We all need certainty in our lives; we need to trust that two and two is four today and will be tomorrow.  But the more we learn about any subject, the more we’re exposed to the qualifiers and exceptions that belie perfect certainty.  It’s a conundrum for me when someone writes about cryptographic hashing, the magical math that allows an infinite range of numbers to match to a finite complement of digital fingerprints. Trying to simplify matters, well-meaning authors say things about hashing that just aren’t so.  Their mistakes are inconsequential for the most part—what they say is true enough–but it’s also misleading enough to warrant caveats useful in cross-examination.

I’m speaking of the following two assertions:

1. Hash values are unique; i.e., two different files never share a hash value.
2. Hash values are irreversible, i.e., you can’t deduce the original message using its hash value.

Both statements are wrong. Continue reading →

It’s October (already?!?!) and–YIKES–I haven’t posted for two weeks.  I’m tapping away on a primer about e-discovery processing, a topic that’s received scant attention…ever.  One could be forgiven for thinking the legal profession doesn’t care what happens to all that lovely data when it goes off to be processed!  Yet, I know some readers share my passion for ESI and adore delving deeply into the depths of data processing.  So, here are a few paragraphs pulled from my draft addressing the well-worn topic of hashing in e-discovery where I attempt a foolhardy tilt at the competence windmill and seek to explain how hashing works and what those nutty numbers mean.  Be warned, me hearties, there be math ahead!  It’s still a draft, so feel free to push back and all criticism (constructive/destructive/dismissive) warmly welcomed.

My students at the  University of Texas School of Law and the Georgetown E-Discovery Training Academy spend considerable time learning that all ESI is just a bunch of numbers.  They muddle through readings and exercises about Base2 (binary), Base10 (decimal), Base16 (hexadecimal) and Base64; as well as about the difference between single-byte encoding schemes (ASCIII) and double-byte encoding schemes (Unicode).  It may seem like a wonky walk in the weeds; but the time is well spent when the students snap to the crucial connection between numeric encoding and our ability to use math to cull, filter and cluster data.  It’s a necessary precursor to their gaining Proustian “new eyes” for ESI.

Because ESI is just a bunch of numbers, we can use algorithms (mathematical formulas) to distill and compare those numbers.  Every student of electronic discovery learns about cryptographic hash functions and their usefulness as tools to digitally fingerprint files in support of identification, authentication, exclusion and deduplication.  When I teach law students about hashing, I tell them that hash functions are published, standard mathematical algorithms into which we input digital data of arbitrary size and the hash algorithm spits out a bit string (again, just a sequence of numbers) of fixed length called a “hash value.”  Hash values almost exclusively correspond to the digital data fed into the algorithm (termed “the message”) such that the chance of two different messages sharing the same hash value (called a “hash collision”) is exceptionally remote.  But because it’s possible, we can’t say each hash value is truly “unique.”

Using hash algorithms, any volume of data—from the tiniest file to the contents of entire hard drives and beyond—can be almost uniquely expressed as an alphanumeric sequence; in the case of the MD5 hash function, distilled to a value written as 32 hexadecimal characters (0-9 and A-F).  It’s hard to understand until you’ve figured out Base16; but, those 32 characters represent 340 trillion, trillion, trillion different possible values (2¹²⁸ or 16³²). Continue reading →

When computer forensics was in its infancy, examiners collected evidence from disks by copying their contents byte-for-byte to matching, sterilized disks, creating archival and working copies called “clones.”  Cloning drives was inefficient, expensive and error prone compared to the imaging processes that replaced it.  Yet, disk cloning worked for years, and countless cases were made on forensic evidence preserved by cloning and examined on cloned drives.

Now, cloning may be coming back; not to preserve hard drives but  to collect data from mobile devices backed up online, particularly Android phones.  If I’m right, it will be only a stopgap technique; but, it will also be an effective (if not terribly efficient) conduit by which mobile data preserved online can be collected and analyzed in discovery.

Case in point: Google’s recently expanded offering of cheap-and-easy online backup of Android phones, including SMS and MMS messaging, photos, video, contacts, documents, app data and more.  This is a leap forward for all obliged to place a litigation hold on the contents of Android phones — a process heretofore unreasonably expensive and insufficiently scalable for e-discovery workflows.  There just weren’t good ways to facilitate defensible, custodial-directed preservation of Android phone content.  Instead, you had to take phones away from users and have a technical expert image them one-by-one.

Now, it should be feasible to direct custodians to undertake a simple online preservation process for Android phones having many of the same advantages as the preservation methodology I described for iPhones two years ago.  Simple.  Scalable.  Inexpensive.

But unlike the iOS/iTunes methodology, Android backups live in the cloud.  At first, I anticipate there will be no means to download the complete Android backup to a PC for analysis.  Consequently, when we must process the preserved data for litigation, we may need to first restore the data to a factory-initialized “clean” phone as a means to localize the data for collection.  That’s not to say that Google won’t eventually offer a suitable takeout mechanism; after all, Google Takeout capabilities are second to none.  But, until we can backup Android content in a way that it can be faithfully and intelligibly retrieved directly from Google, examiners may revive the tried-and-true cloning of evidence to clean devices then collecting from the restored device.  Everything old is new again.

It won’t be so bad to use this stopgap approach considering that e-discovery typically entails preservation of far more mobile sources than need ultimately be processed.  So, while backing up many online and cloning a few to clean phones certainly isn’t a perfect solution for Android evidence, it’s good enough and cheap enough that courts should give short shrift to parties claiming that preserving phone evidence is unduly burdensome or complex.  For, as my e-discovery colleagues love to say, “Perfect isn’t the standard.”  I agree.  But, neither is the standard, “we couldn’t be bothered, judge.”

I’ve been on something of an e-discovery crusade for the last few years.  No, not my Quixotic, decade-long, “Native Production is More Utile and Efficient” crusade.  This is the other, later-but-just-as-frustrating crusade I call, “Mobile to the Mainstream.”  It’s a relentless, battleship-banging effort to foster recognition that mobile devices and their online information ecosystems are the most important sources of probative electronic evidence we have today.  Unless privileged, mobile evidence should be routinely preserved and produced in mainstream electronic discovery.  Honestly, shouldn’t that be obvious to even the most casual observer of modern life?

That mobile evidence is routinely ignored in civil matters by counsel, government and industry is troubling, and defended–if defended at all–by pointing to the alleged burden and technical “forensic-ness” of marshalling phone content.  I’ve countered with articles showing the ease with which iPhone content can be preserved, extracted and searched–at little to no cost and, crucially, without separating custodians from their devices.  The “trick” for Apple iOS devices was exploiting iTunes, and it was a good trick because iTunes is free, easy to use and supported by Apple on both Mac and Windows platforms around the world.

Then, Apple lately announced it was doing away with iTunes.  ARRRRGGHHH! 😱😖😭

But, no worries, the iPhone backup methodology I’ve put forward is still going to work after Apple releases the new Catalina operating system and cleaves iTunes into dedicated apps for music, podcasts and TV.  In fact, preserving iPhones may be easier for Mac users as Apple is shifting the backup tool into the Finder app.  You’ll do exactly the same thing I wrote about but Mac users with Catalina won’t even need to use iTunes to preserve mobile evidence.  It’ll be built in.

From what I understand, Windows users will still have an app for the task, probably iTunes for the foreseeable future.  So, I’m relieved to know that the “demise” of iTunes won’t be a barrier to simple, scalable preservation of iPhone content.  Things may even get a little easier.

Is there a war on e-discovery?  Sounds like a paranoid notion, but the evidence is everywhere.  The purpose of discovery is to exchange information bearing on matters in litigation, particularly material tending to prove or disprove the parties’ claims and defenses.  The soul of discovery is disclosure of relevant records and communication, limited by privilege and proportionality. So, you’d think the focus of e-discovery would be on where information resides and the forms it takes, on how to preserve it, collect it and produce it.  That was what we talked about a decade ago, but, no more.

Now, when I look at the composition of e-discovery education, I’m flummoxed by how the tide has turned to anti-discovery topics.  Instructing lawyers how to surface information has been steadily supplanted by how to keep information at bay and defend failures to disclose. There is no balance between supporting the right to obtain information and the right to withhold it.

Proportionality is about limiting the scope of discovery.  Privacy and GDPR seek to limit access to information.  Cost control is code for circumscribed discovery.  Even cybersecurity tends to be positioned to confound discovery.  I see discussions of “streamlining” privilege logs that advocate giving as little information as possible about items withheld on claims of privilege.  Considering the regularity with which privilege claims are abused, shouldn’t we require greater specificity be brought to logging so that privilege stops being the black hole in which we hide everything we don’t want to hand over?  Privilege is anathema to evidence and must be narrowly construed.  No one talks about that.

Don’t get me wrong.  These are important topics.  Discovery needs to be just, speedy and inexpensive.  But why do we keep forgetting that there’s a comma in there?  Will we ever balance our self-interest in advancing our client’s wishes against our common interest in a justice system that serves everyone? Continue reading →

I read a couple of good articles on the e-discovery implications of the Mueller report and tweeted,

“The Mueller report underscores why image+ productions are ridiculous. Compare the OCR to the true text. It’s a mess, so search is off. Image files many times larger than the native, ergo much more costly to load, store, host, transmit. BTW: YES, you CAN redact a Word file. It’s XML!”

This bears fleshing out, and I want to do it by sharing a simple trick enabling you to peer inside the raw guts of a Microsoft Word file and understand why native redaction isn’t the pipe dream some try to make it.  But first, let’s unpack the jargon.

“Image+” or “TIFF+” productions refer to the common practice of fixing the content of a document by printing the file to a static image format like TIFF or PDF.  I use “fixing” in the sense of making something permanent, but it’s also accurate to use it the way we speak of “fixing” a cat; that is, cutting its balls off.

The “plus” in TIFF+ refers to the need to supply the native file’s searchable text and application metadata in ancillary load files to accompany the page images.  That is, rather than supply the evidence, producing parties degrade it to a deconstructed “kit” version of the evidence that requesting parties must load into review platforms to restore a crude level of searchability. This enables producing parties to suppress content (like embedded comments, speaker notes and changes in text documents) and much of the application metadata of the original.  It also neuters the evidence.  It’s no longer functional in the programs that created it, like Word, PowerPoint or Excel.

I’ve written extensively about this elsewhere (e.g., Lawyers’ Guide to Forms of Production ), and I try to present the pros and cons of TIFF+, notwithstanding my belief that the cons decidedly outweigh the pros.  It largely comes down to Bates numbers and disagreement about how and when those fetishistic Bates identifiers should be added to evidence and at what absurd cost.

TIFF+ enables producing parties to sidestep their obligation to review unprinted information for responsiveness and privilege.  Instead, they silently make that content disappear like a “fixed” cat’s testicles.  To be fair, most lawyers know so little about ESI processing that they are blissfully unaware it’s happening, so they deny it with genuine equanimity.  When you force them to acknowledge the spoliation, they fall back on claiming that, whatever they excised and didn’t review wouldn’t have been worth the trouble of reviewing or producing.  Genius, right?

Apart from what’s missing from the dumbed-down data, the big objection I offer to TIFF over native productions is the huge size difference between them.  TIFF productions are much, much fatter.  Though information and utility has been stripped from the images, the degraded set is nonetheless many times larger (measured in bytes) than the native originals.

Because most e-discovery service providers price their wares by the gigabyte volume going into, onto and out of their systems, bigger files mean bigger bills.  Much bigger files mean…well, you get it.

Perhaps you’re thinking, “Craig, you sad, sad Cassandra; how much bigger can these image sets be than their native counterparts?”  Would ten times bigger surprise you? Well, then surprise!  But, they’re usually more than ten times larger.  It’s not a one-off rip-off either.  Most hosted platforms charge you for the fatter file volume every month.  Over, and over, and over again.

Sucker. Continue reading →