Speaker 1: Imagine waking up to an alert that your company's entire
Speaker 1: customer database has just been exposed to the public internet.
Speaker 2: Oh, that is the absolute nightmare scenario.
Speaker 1: Right, So you scramble to figure out, like what sophisticated
Speaker 1: hacking syndicate managed to breach your firewalls, only to discover
Speaker 1: there was no hack yet, none at all. A developer
Speaker 1: simply made a typo in a text file and your
Speaker 1: network automatically deleted its own security walls. And you know,
Speaker 1: under European GDPR laws, you now have exactly seventy two
Speaker 1: hours to report that personal data breach.
Speaker 2: Yeah, and you are staring down a potential fine of
Speaker 2: twenty million euros or four percent of your global revenue,
Speaker 2: whichever is.
Speaker 1: Higher, which is just wild. But I mean, it's a
Speaker 1: terrifying scenario, and it happens way more often than companies
Speaker 1: actually want to admit.
Speaker 2: It really does. I mean the physical reality we used
Speaker 2: to rely on for security, you know, the concrete building,
Speaker 2: the heavy steel vault, the single front door with a
Speaker 2: security guard, that is entirely gone.
Speaker 1: It's completely gone. Operating in this invisible shape shifting architecture
Speaker 1: where the vault might be spinning of and down a
Speaker 1: thousand times a day exactly. So whether you are prepping
Speaker 1: for a massive infrastructure meeting this week, or you're just
Speaker 1: inherently curious about the invisible plumbing that powers the modern Internet,
Speaker 1: you are in the right place to figure out how
Speaker 1: this actually works. Welcome to today's deep dive.
Speaker 2: Glad to be here for this one. It's a big.
Speaker 1: Topic, it really is. Today we are pulling from a massive,
Speaker 1: multi author dossier titled The Practical Guide to Security in
Speaker 1: the AWS Cloud, and our mission here is pretty simple.
Speaker 1: Cloud security is no longer just like an IT problem.
Speaker 1: It is a fundamental business driver. So we are going
Speaker 1: to extract the most critical insights from these expert blueprints
Speaker 1: and really build a comprehensive mental model of how to
Speaker 1: actually lock down a cloud environment. And we're going to
Speaker 1: try to do it without drowning you an acronym soup.
Speaker 2: Which is hard to do in this industry, but we'll try.
Speaker 2: What makes this particular dossier so valuable, though, is that
Speaker 2: it forces us to look past the endless catalog of
Speaker 2: security products, right It makes us understand the underlying mechanics
Speaker 2: of the cloud.
Speaker 1: Because if you don't understand the logic of the environment,
Speaker 1: you can't possibly secure.
Speaker 2: It exactly, you're just flying blind.
Speaker 1: So before we can even talk about, you know, encrypting
Speaker 1: data or setting up firewalls, the guide makes this really
Speaker 1: compelling case that we have to fundamentally rewire how we
Speaker 1: view it assets.
Speaker 2: Yeah, you can't just take an old on premise mentality
Speaker 2: and lift and shift it into the cloud. It's a
Speaker 2: complete recipe for disaster, which is.
Speaker 1: Probably the most common architectural mistake companies make. Right.
Speaker 2: Oh by far, organizations try to treat virtual assets the
Speaker 2: exact same way they treated physical hardware, and to break
Speaker 2: this habit, the text highlights this brilliant industry analogy originally
Speaker 2: introduced by Bill Baker. It's the concept of pets versus cattle.
Speaker 1: Okay, I love this analogy. So historically, on premise servers
Speaker 1: were pets, right, They were highly nurtured, uniquely named, deeply
Speaker 1: cared for. Like if your main database server started throwing
Speaker 1: aerror codes, it was an all hands on deck emergency.
Speaker 2: Oh yeah, you brought in the crash cart, you diagnosed
Speaker 2: the issue, and you basically nursed that specific, highly expensive
Speaker 2: machine back to health.
Speaker 1: But in the cloud, assets are cattle.
Speaker 2: Yes, they are purely functional, they are highly scalable, and importantly,
Speaker 2: they are designed to be easily replaced. Right if a
Speaker 2: cloud server goes down or you know, gets infected with something,
Speaker 2: you don't spend hours trying to fix it. You just
Speaker 2: terminate it.
Speaker 1: You literally just shoot it, exactly.
Speaker 2: You shoot it and let an automated script spin up
Speaker 2: a perfectly clean, identical replacement in a matter of seconds.
Speaker 1: And that fundamentally changes the entire premise of disaster recovery because,
Speaker 1: I mean, recovering a pet requires massive amounts of human
Speaker 1: intervention and delicate process to minimize downtime yep, But recovering
Speaker 1: cattle requires almost zero people, just automated technology. It completely
Speaker 1: rewrites your security posture, it really does.
Speaker 2: But to build that automated posture, you need a highly
Speaker 2: accurate blueprint, and that's where the dossier brings in Josh Thurston.
Speaker 2: He provides a methodology for mapping industry security frameworks like
Speaker 2: the NIST Cybersecurity Framework to actual technology.
Speaker 1: Because buyers and sellers are constantly getting lost trying to
Speaker 1: map a theoretical security control to like a specific software
Speaker 1: product exactly.
Speaker 2: So Thurston outlines three primitives to solve this. The first
Speaker 2: primitive asks is the control requiring people process or technology?
Speaker 1: Okay, break that down for me.
Speaker 2: So a security guard checking an ID that's people, the
Speaker 2: checklist they follow on their clipboard that is process, and
Speaker 2: the actual digital badge scanner on the wall that's technology.
Speaker 2: You have to isolate what you are actually solving for.
Speaker 1: First, that makes sense. But the second primitive this is
Speaker 1: where organizations just hemorrhage money. Oh, absolutely primitive too, asks
Speaker 1: what is the primary function of the technology you're evaluating, Like,
Speaker 1: does it fundamentally do the thing the control requires? Because
Speaker 1: vendors will constantly try to sell you one magic tool
Speaker 1: that claims to do everything identify, protect, detect, respond and recover.
Speaker 2: Which is incredibly rare in practice.
Speaker 1: Okay, let's unpack this for a second, because the guide
Speaker 1: uses a specific example of companies trying to map a
Speaker 1: SIME tool, a security information an event management tool to
Speaker 1: the NIS control labeled protect data at rest.
Speaker 2: Yes, the sign example is perfect.
Speaker 1: To me. Buying a sign to protect data is like
Speaker 1: buying a smoke detector and claiming it puts out fires.
Speaker 2: That is a great way to put it.
Speaker 1: Right, because a SIME only logs and aggregates alerts after
Speaker 1: the fact it recedes telemetry to tell you someone access
Speaker 1: the data, much like a camera recording a burglar, but
Speaker 1: it cannot physically protect the data from being accessed in
Speaker 1: the first place.
Speaker 2: Exactly, you basically mapped a detection tool to a protection
Speaker 2: requirement and it gives you a false sense of security.
Speaker 1: And why does this specific mapping matter so much for
Speaker 1: the listener's actual.
Speaker 2: Business Because when you use a framework like NIST correctly
Speaker 2: and you prioritize the actual primary function of your technology,
Speaker 2: you unlock a massive advantage. You can finally translate highly
Speaker 2: technical operational metrics into actual business language.
Speaker 1: For the board of directors, Oh that is huge. So
Speaker 1: you stop boring the board with stats about your time
Speaker 1: to detect dropping by three minutes, right.
Speaker 2: They don't care about that. You start showing them how
Speaker 2: the security team is actively decreasing the realized financial impact
Speaker 2: of residual risks. That is how security leaders actually secure budget.
Speaker 1: Makes total sense. So once that blueprint is sorted and
Speaker 1: you know your cameras aren't locks, we have to look
Speaker 1: at what we are actually protecting the payload the data.
Speaker 1: It's that data itself. And this is where companies fall
Speaker 1: into a massive, highly publicized trap. They assume moving to
Speaker 1: the cloud means the cloud provider just handles all the
Speaker 1: security for them.
Speaker 2: Yeah. Matt Bromley warns about this explicitly in the text.
Speaker 2: He says, someone else's server does not equate to someone
Speaker 2: else's problem.
Speaker 1: I love that quest.
Speaker 2: It's so true. We are operating in what's called the
Speaker 2: shared responsibility model. The cloud provider, whether that's Aws, Azure, Google,
Speaker 2: they are responsible for the security of the cloud, meaning
Speaker 2: the physical stuff exactly. They manage the physical data center,
Speaker 2: the arm guards, the actual hardware, the core network infrastructure.
Speaker 2: But the customer, you are responsible for security in.
Speaker 1: The cloud, so data integrity, identity management, compliance. That is
Speaker 1: entirely your job, one hundred percent your job. And the
Speaker 1: text provides a pretty brutal cautionary tale of ignoring this
Speaker 1: based on real industry events. They use this fictionalized rapidly
Speaker 1: scaling payment processing company called Bobby's.
Speaker 2: Bits or Bobby's Bits. They chose speedover security. They experienced
Speaker 2: hyper growth and migrated rapidly to the cloud, and to
Speaker 2: basically remove any friction for their developers, they just handed
Speaker 2: out shared administrative accounts to everyone.
Speaker 1: Wow, okay, bad start, very bad.
Speaker 2: Then they deployed no SQL database. Now, noseql is a
Speaker 2: type of non relational database that is incredibly fast and flexible,
Speaker 2: which is perfect for scaling web apps. But historically many
Speaker 2: Noseql platforms prioritize speeds so heavily that they actually deployed
Speaker 2: without default authentication enabled.
Speaker 1: Wait, so they just assumed the cloud was inherently a
Speaker 1: private network.
Speaker 2: Yep, they left the default network ports completely open and
Speaker 2: directly accessible to the public Internet.
Speaker 1: Oh man, And as the guide points out, this specific
Speaker 1: configuration error led to massive global ransomware attacks on no
Speaker 1: SQL databases back in twenty seventeen. It did.
Speaker 2: Hackers literally just scanned the Internet for open ports, walked
Speaker 2: right in and deleted the data, leaving a ransom note behind.
Speaker 1: They completely failed their end of the shared responsibility model spectacularly.
Speaker 1: But here's where it gets really interesting to me. Let's
Speaker 1: talk about the sheer physics of doing this correctly, especially
Speaker 1: for a massive enterprise. If a company has an absurd
Speaker 1: amount of sensitive data, like petabytes of it, they can't
Speaker 1: just upload that over a standard corporate Internet connection.
Speaker 2: No, it would take decades, literally decades, and it would
Speaker 2: expose the data to interception. The entire time.
Speaker 1: So how do you even get that much data there
Speaker 1: securely without exposing it over the internet.
Speaker 2: So AWS built a physical solution to this digital problem.
Speaker 2: It's called the AWS Snowmobile.
Speaker 1: Okay, a physical solution, what does that mean?
Speaker 2: It is an exabate scale data transfer service. They literally
Speaker 2: drive a forty five foot long ruggedized shipping container pulled
Speaker 2: by a semi truck directly to your corporate data center.
Speaker 1: Wait, really a semi truck, a.
Speaker 2: Literal semi truck, and the container is Tampa resistant, water resistant,
Speaker 2: temperature controlled, GPS tracked. They run massive fiber optic cables
Speaker 2: from the truck directly into your local servers, ingest the
Speaker 2: data at ridiculous speeds, and then physically drive the truck
Speaker 2: back to the AWS data center to plug it directly
Speaker 2: into the cloud.
Speaker 1: That is insane. It is basically a digital Brinks truck exactly.
Speaker 1: But once that payload is safely inside the cloud, you know,
Speaker 1: you don't just leave it sitting out in the open.
Speaker 1: The dossier details using AWS Key Management Service or KMS
Speaker 1: to encrypt everything at rest, and then they highlight Amazon Macy,
Speaker 1: which is fascinating. It's a service that actively uses machine
Speaker 1: learning to automatically discover and classify sensitive data.
Speaker 2: Yeah, Macy is brilliant. It continuously scans your storage buckets
Speaker 2: looking for patterns that match you know, credit card numbers,
Speaker 2: social security numbers, private keys and flags them. It continuously
Speaker 2: profiles the environment so you know exactly where the gold
Speaker 2: is buried.
Speaker 1: So the date is in the cloud, it's encrypted and
Speaker 1: it's classified. But where are the walls Because in the cloud,
Speaker 1: the traditional network perimeter is just entirely dead. You cannot
Speaker 1: rely on a single massive firewall at the edge of
Speaker 1: your network because your users are remote, your apps are distributed,
Speaker 1: and there's just no defining edge anymore.
Speaker 2: That's where Dave Shackelford's chapter comes in. He dives deep
Speaker 2: into the solution micro segmentation micro. Yes, we basically have
Speaker 2: to build micro revaults around every single individual asset using
Speaker 2: identity and network controls. He explains the concept of least
Speaker 2: privilege architecture, where Identity and Access Management or IM is
Speaker 2: the new.
Speaker 1: Perimeter meaning what exactly.
Speaker 2: Meaning when you create a new user or a new
Speaker 2: server in the cloud, it has an implicit deny all policy.
Speaker 2: It can do absolutely nothing by default. You have to
Speaker 2: explicitly grant every single permission.
Speaker 1: Okay, so that identity perimeter has to be paired with
Speaker 1: a granular network perimeter, then.
Speaker 2: Right, and the guide breaks down the two main tools
Speaker 2: for this network, ACLS and security groups. Understanding the mechanical
Speaker 2: difference between these two is absolutely vital.
Speaker 1: Okay, let's hear it.
Speaker 2: So, network access control lists or nacls are applied to
Speaker 2: entire subnets broad sections of your network, and importantly, they
Speaker 2: are stateless. Security groups, on the other hand, are applied
Speaker 2: to individual instances, the actual virtual servers themselves, and they
Speaker 2: are stateful.
Speaker 1: Okay, let's translate stateless versus stateful for a second. I
Speaker 1: like to think of it with a hotel analogy.
Speaker 2: Okay, let's hear it.
Speaker 1: Think of the entire hotel property as your cloud environment.
Speaker 1: The network ACL is the security guard standing at the
Speaker 1: front doors of the building checking IDs. They evaluate your
Speaker 1: credentials when you walk in, but they have no memory.
Speaker 1: They are stateless, so when you try to walk back
Speaker 1: out the front door an hour later, they have to
Speaker 1: evaluate your ID all over again. Every single packet of
Speaker 1: data is evaluated coming and going.
Speaker 2: That's exactly how an NaCl work and security groups act
Speaker 2: like the electronic lock on your specific hotel room door
Speaker 2: deep inside the building. If your key card successfully lets
Speaker 2: you into the room, the lock inherently knows to let
Speaker 2: you back out. It remembers the state of the connection.
Speaker 2: It is stateful if traffic is allowed in. The return
Speaker 2: traffic is automatically allowed out without a second evaluation.
Speaker 1: That makes total sense, But relying solely on those built
Speaker 1: in cloud controls isn't always enough for advanced enterprise security.
Speaker 2: Right Oh?
Speaker 1: Usually not, because modern cloud firewalls take this further by
Speaker 1: utilizing deep Packet Inspection or DPI. They aren't just looking
Speaker 1: at the shipping label to see where the network traffic
Speaker 1: is going. They are actually opening up the digital envelopes
Speaker 1: to look inside from malicious payloads as it traverses the infrastructure.
Speaker 2: And managing all of this is where the dossier introduces SESS,
Speaker 2: which stands for Secure Access Service Edge. It is basically
Speaker 2: a convergence of security as a service and SD one.
Speaker 1: Let's define SD one really quickly. It stands for software
Speaker 1: to find wide area network. In the past, companies bought
Speaker 1: incredibly expensive private physical network lines to connect their global offices.
Speaker 1: Very expensive SD one uses software to route traffic securely
Speaker 1: and intelligently over the standard public Internet instead.
Speaker 2: Precisely, and SaaS takes that smart routing and bundles it
Speaker 2: directly with security checkpoints. Instead of routing a remote workers
Speaker 2: traffic all the way back to a central corporate firewall
Speaker 2: just to inspect it, SAZ pushes the security checks out
Speaker 2: to the edge of the network.
Speaker 1: As close to the user as possible.
Speaker 2: Exactly, It provides identity driven protection in a completely boundary
Speaker 2: less environment.
Speaker 1: Okay, so walking down the network in the data is
Speaker 1: a great baseline, but developers are constantly renovating the building
Speaker 1: from the inside.
Speaker 2: Oh yeah, constantly.
Speaker 1: We live in the era of CICD, continuous integration and
Speaker 1: continuous deployment. In the old days, software companies pushed a
Speaker 1: massive update maybe twice a year. Today developers are writing
Speaker 1: code and pushing it live to customers multiple times a day.
Speaker 2: And the sheer speed of CICD is exactly why the
Speaker 2: industry shifted to DevSecOps. Dev sacops basically means building automated
Speaker 2: security tests directly into that fast moving assembly line, rather
Speaker 2: than waiting for a manual security review at the very
Speaker 2: end of the process.
Speaker 1: Because a manual review just creates massive bottlenecks.
Speaker 2: Exactly, and Sean McCullough's chapter introduces the dread framework to
Speaker 2: help prioritize risks in this totally chaotic environment.
Speaker 1: So dread Sandford damage potential, reproducibility, exploitability, affected users, and discoverability.
Speaker 2: Right, let's walk through how a team actually uses dread.
Speaker 2: Imagine a developer accidentally configure as a cloud storage bucket
Speaker 2: to be publicly readable.
Speaker 1: Okay, bad news.
Speaker 2: First, damage potential it is extremely high as customer data
Speaker 2: could be stolen. Reproducibility dot high. Anyone with a web
Speaker 2: browser can access it. Exploitability very easy, it requires zero
Speaker 2: hacking skills. Affected users, all of your customers. Discoverability incredibly
Speaker 2: high because automated bot nets constantly scan the Internet for
Speaker 2: open buckets, so.
Speaker 1: The dread score for that vulnerability would be maxed out
Speaker 1: across the board. The system flags it, and it gets
Speaker 1: fixed immediately, well before the team worries about like a
Speaker 1: minor bug in the user interface. But wait, let me
Speaker 1: push back on this a little bit. So what does
Speaker 1: this all actually mean. If we are automating everything so
Speaker 1: code can be deployed instantly, aren't we basically just giving
Speaker 1: ourselves the ability to deploy catastrophic vulnerabilities at leasing speed.
Speaker 2: That is such a good question, and honestly, it is
Speaker 2: the ultimate paradox of DevSecOps. Automation absolutely reduces human error,
Speaker 2: but it can hide unforeseen problems and deploy them at scale.
Speaker 2: The guide actually highlights a specific, terrifying use case for
Speaker 2: this credential disclosure.
Speaker 1: Okay, how does that happen?
Speaker 2: Well, imagine a developer is testing a database connection. They
Speaker 2: hardcode the database username and password directly into a configuration
Speaker 2: file on their laptop.
Speaker 1: Oh no, and then they accidentally commit that file into
Speaker 1: a distributed version control system like get up.
Speaker 2: Exactly, the automated CICD pipeline immediately detects the new code,
Speaker 2: it integrates, it builds it, and pushes that vulnerability live.
Speaker 2: You have now exposed your production database credentials to the
Speaker 2: world entirely automatically. This is why the pipeline itself must
Speaker 2: be threat modeled. You must implement automated scanning tools that
Speaker 2: specifically look for strings of text resembling passwords or apikeys.
Speaker 1: Right like a pre flight check.
Speaker 2: Exactly, if a c SURE is detected in the code,
Speaker 2: the tool must automatically break the build and reject the
Speaker 2: merge before it ever reaches production.
Speaker 1: It is basically like putting a metal detector on the
Speaker 1: assembly line. It stops the conveyor built before the flawed
Speaker 1: product gets out the door.
Speaker 2: Yep.
Speaker 1: So the code is secure, the network is micro segmented,
Speaker 1: and that data is encrypted. But at the end of
Speaker 1: the day, a human being is going to access that
Speaker 1: data on a device, and this brings us to the
Speaker 1: final vulnerability point, the new end.
Speaker 2: Point right because the definition of an endpoint has completely changed.
Speaker 2: It is no longer just a laptop sitting on a
Speaker 2: physical desk. In the cloud. Endpoints are provider hosted servers,
Speaker 2: virtual instances, and micro services.
Speaker 1: And securing them is completely non negotiable, which brings us
Speaker 1: back to those massive GDPR stakes we talked about at
Speaker 1: the very beginning. A compromise virtual server can lead directly
Speaker 1: to a twenty million euro fine very quickly.
Speaker 2: Visibility into these endpoints is critical, but there is this
Speaker 2: mind bending concept from the text that totally changes how
Speaker 2: we view visibility. It is called infrastructure as code or IAC.
Speaker 1: I love this concept.
Speaker 2: It's wild in the cloud, your entire network, your firewalls,
Speaker 2: your subnets, your servers. It isn't physical hardware bolted to
Speaker 2: a rack somewhere. It is literally just a text file,
Speaker 2: a template file that tells the cloud provider exactly what
Speaker 2: to build, right.
Speaker 1: It's fully programmable infrastructure exactly. It's like having a magical
Speaker 1: three D printer that can print an entire fully functioning
Speaker 1: bank vault out of thin air, and the only thing
Speaker 1: protecting that vault from being altered or deleted is the
Speaker 1: blueprint file fed into the printer.
Speaker 2: That analogy is spot on, and this is exactly why
Speaker 2: traditional antivirus is completely useless here. It's why endpoint detection
Speaker 2: and Response tools or EDR, alongside cloud native monitoring like
Speaker 2: AWS cloud Trail are so vital.
Speaker 1: Because traditional antivirus just looks for known signatures.
Speaker 2: Of malware right right, whereas EDR looks for behavioral anomalies
Speaker 2: and suspicious patterns across the environment. And cloud trail goes
Speaker 2: a step further. It logs every single API.
Speaker 1: Call made in your account, and an API call is
Speaker 1: basically just a digital request that software uses to talk
Speaker 1: to other software. Every single action in the cloud, you know,
Speaker 1: creating a user, deleting a server, changing a firewall rule
Speaker 1: is an.
Speaker 2: API call exactly so if someone maliciously or you know,
Speaker 2: even accidentally alters that infrastructure text file, they can rewrite
Speaker 2: your entire security posture in seconds. Wow, a critical firewall
Speaker 2: rule that's blocking malicious traffic can be deleted with a
Speaker 2: single backspace key. By monitoring API calls, you monitor the
Speaker 2: code that builds the infrastructure just as closely as you
Speaker 2: monitor the infrastructure itself.
Speaker 1: We have covered a massive amount of ground today. I mean,
Speaker 1: we started by realizing we needed a totally new mental framework,
Speaker 1: moving from nurturing delicate pets to managing automated cattle.
Speaker 2: Yeah, that's the foundational shift.
Speaker 1: And we learned that under the shared responsibility model, we
Speaker 1: are still completely on the hook for protecting the payload.
Speaker 1: Whether we use machine learning to find it or a
Speaker 1: forty five foot snowmobile SEM truck to.
Speaker 2: Move it, they still can't get over the truck, right.
Speaker 1: And we explored how micro segmentation uses explicit identity controls
Speaker 1: and stateful security groups to lock down this new boundaryless
Speaker 1: perimeter while SaaS protects the edge.
Speaker 2: And we secured the DevOps assembly line using the dread
Speaker 2: framework to prevent automating our own destruction, which is key.
Speaker 1: And we redefine what an endpoint actually is in the
Speaker 1: era of programmable infrastructure. But I want to leave you
Speaker 1: with a final thought to mull over, building directly on
Speaker 1: that concept of infrastructure as code.
Speaker 2: Okay, what is it?
Speaker 1: So? The guide stresses that cloud infrastructure is defined by
Speaker 1: text files and that we should treat virtual servers as
Speaker 1: replaceable cattle. But if your entire global network architecture, your firewalls,
Speaker 1: your subnets, your massive data vaults can be spun up
Speaker 1: or destroyed based on a single version controlled text file,
Speaker 1: doesn't that make that single text file the most dangerous
Speaker 1: and valuable asset your company actually.
Speaker 2: Owns well, it undeniably does.
Speaker 1: Right. If the network is just code, then a single
Speaker 1: typo doesn't just crash a server, it could accidentally delete
Speaker 1: the actual walls of the bank. Take a look at
Speaker 1: your own business's cloud footprint this week through this new lens.
Speaker 1: We'll catch you next time on the Deep Dive.