viewer.
It supports many formats, segB's ones and twos, which are not

(53:50):
supported pretty much nowhere.
He has a really nice graphicaluser interface to support those
different ways of looking atthat data.
So again, we appreciate himmaking that effort to making
that available to the communityand it's free, which is awesome
you can't, you can't beat that,it's free and uh yeah.
So, as I always say, I bet hewill agree 100 money back

(54:11):
guarantee.

Speaker 2 (54:12):
So yeah, go check it out.
So we would be to the meme ofthe week now.
But this week, uh, we posted upthat it was our one year
anniversary of the podcast.
So, um, I had asked people tolike and share our posts and
whoever did their name was goingto get um put into a drawing
for some swag, like.
Whatever I have for you.

(54:32):
I'll mail it out when I'm backfrom alabama, but I'm going to
just share my screen herebecause I put everybody's name
that shared our posts into awheel.
I love the wheel graphic I getexcited about it, like, oh, look
at that, I just have to find itnow here.
Where are we?
Okay, right here, this shoulddo it.

Speaker 1 (54:53):
Let's look at the wheel.
I don't see you anymore, okay,no, but I see it, and it has our
logo in the middle.
I don't see you anymore, okay,no, but I see it, and it has our
logo in the middle.
Yeah, I put our logo.
Yeah, I love it.

Speaker 2 (55:02):
I love it, so I'm going to spin it three times and
pick three winners Woohoo, herewe go.
Here goes number one.

Speaker 1 (55:11):
Drum roll.
Sorry D for Dan.

Speaker 2 (55:16):
You needed to share the post.
Who won?
Richard Ingress?
All right, who?

Speaker 1 (55:26):
who won?
Richard ingress.
All right, I think I have it onmy linkedin.
Yeah, you know him.
Yes, you do absolutely allright, congrats, richard.

Speaker 2 (55:30):
You're getting some sweet swag.
All right, let's spin again.

Speaker 1 (55:42):
Let's see here who won.

Speaker 2 (55:43):
Brian Hempstead.

Speaker 1 (55:47):
It's like we know everybody.

Speaker 2 (55:49):
I know Brian too yeah .
All right, let's see.

Speaker 1 (56:03):
One more.

Speaker 2 (56:04):
Let's see.
Oh yeah, let me tell you thisis totally random.

Speaker 1 (56:08):
We did not put our fingers on the scale right this
is how the program works.
Look at that of the kevin.
You won.

Speaker 2 (56:16):
You won.
You won Fair and square.
All right, I will send somestuff to the three of you when
I'm back in New York, so it'lljust be an extra week.
Sorry about that.

Speaker 1 (56:29):
Yeah, and thank you everybody for sharing the post
making people aware of the showand for listening and watching
Again.
We appreciate it.
Here are rants, at least myrants, because Heather rants,
because she, you know, she's not, she's not like that I think I
have one where I ranted well, atleast not in public.

Speaker 2 (56:46):
Yeah, true, um, so now we are to the meme of the
week.
So this week, let me go grabthat.
If I can share my screen.
I don't know what just happened, so bear with me.

Speaker 1 (57:03):
Bear with me, I'm finding it, we'll find it, we'll
find a meme.

Speaker 2 (57:06):
Ah there, let's see if I can do it.

Speaker 1 (57:09):
All right, there we go.
Describe the meme for usHeather.
What are we seeing?

Speaker 2 (57:17):
So the meme of the week has a very, very large
stack of cash with the wordsoftware, a sort of smaller
stack of cash with a 50 thatsays hardware, and a smaller
stack of cash with a 20 thatsays training.

Speaker 1 (57:30):
If, you're in this field.
You know this is true.
Sad but true.

Speaker 2 (57:36):
you know this is true that but true, yeah, the
accuracy of this picture is spoton Spot.
On Spending a lot of money onthe software, not so much on
training and hardware.

Speaker 1 (57:48):
People are training.
You have a stack of $20 billsfor training and I'm like, look,
there's a $20 bill andunderneath it there's $1 bills.
Oh and, by the way, when you'redone, make sure there's some
money left over so you can bringthat back.
Don't spend it all, and I wouldbe a little facetious about it,
but obviously I made this meme.

(58:09):
So what is part of this is meseeing this price increases kind
of go off the roof in a sense,and I'm sorry, but I got
triggered again.
Look, our business is a publicservice business, right, we're
here to protect the citizens, todefend the defenseless and to

(58:32):
apprehend the guilty.
So this is not our business notto make a profit.
Now, I understand thatproviding a service to a
business that's not for profitrequires money, which requires
them to make a profit.
I understand that.
I get it.
But, for example, if you wantto work and find abused children
and free them from their abuseor their slavery and all that,

(58:55):
all right, just having a program, and again I'm going to say it
and then I'll say sorry later.
I'm going to say it's how Ithought it.
Well, we have a scholarship fordepartments to send one officer
to be trained and use of thetools.
Or we're going to send somelicenses to some third-party

(59:19):
non-governmental nonprofits toshow our commitment to the cause
.
That's fine, but I'd ratherhave a tool that takes into
consideration the price points,takes into consideration that
the money comes from thecitizens to provide a service to
citizens.
It's from tax money.
It's not a money tree, it'staxes that come out of that.

(59:39):
To provide a service tocitizens.
It's from tax money.
It's not a monetary.
It's taxes that come out ofthat to protect the citizenship.
And a commitment to beeffective in the mission is not
by giving a few licenses out forfree or training five or six
people a year.
If you bring those prices downacross the border, everybody's
capable to do more save more,find more, release more, defend

(01:00:00):
more, protect more of thecitizens that need it.
And you might say to me andthat's why you make free tools,
because you are a really badbusinessman, you will go broke
and that's true.
I accept that criticism.
But at the same time I thinkthe industry needs to take into
account who are we serving andwhere's the money coming from

(01:00:23):
and what are the uses.
And just because you believeyou can squeeze more money out
of it because it's needed andthen try to sell or PR yourself
into how committed you are tothe mission, people will see
through it, and at least thepeople in the industry, that
work in this industry, likeourselves, we see through it.
Right?
If you're charging me and againI'm not picking one company

(01:00:45):
Notice that I use examples thatare broad, so I'm not a bully.
If I'm going to be a bully, I'mgoing to be a bully against
everybody.
All right, you know we want toserve and these tools are needed
and you need to make a profit,I agree.
But don't, don't, don't kid,don't, don't try to then kid,

(01:01:08):
you know, not lie, but try toportray yourself to my face that
you're something else.
Actually, I would rather, Iwould rather.
I would rather you have betotally transparent and greedy
about it and say it's a business, we're here to make money and
to maximize it to all ourcapable means.
And I said like, okay, I cansee that, I can understand that
right, but you really want to be?
Show your devotion to themission across the board, make

(01:01:32):
it more accessible and morefolks will be saved, More folks
will go free and more guiltywill be able to be judged and
carry the responsibilities oftheir actions.
And again, this does notreflect my employer.
It's just me talking mythoughts.
So take it for what it's worth.

(01:01:53):
I know Heather doesn't want totouch it with a 10-foot pole,
obviously.

Speaker 2 (01:01:57):
I didn't know the meme was going to turn into
another sofa.
I really set you up this week.

Speaker 1 (01:02:02):
Oh, you, you, you, you, you, you, you you.
I mean Heather.
I know.
You know you don't want totouch the topic with 10 foot
pole, but I'm going to force you.
What do you think about?

Speaker 2 (01:02:10):
it.
Yeah, I mean it's a good memethe software, the software.
It takes the whole budget.
Um, the training?
I mean you're getting trainingbut it's going to be overlooked
or reduced because of the costin other areas.
And I agree 100% that if you'regoing to support a cause, make
it easier for the people who areactually doing it and working
toward the costs.

Speaker 1 (01:02:32):
Yeah, I mean, and I feel that if it's government
work it's going to be moreexpensive as opposed to and
maybe I'm wrong, right, I don'tknow what private industry pays
for the equivalent tools.
I don't know what that meansand how that works, but I think
what we're seeing across theboard in government work is that
budgets are getting tighter forobvious reasons.

(01:02:54):
And then what do you cut?
You're going to cut on hardware, you're going to cut on
training, and that's toughbecause some of the software
depends on the hardware.
Right, the proper use of thesoftware depends on the training
.
And especially, these vendorsnow are kind of pushing out
again another soapbox moment.
They're pushing out their owntraining about the tool as a
necessary item to properly beable to testify about the tool

(01:03:15):
or to show that the tool does Xand Y, and I think that's just
another way of taking that cowand trying to squeeze more out
of it, and I don't believethat's true.
I mean, would I love to becertified in all vendor tools?
Absolutely.
Do I need to to use them andactually to even find when they
don't work and correct them?
Of course not.

(01:03:36):
Right the tool doesn't make mean expert.
Right, the tool doesn't certifyme.
I certify the tool.
The tool doesn't do theexamination, I do the
examination.
A tool is a tool.
The hammer doesn't build ahouse.
The nails don't build the wallright.
The saw doesn't make the palaceright, it's the person.
And this concept of toolingplus training is what actually

(01:03:58):
makes the house.
And having courts believe that.
I think we should, as agenciesand practitioners, we should
move away from that.
It's good to have.
But this fallacy as well ifyou're not certified in ILEAP,
you could not even talk about itand your testimony should be
suspect.
I think it's a disservice tothe science of the field.

Speaker 2 (01:04:21):
I think maybe you should start some training
courses on ILEAP and ALEAP.
You've got time for that, don'tyou?

Speaker 1 (01:04:26):
Sorry, I mean I'm kind of doing it ad hoc.
Ask for the training.
And again, a lot of credit tomy agency.
For example, I'm going to theICAC to teach the tool and my
agency supports me on that.
So I can not be more gratefulabout my bosses and my Tampa
division.
They are.
They really see that this willhelp around the country and they

(01:04:49):
support me on that and I'mblessed because not everybody
has that benefit to say, yeah,go out and make the world better
with these things that you havedone.
So I'm grateful for that.
But I hope vendors also in thespace, especially because this
is not about the folks that aredoing the grunt work like us
right in those companies.
I'm talking about, you know,ceo, board members, people up

(01:05:10):
there they actually reassess andthink what are we doing here
and who are we doing it for andfor what purposes and who are we
doing it for and for whatpurposes?

Speaker 2 (01:05:25):
And hopefully that guides their thought process as
we move along as a field and asa way of let's be honest making
money as well.
All right, that's it.
We're at the end Boom.
Thank you so much for everybodythat listened or that watched
tonight live.

Speaker 1 (01:05:37):
Thank you everybody.
Thank you, heather.
Now I need to get some nervepills to calm myself down.

Speaker 2 (01:05:43):
Yeah, sorry, rhyal Jalop, I'll bring some relaxers
or something, some Xanax nothose need to be prescribed.
And we don't do that here inthis podcast.
At most I'll have to take someTylenol.

Speaker 1 (01:05:59):
Okay, there you go.
That's the only thing I cantake.
Anyhow, no for real.
Thank you everybody, uh all thefolks in the chat.
Um, there's some, some goodcomments.
We didn't put them up on thescreen, um, but we read them and
we appreciate them and, uh,hopefully we'll be back in in a
week, a week and a half, or theother week, a week over, um, to
keep talking about what'shappening.
Anything else for the good orthe other?

Speaker 2 (01:06:18):
week, a week over to keep talking about what's
happening.

Speaker 1 (01:06:20):
Anything else for the good or the other Heather?

Speaker 2 (01:06:22):
That's all I have, thank you.

Speaker 1 (01:06:24):
That's all we have everybody, so see you next time.
Peace.
Thank you, we'll see you nexttime.