Speaker 1: All right, listeners, get ready to dive deep. We've got
Speaker 1: some fascinating stuff done pack today.
Speaker 2: Yeah, this is exciting you guys sent.
Speaker 1: Us excerpts from the cert Oracle Secure Coding Standard for Java.
Speaker 2: Oh that's a good one.
Speaker 1: It's like the holy grail of secure Java development.
Speaker 2: Yea.
Speaker 1: Even James Gosling himself endorses this thing.
Speaker 2: He does. Yeah, it's the real deal. We're talking enterprise
Speaker 2: grade best practices, the stuff they use to build the
Speaker 2: systems that run well practically everything exactly.
Speaker 1: And the goal today is to pull out the absolute
Speaker 1: key nuggets of wisdom from this standard. Wow, the stuff
Speaker 1: that's going to help you guys write seriously secure Java code.
Speaker 2: Absolutely, And just to add to that, it's not just
Speaker 2: theory we're talking about here, right. The introduction of this
Speaker 2: standard actually points out that a crazy sixty four percent
Speaker 2: of vulnerability is back in two thousand and four. And
Speaker 2: this is still relevant today, by the way, Yeah, sixty
Speaker 2: four percent. They were just simple coding errors. Wow, So
Speaker 2: this is stuff that has real world implications.
Speaker 1: That is a so bring statistic. Okay, So before we
Speaker 1: get into the really nitty gritty details, let's just sort
Speaker 1: of scent the stage a little bit. What exactly is
Speaker 1: a coding standard and why should developers even care about
Speaker 1: this stuff?
Speaker 2: That's a great question. Think of a coding standard as
Speaker 2: a blueprint for secure development. It's a set of rules,
Speaker 2: a set of guidelines that are really there to eliminate
Speaker 2: those really common coding mistakes, right, the ones that we
Speaker 2: all make, let's be honest, that can just open up
Speaker 2: these huge security holes in our applications.
Speaker 1: Right, So it's all about being proactive exactly.
Speaker 2: It's all about prevention, you know, preventing these issues before
Speaker 2: they even have a chance to become a problem.
Speaker 1: And this standard is serious business. I mean, it even
Speaker 1: has different levels of conformants. Like there's nonconforming, which I
Speaker 1: guess is self explanatory, so.
Speaker 2: You're not following the rules.
Speaker 1: Conforming, you're crying. And then there's the like gold standard
Speaker 1: provably conforming, right.
Speaker 2: And those levels are there to help organizations figure out
Speaker 2: where they stand security wise.
Speaker 1: Right.
Speaker 2: But there's this really cool thing called the deviation procedure.
Speaker 2: So sometimes there are very specific reasons why you might
Speaker 2: need to deviate from a rule.
Speaker 1: Okay, so it's kind of like a break glass in
Speaker 1: case of emergency kind of thing.
Speaker 2: Exactly, but the standards really really clear about this. Security
Speaker 2: cannot be sacrificed for performance ever, that's non negotiable.
Speaker 1: No shortcuts when it comes to security.
Speaker 2: Got it now, Java itself is often considered a pretty
Speaker 2: secure language, right, I mean, what is it about Java
Speaker 2: that makes it so special in the security department.
Speaker 1: Well, Java was really designed with security in mind from
Speaker 1: the very beginning. Okay, So there are features like automatic
Speaker 1: bounds checking. You know, there's no explicit pointers in Java,
Speaker 1: which is a good thing, right. And there's this thing
Speaker 1: called the bytecode verifier that's constantly checking for violations, you know,
Speaker 1: making sure that the code is playing by the rules.
Speaker 2: So Java itself is kind of like a fortress already
Speaker 2: pretty well defended. Yeah, you could say that that even
Speaker 2: the strongest fortress can be compromised if the people inside
Speaker 2: aren't careful, right, the human element, that's often the weakest link.
Speaker 2: We can make mistakes.
Speaker 1: So even with the best intentions, developers can still mess
Speaker 1: things up. What's a common area where things tend to
Speaker 1: go wrong?
Speaker 2: Ah concurrency. Ah concurrency powerful tool for building responsive applications,
Speaker 2: but it's also like opening a Pandora's box of security issues.
Speaker 1: Yeah, concurrency the double edged sword. You've got multiple threads
Speaker 1: all running around, potentially step it on each other's toes,
Speaker 1: messing with data. It's a lot to keep.
Speaker 2: Track of exactly. You have data races where you've got
Speaker 2: multiple threads trying to access and modify the same data
Speaker 2: at the same time, right, leading to unpredictable results total chaos.
Speaker 2: Then you have visibility issues where changes made by one
Speaker 2: thread aren't immediately visible to the others.
Speaker 1: Oh right.
Speaker 2: And then, just to make things even more interesting, there's
Speaker 2: the unpredictable order in which threads might actually execute. It
Speaker 2: makes it so hard to figure out what the program's
Speaker 2: going to do.
Speaker 1: It sounds like a recipe for disaster. So how does
Speaker 1: the cert standard help us navigate this concurrency mindfield? How
Speaker 1: do we stay safe?
Speaker 2: Well? One way it does this is by really emphasizing
Speaker 2: the concept of happens before relationships.
Speaker 1: Happens before relationships.
Speaker 2: Okay, Yeah, it's a way to bring order to the
Speaker 2: chaos of concurrency. It's basically defining a strict order of operations. Okay,
Speaker 2: even when you have all these threads running around. For example,
Speaker 2: think about releasing an object's intrinsic lock that always happens
Speaker 2: before the next time that lock is acquired. It's a rule,
Speaker 2: and that helps prevent those data races.
Speaker 1: So happens before is like a set of traffic signals
Speaker 1: for threads, making sure they don't collide at intersections exactly.
Speaker 2: But how do you actually implement these happens before relationships
Speaker 2: in your code. That's where synchronization methods come.
Speaker 1: In, right, synchronization keeping those threads in check. Tell me
Speaker 1: more about these methods and how they work.
Speaker 2: Well, you've got several options, each with us own trade offs.
Speaker 2: There's volatile variables, which guarantee that changes are visible to
Speaker 2: all threads instantly. Then there are synchronized blocks, which allow
Speaker 2: only one thread at a time to access a protected
Speaker 2: section of code. And then you have atomic classes, which
Speaker 2: provide thread safe operations on individual variables.
Speaker 1: So many choices. How do we know which one to
Speaker 1: pick in a given situation.
Speaker 2: Well, the standard actually gives some excellent guidance on that.
Speaker 2: It even quotes Brian Goats.
Speaker 1: Oh yeah, I've heard of him, a concurrency guru, right.
Speaker 2: Exactly, and he says atomic classes are perfect for low
Speaker 2: contention situations. You know, when you don't have a ton
Speaker 2: of threads fighting over the same variable. But for those
Speaker 2: high contention situations blocks, you know, like those provided by
Speaker 2: synchronized blocks, those are a better choice.
Speaker 1: So choosing the right synchronization method is like choosing the
Speaker 1: right tool for the job. You wouldn't use a hammer
Speaker 1: to screw in a light bulb exactly.
Speaker 2: And speaking of choosing the right tool, another crucial part
Speaker 2: of secure coding is input validation.
Speaker 1: Uh, input validation. The golden rule never trust anything that
Speaker 1: comes from the outside world.
Speaker 2: You said it, and that means any external input user's environment,
Speaker 2: veriables data from the network, anything. Treat it all as
Speaker 2: potentially malicious, validate it, sanitize it before you even think
Speaker 2: about using it.
Speaker 1: Because if we skip that validation step, what kind of
Speaker 1: trouble are we in?
Speaker 2: Oh, the consequences can be severe. We're talking SQL injection,
Speaker 2: where malicious input messes with your database queries, command injection
Speaker 2: where attackers can run commands on your system. And then
Speaker 2: there are XML external entity attacks which exploit vulnerabilities in
Speaker 2: XML parsing.
Speaker 1: So basically, not validating input is like leaving your front
Speaker 1: door wide open with a big neon sign that says
Speaker 1: welcome hackers.
Speaker 2: Pretty much, but luckily The standard gives some very specific
Speaker 2: advice on how to protect yourself. Normalize those strings before validation,
Speaker 2: you know, make sure they're formatted consistently, use whitelists to
Speaker 2: only allow save input patterns, and sanitize that user input
Speaker 2: before you log it so you don't accidentally inject any
Speaker 2: malicious code.
Speaker 1: Okay, speaking of sneaky attacks, our source material also mentions
Speaker 1: character encodings as a potential security risk. Why is that
Speaker 1: they seem like such a low level detail.
Speaker 2: You'd be surprised how often character encoding mismatches can cause
Speaker 2: major data correction, especially when you're working with file imputed
Speaker 2: output or network stuff. Right, and the standard dives into
Speaker 2: a really tricky issue called trailing byte problem. This happens
Speaker 2: in multi byting codings.
Speaker 1: Trailing byte sounds ominous, it can be.
Speaker 2: Imagine you've got a buffer boundary right where your data
Speaker 2: gets split up, and a multi byte character it gets
Speaker 2: split across that boundary. Because of how these encodings work,
Speaker 2: those split bytes, they can get interpreted completely differently than
Speaker 2: what you intended.
Speaker 1: So it's like a word getting cut in half, and
Speaker 1: suddenly the second half takes on a whole new meaning.
Speaker 2: Exactly and It can happen even if the data looks
Speaker 2: fine at first glance. So the standard's advice is to
Speaker 2: always be super aware of your platform's default encoding.
Speaker 1: Okay, noted, always double check those encodings. Okay, get ready,
Speaker 1: We're about to go deep here. The next section in
Speaker 1: this standard is called Sneaky Subtleties. Yeah, what hidden dangers
Speaker 1: are we about to uncot?
Speaker 2: Oh? This is where it gets interesting, even for those
Speaker 2: seasoned Java developers up there. It's all about those little gotchas,
Speaker 2: those tiny details that can trip you up if you're
Speaker 2: not paying close attention.
Speaker 1: All right, color me intrigued. Give me the lowdown on
Speaker 1: these sneaky subtleties. What kind of things should we be
Speaker 1: watching out for?
Speaker 2: Well, one example is ignoring return values. The standard talks
Speaker 2: about the string dot replace method. Okay, because strings and
Speaker 2: Java are immutable, that replace method. It doesn't modify the
Speaker 2: original string, right, It returns a brand new string with
Speaker 2: the replacements. So if you ignore that return value, you're
Speaker 2: basically throwing away the results.
Speaker 1: Ah, So you have to assign that return value to
Speaker 1: a variable.
Speaker 2: Exactly, otherwise it's gone poof. Another sneaky trap is comparing
Speaker 2: boxed primitives, you know, things like integer or boolean, where
Speaker 2: primitive type is wrapped up in an object. Right when
Speaker 2: you use the double equals operator to compare those things
Speaker 2: get a little weird because of memmoization.
Speaker 1: Memoization. That's like when my web browser remembers my passwords
Speaker 1: so I don't have to type them in every single time.
Speaker 2: Sort of. It's basically cashing commonly used values to make
Speaker 2: things faster, but with boxed primitives it can cause unexpected results.
Speaker 2: Say you have two integer objects, both with the value
Speaker 2: one hundred. You'd think comparing them with moocitrals would return.
Speaker 1: True, right because they have the same value.
Speaker 2: Right, But because of memmalization, Java might be comparing the
Speaker 2: object references instead of the values themselves, so you might
Speaker 2: get a false result.
Speaker 1: So it's like you think you're comparing the contents of
Speaker 1: two boxes, but you're actually comparing the boxes themselves. That
Speaker 1: is tricky, tricky.
Speaker 2: Indeed, the standard is full of these insights. Another one
Speaker 2: is hidden side effects within assertions.
Speaker 1: AH assertions, those are the statements we use to check
Speaker 1: conditions that should be true, and if they're not, it
Speaker 1: throws an error.
Speaker 2: Exactly, But here's the catch. Assertions in Java can be
Speaker 2: turned on or off at runtime, So if you put
Speaker 2: code with side effects inside an assertion, it might not
Speaker 2: always get executed when you expect it to.
Speaker 1: Oh so it's like setting a trap, but it might
Speaker 1: not actually spring when an intruder steps on it.
Speaker 2: That's a great way to put it, and that can
Speaker 2: lead to some really unexpected and potentially dangerous behavior.
Speaker 1: Okay, so far we've talked about concurrency chaos, the importance
Speaker 1: of input validation, sneaky character encodings, ignoring return values, boxed
Speaker 1: primitive comparison, weirdness, and hidden side effects and assertions. I'm
Speaker 1: starting to see why this standard is considered like the
Speaker 1: gold standard for secure Java coding. What other landmines are
Speaker 1: we going to encounter in this deep dive?
Speaker 2: Well, locking, for one, it's crucial for thread safety, but
Speaker 2: even the most experienced developers can make mistakes that lead
Speaker 2: to deadlocks.
Speaker 1: Deadlocks those sound scary. What are they and how do
Speaker 1: they happen?
Speaker 2: Imagine a classic traffic jam. Everyone's stuck because they're all
Speaker 2: waiting for each other to move. That's essentially a deadlock.
Speaker 2: In the world of multi threaded programming, it happens when
Speaker 2: you have two or more threads that are blocked indefinitely,
Speaker 2: waiting for each other to release the resources they need.
Speaker 1: So it's like a very polite dinner party gone horribly
Speaker 1: wrong because everyone's too busy being polite to actually eat exactly.
Speaker 2: The standard recommends a specific pattern called the private Final
Speaker 2: lock Object IDIOM to prevent these kinds of deadlocks. Basically,
Speaker 2: you create a dedicated lock object that's only accessible within
Speaker 2: the class that needs to protect its data. It keeps
Speaker 2: external code from interfering.
Speaker 1: Ah, So it's like having a separate lock and key
Speaker 1: for each room in your house instead of one master
Speaker 1: key that anyone could copy exactly.
Speaker 2: And to further avoid deadlocks, the standard says, hey, release
Speaker 2: those locks in the same order you acquired them. It
Speaker 2: even uses that classic philosopher's dining analogy to illustrate the point.
Speaker 1: Philosopher's dining Okay, I'm listening.
Speaker 2: Imagine a bunch of philosophers sitting around a table, and
Speaker 2: they each need two forks to eat. If they all
Speaker 2: grab their right fork first and then wait for the
Speaker 2: left fork, nobody eats. They're all stuck.
Speaker 1: So it's like a philosophical discussion that descends into chaos
Speaker 1: because everyone is too busy holding onto their own idea
Speaker 1: is to actually listen to anyone else precisely.
Speaker 2: And this brings us to serialization, a powerful tool, no doubt.
Speaker 2: It lets you convert objects into a stream of bites
Speaker 2: so you can easily send them over a network or
Speaker 2: store them in a file.
Speaker 1: Right. Serialization making those objects travel ready. But I have
Speaker 1: a feeling there's a butt coming there is.
Speaker 2: Serialization is great, but it has its security risks. Attackers
Speaker 2: can potentially mess with the state of an object during reconstitution.
Speaker 2: You know when those bites are being converted back into
Speaker 2: an object.
Speaker 1: So it's like sending a package through the mail and
Speaker 1: someone tampers with the contents en rout, replacing those delicious
Speaker 1: cookies with something less hepatizing.
Speaker 2: That's a great analogy to prevent that kind of tampering.
Speaker 2: The Standard recommends what they call the sign then seal
Speaker 2: approach for sensitive data. It combines digital signatures.
Speaker 1: And encryption sign then seal tell me more.
Speaker 2: First, you digitally sign the object, which is like adding
Speaker 2: a tamperproof seal. Think of it like a wax seal
Speaker 2: on an old fashioned letter. And then you encrypt the
Speaker 2: whole thing to protect the data.
Speaker 1: Double, the protection, double the peace of mind.
Speaker 2: Exactly, and the standard goes even further. It says, always
Speaker 2: validate an object state after de serialization, especially if you're
Speaker 2: dealing with sensitive stuff like credit card numbers.
Speaker 1: Smart move. Never take anything for granted, especially when dealing
Speaker 1: with sensitive data. Okay, we've covered a ton of ground
Speaker 1: here already, concurrency and synchronization, input validation, character encoding, those
Speaker 1: sneaky subtleties with strings and primitives, locking in deadlocks, and
Speaker 1: even the security considerations of serialization. I'm starting to feel
Speaker 1: like a secure coding ninja.
Speaker 2: That's great, But remember this is just the beginning.
Speaker 1: Oh there's more.
Speaker 2: There is a lot more to explore in the world
Speaker 2: of secure Java coding.
Speaker 1: I'm ready for more. Bring on the next round of
Speaker 1: security wisdom, you got it.
Speaker 2: In the next part of our deep dive, we're going
Speaker 2: to tackle exception handling, how to deal with those unexpected
Speaker 2: events in a way that doesn't compromise security.
Speaker 1: Exception handling. Though it sounds like we're about to venture
Speaker 1: into the dark underbelly of Java code. I can't wait.
Speaker 2: It's going to be good. Okay, are you ready to
Speaker 2: jump back into the world of secure Java coding.
Speaker 1: Absolutely, I'm still buzzing from our last conversation. Where are
Speaker 1: we headed next on this secure coding journey.
Speaker 2: Well, there's a section in the search standard that I
Speaker 2: think you'll find particularly interesting. It's all about exceptional behavior.
Speaker 1: Exceptional behavior hmmm, sounds intriguing. Are we talking about, like
Speaker 1: how to handle exceptions in a way that doesn't compromise
Speaker 1: security exactly?
Speaker 2: Handling exceptions is crucial, but it's often overlooked from a
Speaker 2: security standpoint.
Speaker 1: Okay, I'm all ears. What kind of security risks can
Speaker 1: exceptions actually pose? Fill me in?
Speaker 2: Well, think about it. Exceptions they often carry sensitive information,
Speaker 2: oh right, Like a file not found exception that might
Speaker 2: accidentally reveal the structure of your file system to an attacker, okay,
Speaker 2: or SQL exception it could hint at the details of
Speaker 2: your database schema, stuff you don't want getting out.
Speaker 1: So it's like those detective shows where they find a
Speaker 1: seemingly insignificant clue, like a stray fiber, and it leads
Speaker 1: them to the whole crime scene. You're saying, those little
Speaker 1: exception details can be like breadcrumbs for attackers.
Speaker 2: Precisely, attackers can piece together these seemingly minor leaks to
Speaker 2: get a much bigger picture of your system's weaknesses. It's
Speaker 2: like a puzzle, and exceptions can give them those missing pieces.
Speaker 1: Okay, so how do we prevent those leaks? Do we
Speaker 1: just swallow all exceptions and pretend nothing went wrong.
Speaker 2: That's not the best approach. The key is to handle
Speaker 2: those exceptions gracefully without giving away more information than absolutely necessary.
Speaker 2: One important rule to standard highlights is to avoid exposing
Speaker 2: the original exception when you're rethrowing it. They actually give
Speaker 2: a non compliant example where a file not found exception
Speaker 2: gets wrapped in a more general io exception.
Speaker 1: But isn't wrapping exceptions considered good practice. It makes the
Speaker 1: code cleaner and it allows you to handle errors at
Speaker 1: a higher level.
Speaker 2: It is good practice, but you have to be very
Speaker 2: careful about what information you're propagating up the chain. Even
Speaker 2: if that wrapped exception isn't directly visible to the user,
Speaker 2: it might get logged somewhere, and those logs, they could
Speaker 2: be accessible to someone with bad intentions.
Speaker 1: Ah So even those hidden exceptions can come back to
Speaker 1: haunt you. It's like sweeping dirt under the rug. It
Speaker 1: might look clean on the surface, but it's still there.
Speaker 1: Lurking beneath exactly.
Speaker 2: And speaking of logging, the standard actually has a whole
Speaker 2: rule dedicated to making sure logging itself doesn't break because
Speaker 2: of exceptions.
Speaker 1: Wait, how can logging break? It seems like such a
Speaker 1: simple operation, just writing some text to a file or something.
Speaker 2: You'd think so, But imagine you're trying to log a
Speaker 2: critical security exception to the standard error stream. Now, what
Speaker 2: happens if that stream is closed or filled up? Oh,
Speaker 2: you lose that crucial information. Poof, it's gone.
Speaker 1: Yikes. So it's like having a security alarm that goes
Speaker 1: silent at the worst possible moment.
Speaker 2: Not very helpful, Not helpful at all. That's why the
Speaker 2: standard strongly recommends using a robust logging framework like Java,
Speaker 2: dot util, dot Logging, Logger, or log forge. They're designed
Speaker 2: to handle these errors gracefully, making sure your logs are
Speaker 2: always available when you need them.
Speaker 1: Right, So, even for something as seemingly basic as logging,
Speaker 1: use the right tools for the job. Solid advice. Now
Speaker 1: there was another rule that caught my eye. Do not
Speaker 1: throw undeclared checked exceptions. Why is that such a big no? No?
Speaker 2: Okay? So, in Java, checked exceptions are those that you're
Speaker 2: supposed to declare in a method signature. You use that
Speaker 2: throw as keyword, right, And that's so you're giving callers
Speaker 2: a heads up about what exceptions they might need to handle.
Speaker 1: It's like a warning label on a package. Handle with
Speaker 1: care may throw.
Speaker 2: Exceptions exactly, but there are sneaky ways to bypass this
Speaker 2: whole mechanism, like using reflection or the class dot new
Speaker 2: instance method. They can throw undeclared exceptions at runtime.
Speaker 1: Ah. So it's like sneaking a dangerous item into a
Speaker 1: package without putting that warning label on it. Someone's going
Speaker 1: to get a nasty surprise.
Speaker 2: That's a great way to put it, and it can
Speaker 2: cause all sorts of chaos because the caller isn't prepared
Speaker 2: to handle those unexpected exceptions. The standard is super clear
Speaker 2: on this, don't break the contract of checked exceptions. It's
Speaker 2: like a fundamental rule of the game.
Speaker 1: All right, no surprise exceptions, got it? What other surprises
Speaker 1: await us in the world of exceptional behavior?
Speaker 2: Well, another important rule is to always handle exceptions and
Speaker 2: finally blocks right.
Speaker 1: Finally blocks, those are the code blocks that always execute
Speaker 1: no matter what, even if an exception pops up. They're
Speaker 1: essential for cleanup tasks like closing those resources.
Speaker 2: We talked about exactly. But here's the catch. The standard
Speaker 2: warns against putting any code in a finally block that
Speaker 2: could itself throw an exception.
Speaker 1: Wait, why is that a problem? Wouldn't the finally block
Speaker 1: still execute even if it throws its own exception?
Speaker 2: It would, But here's the thing. If a finally block
Speaker 2: throws an exception, it masks any exceptions that were thrown
Speaker 2: in the triblock I'm masking.
Speaker 1: So it's like one loud sound drowning out another quieter,
Speaker 1: but more important sound.
Speaker 2: Precisely, you lose valuable information about the original exception that
Speaker 2: caused the problem in the first place. The standard even
Speaker 2: gives an example. Imagine a filestream that fails to close properly,
Speaker 2: and that resulting io exception masks a more serious security
Speaker 2: exception that happened earlier.
Speaker 1: So it's like trying to diagnose a patient's illness, but
Speaker 1: a minor symptom is hiding a much more serious underlying condition.
Speaker 2: Exactly. The takeaway here, Handle those exceptions and finally blocks
Speaker 2: for sure, but make absolutely certain that those blocks can't
Speaker 2: throw any new exceptions. You don't want to mask the
Speaker 2: real problem.
Speaker 1: Got it handle with care and don't mask those critical exceptions.
Speaker 1: This exception handling stuff is more nuanced than I realized.
Speaker 1: What's next on the agenda.
Speaker 2: Let's shift gears and talk about thread APIs. These are
Speaker 2: the building blocks for creating and managing threads, and as
Speaker 2: we talked about earlier, concurrency, when not handled carefully, can
Speaker 2: be a breeding ground for security issues.
Speaker 1: All right, bring it on, I'm ready to wrangle some
Speaker 1: threads and make sure they don't go rogue. What kind
Speaker 1: of trouble can these thread APIs get us into? Well?
Speaker 2: One very common mistake is using the thread group class
Speaker 2: for managing threads. The standard actually recommends against using.
Speaker 1: It, really, but thread groups sounds like it was designed
Speaker 1: specifically for managing threads. What's the issue with it?
Speaker 2: It turns out thread group has some limitations that can
Speaker 2: lead to unexpected behavior. For example, that active count method,
Speaker 2: the one that's supposed to tell you how many threads
Speaker 2: are running in a group right, Well, it can actually
Speaker 2: be inaccurate because of timing issues and other subtleties.
Speaker 1: So it's like relying on a faulty speedometer that might
Speaker 1: give you the wrong speed. Not ideal when you're trying
Speaker 1: to manage a fleet of threads, you need accurate.
Speaker 2: Information exactly, and just to add to that, thread group
Speaker 2: methods tend to operate on all the threads in a group,
Speaker 2: which is often too broad. The standard recommends using more
Speaker 2: modern concurrency utilities like the executor framework, which gives you
Speaker 2: much finer control and more robust features.
Speaker 1: Okay, so ditch the old school thread group and embrace
Speaker 1: the modern executor framework. Got it? What other thread API
Speaker 1: pitfalls should we watch out for?
Speaker 2: Another one is misusing the notify and notifile methods.
Speaker 1: Oh right, those are the methods you use to wake
Speaker 1: up threads that are waiting on a condition like ringing
Speaker 1: a doorbell to let them know it's their turn exactly.
Speaker 2: But the standard cautions against using notify. It only wakes
Speaker 2: up one arbitrary thread, and you have no guarantee which
Speaker 2: thread it's going to be. It might not even be
Speaker 2: the one you want to wake up, so.
Speaker 1: It's like sending a vague text message to a group
Speaker 1: chat and hoping the right person sees it.
Speaker 2: And responds exactly. A much better approach is to use notifile,
Speaker 2: which wakes up all the waiting threads and then they
Speaker 2: can figure out amongst themselves who should go next.
Speaker 1: So notifile is like making a clear announcement to the
Speaker 1: entire team, making sure everyone's on the same page. Makes sense.
Speaker 1: Is there anything else we need to know about managing
Speaker 1: those waiting threads?
Speaker 2: The standard highlights the importance of making sure waiting threads
Speaker 2: can be terminated properly. You don't want any zombie threads
Speaker 2: hanging around after they've their work.
Speaker 1: Right, No zombie threads. How do we ensure a clean shutdown?
Speaker 2: It's all about avoiding those operations that can leave a
Speaker 2: thread hanging indefinitely, waiting for a network connection, for example,
Speaker 2: or reading from a stream. If a thread gets stuck
Speaker 2: in one of those blocking operations, it might never respond
Speaker 2: to a termination request.
Speaker 1: It's like being put on hold forever, never getting to
Speaker 1: talk to a human. Incredibly frustrating.
Speaker 2: Exactly. That's why the standard strongly recommends using timeouts or
Speaker 2: other mechanisms to interrupt those blocking operations, give those threads
Speaker 2: a chance to exit gracefully.
Speaker 1: So it's all about giving those threads an escape route
Speaker 1: just in case they get trapped in a blocking operation.
Speaker 1: Good advice. Any other wisdom about thread APIs that we
Speaker 1: should know.
Speaker 2: One thing. The standard is very explicit about never use
Speaker 2: the thread dot stop method to terminate a thread.
Speaker 1: Oh really, but stop seems like the most straightforward way
Speaker 1: to shut a thread down. What's wrong with it?
Speaker 2: It turns out stop is like using a sledgehammer to
Speaker 2: crack a nut. It's a very blunt instrument, and it
Speaker 2: can have all sorts of unpredictable and potentially dangerous side effects. Okay,
Speaker 2: when you call stop on a thread, it immediately throws
Speaker 2: a thread death exception, which can interrupt those critical operations
Speaker 2: and leave your application in an inconsistent state. It's not
Speaker 2: a clean shutdown, so.
Speaker 1: It's like yanking the power cord out of a server
Speaker 1: in the middle of a critical operation. Not a good
Speaker 1: idea exactly.
Speaker 2: The standard recommends more graceful shut down techniques, like setting
Speaker 2: a flag that the thread checks periodically. Then it can
Speaker 2: exit cleanly when it sees that signal.
Speaker 1: So a gentle nudge rather than a forceful shove.
Speaker 2: Much better, much better, and that covers some critical ground
Speaker 2: when it comes to thread APIs always remember concurrency is
Speaker 2: a powerful tool, but handle it with care. Be aware
Speaker 2: of those potential pitfalls, and you'll be much better off.
Speaker 1: My head is spinning with all this knowledge. It's amazing
Speaker 1: how many subtle things can go wrong when you're dealing
Speaker 1: with multiple threads running around. This standard is definitely proving
Speaker 1: its earth as a guide through this treacherous terrain.
Speaker 2: Absolutely, and we're not finished yet. There's more to explore
Speaker 2: in this world of secure Java coding. In the next part,
Speaker 2: we'll dive into thread pools and how to manage those
Speaker 2: groups of worker threads securely and efficiently. It's going to
Speaker 2: be a fascinating discussion, so make sure you tune in
Speaker 2: all right, ready to dive back in?
Speaker 1: You bet, I'm eager to hear what other secure coding
Speaker 1: wisdom this certain standard has in store for us.
Speaker 2: Well. Next up, we're going to tackle thread pools. They're
Speaker 2: a really fundamental tool for managing concurrency efficiently, especially in
Speaker 2: server applications.
Speaker 1: Right, thread pools, it's like having a whole crew of
Speaker 1: worker threads just waiting around, ready to take on tasks
Speaker 1: as they come in.
Speaker 2: Exactly, instead of constantly creating and destroying threads, you've got
Speaker 2: this pool of eager beavers ready to jump into action.
Speaker 2: It's much more efficient.
Speaker 1: I like that analogy. So what are the key things
Speaker 1: we need to keep in mind when we're working with
Speaker 1: threadpools to make sure we're doing things securely.
Speaker 2: One of the biggest mistakes people make is using an
Speaker 2: unbounded threadpool.
Speaker 1: Unbounded yeah, meaning there's no limit to how many threads.
Speaker 2: Can be in the pool exactly. It might seem convenient,
Speaker 2: you know, like a workforce that never says no to
Speaker 2: more work, but in reality that can lead to resource exhaustion.
Speaker 2: Your application could just crash under heavy load.
Speaker 1: So it's like throwing a party and inviting everyone, you know,
Speaker 1: assuming you have unlimited food in space, things could get
Speaker 1: out a hand pretty quickly.
Speaker 2: That's a great way to put it. The standard strongly
Speaker 2: recommends using a bounded threadpool instead. You set a limit
Speaker 2: on the number of threads that can be active at
Speaker 2: any given time. It prevents your application from getting overwhelmed
Speaker 2: and crashing.
Speaker 1: So it's like setting a reasonable guest list for your party,
Speaker 1: making sure you don't run out of chips and dip.
Speaker 1: Bounded threadpool, got it? What other threadpool traps should we
Speaker 1: be aware of?
Speaker 2: Another common pitfall is creating a threadpool with a custom
Speaker 2: thread factory that doesn't set a proper thread group.
Speaker 1: Okay, remind me what a thread group is. Again.
Speaker 2: It's basically a way to group threads together for management purposes.
Speaker 2: But if you're not careful, your threads might end up
Speaker 2: getting created in unexpected places, making them hard to manage
Speaker 2: and monitor.
Speaker 1: So it's like having a bunch of construction workers show
Speaker 1: up at your site but you don't know what team
Speaker 1: they belong to or who their forman is. It's a
Speaker 1: recipe for chaos and potential accidents.
Speaker 2: Exactly the standard says you should either use the default
Speaker 2: thread factory or create a custom one that explicitly assigns
Speaker 2: a thread group. That way, you know where all your
Speaker 2: threads belong and you can keep them under control.
Speaker 1: Okay, thread organization check any other threadpool wisdom you want
Speaker 1: to impart before we move on.
Speaker 2: Yes, there's one more, really nasty problem called thread starvation deadlock.
Speaker 2: It happens when the tasks in your threadpool actually depend
Speaker 2: on each other to complete.
Speaker 1: Wait, how can threads get stuck waiting for each other
Speaker 1: if they're supposed to be working independently in a pool.
Speaker 1: That doesn't sound right.
Speaker 2: It's a tricky situation. Imagine Task A needs a result
Speaker 2: from task B. To finish, but task B is stuck
Speaker 2: waiting for task A to do something first. They're both
Speaker 2: blocked waiting for each other, and the word just grinds
Speaker 2: to a halt.
Speaker 1: It's like a bureaucratic nightmare where you need approval from
Speaker 1: Department A to get something from Department B, but Department
Speaker 1: B needs a sign off from Department A first. Nothing
Speaker 1: gets done.
Speaker 2: A perfect analogy. The standard emphasizes designing your tasks to
Speaker 2: be independent whenever possible, but if you absolutely must have
Speaker 2: those dependencies, consider using techniques like fork join. It breaks
Speaker 2: down those dependent tasks into smaller, more manageable chunks that
Speaker 2: can be executed in parallel.
Speaker 1: Fork join sounds a bit fancy. What's the basic idea
Speaker 1: behind that?
Speaker 2: It's basically a divide and conquer strategy. You split a
Speaker 2: big task into smaller subtasks, you tackle those subtasks concurrently,
Speaker 2: and then you combine the results at the end. Much
Speaker 2: more efficient.
Speaker 1: Ah. So it's like having a team of chefs working
Speaker 1: on different parts of a meal at the same time
Speaker 1: so you can get everything on the table faster. Yeah,
Speaker 1: much more efficient than having one chef try to do
Speaker 1: everything sequentially precisely.
Speaker 2: Now, let's talk about thread local variables, right.
Speaker 1: Thread local those are the very that are specific to
Speaker 1: each thread. Right. It's like giving each worker their own
Speaker 1: personal toolbox that nobody else can touch.
Speaker 2: That's the idea. They can be really useful, but the
Speaker 2: standard warns against reusing thread local variables in thread pools.
Speaker 1: Really, if the threadpool is reusing threads, wouldn't the thread
Speaker 1: local variables just get reused along with them? It seems logical.
Speaker 2: The tricky part is when a thread finishes its task
Speaker 2: and goes back to the pool, those thread local variables
Speaker 2: aren't automatically cleared, so if that thread gets picked up
Speaker 2: for a different task, the old values from the previous
Speaker 2: task might still be hanging around, potentially causing weird and
Speaker 2: unexpected behavior. Oh.
Speaker 1: I see, so it's like getting a rental car and
Speaker 1: finding someone else's stuff in the glove comparted. Yeah, not
Speaker 1: a very pleasant surprise.
Speaker 2: Exactly. The standard recommends clearing those thread local variables explicitly
Speaker 2: before a thread goes back to the pool, or you
Speaker 2: could just pass data as arguments to tasks, which is
Speaker 2: often a cleaner solution.
Speaker 1: Okay, thread local cleanup, got it. I'm really starting to
Speaker 1: appreciate how many subtle details that are to consider when
Speaker 1: it comes to multi threaded programming. This standard is incredibly
Speaker 1: helpful for navigating this tricky terrain.
Speaker 2: I agree, it's a real life saver. Now let's zoom
Speaker 2: out a bit and consider some general thread safety principles
Speaker 2: that apply beyond just specific APIs.
Speaker 1: Thread safety making sure our code works correctly no matter
Speaker 1: how many threads are running around doing their thing.
Speaker 2: Ye.
Speaker 1: What are some of those fundamental principles.
Speaker 2: One of the most important rules is to avoid publishing
Speaker 2: this reference during object construction.
Speaker 1: Publishing that this reference that sounds a bit cryptic. What
Speaker 1: does that actually mean? In practice?
Speaker 2: It basically means exposing a reference to an object that's
Speaker 2: still under construction before it's fully initialized. Okay, like assigning
Speaker 2: this to a static variable or passing it as an
Speaker 2: argument to another method during the constructor.
Speaker 1: So it's like showing off a half built house before
Speaker 1: the roof is even on. Yeah, people might get the
Speaker 1: wrong impression exactly.
Speaker 2: The problem is that another thread could see that partially
Speaker 2: constructed object and try to use it before it's ready,
Speaker 2: and that can lead to some really bad consequences.
Speaker 1: Ouch. Yeah, it's like trying to move into a house
Speaker 1: that's still a construction zone. Bad idea.
Speaker 2: The standard's message is clear, finish building that object before
Speaker 2: you give out any references to it. Don't let those
Speaker 2: other threads peek behind the curtain before the show is ready.
Speaker 1: Object construction safety check. What other thread safety gems does
Speaker 1: this standard have for us?
Speaker 2: Another crucial one is protecting shared variables. If you've got
Speaker 2: multiple threads accessing the same variable without proper synchronization, things
Speaker 2: can get messy fast.
Speaker 1: It's like having multiple cooks all trying to use the
Speaker 1: same mixing bowl at the same time. Without any coordination,
Speaker 1: ingredients would be flying everywhere.
Speaker 2: It's a great analogy. The standard says, use synchronization mechanisms
Speaker 2: like locks or atomic variables to protect that shared data
Speaker 2: from the chaos of multiple threads. Make sure everyone takes
Speaker 2: turns and plays nicely.
Speaker 1: Shared data protection check anything else we need to be
Speaker 1: aware of.
Speaker 2: When it comes to safety, the standard specifically addresses a
Speaker 2: technique called double checked locking.
Speaker 1: Double checked locking, I'm not familiar with that.
Speaker 2: It's a way people try to optimize locking by checking
Speaker 2: a condition twice, once without a lock, and then again
Speaker 2: with a lock. If the first check passes. It's an
Speaker 2: attempt to avoid the overhead of acquiring a lock unnecessarily.
Speaker 1: So it's like checking if a door is locked twice
Speaker 1: before you try to open. It seems a little excessive.
Speaker 2: The intention is good, but the standard warns that double
Speaker 2: checked locking is super tricky to get right. In Java,
Speaker 2: there are these subtle memory visibility issues that can really
Speaker 2: mess things up, can give you a false sense of
Speaker 2: security and lead to those really hard to find bugs.
Speaker 1: So double checked locking proceed with extreme caution. I'm starting
Speaker 1: to notice a pattern here. It seems like multi threaded
Speaker 1: programming is full of these seemingly clever optimizations that can
Speaker 1: backfire spectacularly if you're not incredibly careful.
Speaker 2: You're absolutely right, and that's exactly why this standard is
Speaker 2: so valuable. It's a distillation of hard one experience guiding
Speaker 2: us away from those tempting but often treacherous paths.
Speaker 1: I completely agree. Now let's talk about fileio. It might
Speaker 1: seem like a pretty straightforward area of programming, but I
Speaker 1: suspect there are some security nuances we need to be
Speaker 1: aware of.
Speaker 2: You are absolutely right. Fileio can be surprisingly tricky when
Speaker 2: it comes to security. One of the most basic rules
Speaker 2: is to always work within what we call a secure directory.
Speaker 1: A secure directory, so it's not enough to just check
Speaker 1: file permissions. We need to worry about the directory itself.
Speaker 2: Exactly. A secure directory is one where only authorized users
Speaker 2: and of course the system administrator have control. This prevents
Speaker 2: attackers from messing with files or creating new files where
Speaker 2: they shouldn't, so it's.
Speaker 1: Like having a vault where only certain people have the combination.
Speaker 2: Precisely, the standard really stresses understanding this concept of secure
Speaker 2: directories and making sure your application is playing within those boundaries.
Speaker 1: Secure directories. Check what other file io pitfalls should we
Speaker 1: watch out for.
Speaker 2: A really common mistake is forgetting to clean up temporary files.
Speaker 2: It's easy to create a temporary file for some operation
Speaker 2: and then totally forget to delete it when you're done.
Speaker 2: But over time those leftover temporary files they can clutter
Speaker 2: up your system and potentially leak sensitive information.
Speaker 1: It's like leaving your trash out on the curb and
Speaker 1: never bothering to take it to the dump. Eventually, it's
Speaker 1: going to attract some unwonted attention.
Speaker 2: Exactly. The standard suggests a few different mechanisms. There's a
Speaker 2: method called file dot delete on exit. And you can
Speaker 2: also use those try with resources blocks to make sure
Speaker 2: your temporary files get cleaned up even if something goes.
Speaker 1: Wrong temporary file cleanup check. Yeah, what else do we
Speaker 1: need to be mindful of when we're dealing with files?
Speaker 2: Another area that can trip people up is file links.
Speaker 2: You know those aliases or shortcuts that point to other files.
Speaker 1: Right.
Speaker 2: Attackers can actually exploit those links to trick your application
Speaker 2: into accessing files that it shouldn't.
Speaker 1: Oh, I see, So it's like clicking on a suspicious
Speaker 1: link in an email that takes you to a militia
Speaker 1: website disguised as something legitimate.
Speaker 2: That's a great analogy. The standard recommends using methods like
Speaker 2: file dot get canonical path, which will resolve those links
Speaker 2: and make sure you're actually dealing with the file you
Speaker 2: intended to and not some malicious substitute.
Speaker 1: Following verification check any other file io wisdom you want
Speaker 1: to share.
Speaker 2: One more. When you're reading data from a file stream,
Speaker 2: make sure you read the entire thing. Don't leave any
Speaker 2: data behind.
Speaker 1: Why is that important?
Speaker 2: Well, if there's leftover data, an attacker won't be able
Speaker 2: to get to it. So the standard says keep reading
Speaker 2: until you hit the end of the file or an
Speaker 2: exception occurs.
Speaker 1: So it's like finishing your plate at a restaurant, even
Speaker 1: if you're full. Make sure no one can sneak a itte.
Speaker 2: Exactly, filestream, cleanup, check.
Speaker 1: This file io. Stuff is trickier than I thought. Right, Okay,
Speaker 1: what's next on the agenda.
Speaker 2: Let's talk about platform security. This is all about understanding
Speaker 2: the security features and limitations of the Java platform itself.
Speaker 1: Platform security sounds like we're getting down to the nuts
Speaker 1: and bolts the Java virtual machine. Now.
Speaker 2: You could say that the standard highlights features like security
Speaker 2: managers and security policies which you can use to control
Speaker 2: what code can actually do. You can prevent those malicious
Speaker 2: actions before they happen.
Speaker 1: So it's like having security guards and access control systems
Speaker 1: in place to protect a building from intruders exactly.
Speaker 2: The standard points out common mistakes like putting security sensitive
Speaker 2: code in multiple jrr files. It's like scattering your valuables
Speaker 2: all over the place, making them easier to steal. The
Speaker 2: recommendation is to consolidate that code into a single signed
Speaker 2: jar file, making it much harder to compromise.
Speaker 1: Consolidated security check what other platform security tips do we
Speaker 1: need to keep in mind.
Speaker 2: Another really important one is to use reflection carefully. It's
Speaker 2: a powerful tool for accessing and manipulating code at runtime,
Speaker 2: but it can also introduce security vulnerabilities if you're not careful.
Speaker 1: Reflection that's the one that lets you do all sorts
Speaker 1: of magical things with code, but also has the potential
Speaker 1: to things if.
Speaker 2: You're not careful exactly, and the standard specifically warns against
Speaker 2: using reflection to increase the accessibility of classes, methods, or
Speaker 2: fields that should be private or protected.
Speaker 1: So it's like using a master key to unlock every
Speaker 1: door in a building, including the ones that should.
Speaker 2: Be off limits precisely. Reflection is a powerful tool, but
Speaker 2: it should only be used when absolutely necessary, and you
Speaker 2: need to take precautions to avoid those security risks.
Speaker 1: Reflection security check anything else on the platform security front.
Speaker 2: One more, the standard has a rule about deploying applications
Speaker 2: that can be remotely monitored whoa while that can be
Speaker 2: useful for things like debugging and performance tuning, it can
Speaker 2: also be a security risk if you leave those features
Speaker 2: enabled in a production environment, so it's.
Speaker 1: Like leaving a surveillance camera running in your house even
Speaker 1: when you're not home, anyone could be watching.
Speaker 2: That's a great way to think about it. The recommendation
Speaker 2: is to disable those remote monitoring features in production to
Speaker 2: prevent attackers from gaining access or missing with your applications behavior.
Speaker 1: Remote monitoring lockdown check. Okay, we've covered a lot of
Speaker 1: ground with platform security. What's next on our deep dive itinerary.
Speaker 2: We're down to the miscellaneous category. These are those rules
Speaker 2: that don't fit neatly into other categories, but they're still
Speaker 2: really important for writing secure Java code.
Speaker 1: Bring on that grab bag of security tips. I'm ready
Speaker 1: for anything, right.
Speaker 2: One really important rule is to always generate strong random
Speaker 2: numbers when you need them.
Speaker 1: Random numbers they're used for all sorts of things, from
Speaker 1: generating passwords to creating encryption keys exactly.
Speaker 2: But the standard cautions against using the basic Java dot
Speaker 2: util random class for security sensitive applications. Its output is
Speaker 2: actually pretty predictable, especially if you use the same seed value, so.
Speaker 1: It's like using a weak password that's easy for attackers
Speaker 1: to guess precisely.
Speaker 2: The recommendation is to use the Java dot security secure
Speaker 2: random class instead. It produces much stronger random numbers that
Speaker 2: are much harder to predict.
Speaker 1: Secure randomness Check what other miscellaneous wisdom can you share?
Speaker 2: Never hard code sensitive information directly into your code.
Speaker 1: Hard coding sensitive information. That's like writing your passwords on
Speaker 1: a sticky note and attaching it to your monitor. Anyone
Speaker 1: could see them.
Speaker 2: It's a surprisingly common practice, and it's a really bad idea.
Speaker 2: Those secrets are just sitting there waiting to be discovered.
Speaker 2: The standard recommends storing that sensitive information in external configuration
Speaker 2: files or using environment variables. That way, you can keep
Speaker 2: those secrets out of your code and much safer secret stores.
Speaker 1: Check anything else Before we wrap up this deep dive.
Speaker 2: Just a few quick points about memory management. The standard
Speaker 2: emphasizes avoiding memory leaks, which can really slow down your
Speaker 2: application and even cause it to crash.
Speaker 1: Memory leaks those are like those tiny drips from a
Speaker 1: leaky faucet. They seem small, but they can waste a
Speaker 1: lot of water over time.
Speaker 2: A perfect analogy. The standard recommends a few techniques, like
Speaker 2: using weak references and being very diligent about cleaning up
Speaker 2: resources when you're done with them. Plug those leaks.
Speaker 1: Memory leak prevention check. Wow, we've covered a ton of
Speaker 1: ground in this deep dive. Concurrency threadpools file io platform security,
Speaker 1: even those little details like random numbers and memory management.
Speaker 1: I feel like I've leveled up my secure coding skills significantly.
Speaker 2: I'm glad to hear it. But remember, secure coding is
Speaker 2: an ongoing process. There are always new threats and vulnerabilities
Speaker 2: popping up, so it's important to stay up to date
Speaker 2: with the latest best practices keep learning.
Speaker 1: Absolutely, this cert Oracle Secure Coding Standard has been such
Speaker 1: a valuable guide for us. I highly recommend it to
Speaker 1: any Java developer out there who wants to write more secure,
Speaker 1: robust code. Thanks so much for taking us on this
Speaker 1: incredible journey.
Speaker 2: It was my pleasure. And always remember everyone has a
Speaker 2: role to play in security. By putting these principles into practice,
Speaker 2: we can all contribute to making the digital world a
Speaker 2: safer place.