Monday, 16 February 2015

Keeping a Web Service Secure

This post is aimed at those tasked with developing and maintaining a secure system, but who have not had to do so previously. It is primarily a sign-posting exercise, pointing initiates in the right direction. It is not gospel; many things require common sense, and there is rarely a right answer. Everything is a trade off; performance for security, usability for development time, backup size for recovery ability. To do this effectively, you need to consider your systems as a whole, including the people running and building them.

Keeping a web service adequately secure is quite a task. Many of the things covered will simply not apply, depending on your business model. For instance, web services which use services such as Google App Engine, Heroku, or OpenShift will not need to keep up with OS patches. Those that are for intranet use only may be able to get away with weaker password policies if they're not usually exposed to the internet.

Use your common sense, but be prepared to backup your decisions with evidence. When the executioner comes, you need to be able to honestly argue that you did the right thing, given the circumstances. If you can't do this honestly, you will get found out, your failure will be compounded, and the outcomes all the more severe.

The whole aim of these recommendations is to give you a head start removing potential avenues of attack for your adversaries, providing some mitigation to recover from an attack, and giving you plenty of places to go do further research.

You'll need to do the basics for securing your infrastructure. As with most other things, this is an ongoing process.

You will likely need, as a bare minimum, a properly configured firewall. I'm a big fan of pf, but IPTables is probably more widely used. Use what's appropriate for your platform, do some reading, and make sure you've got it dropping as much un-necessary traffic as possible, in and out of your organisation.

For remote access, most services go with SSH. OpenSSH is easily hardened. I'd recommend having a good read of Lucas' SSH Mastery to familiarise yourself with the finer points of the service. If your platform doesn't have SSH, it's likely that you'll have something similar, but you'll have to do your research.

If your company has more than a small handful of employees, sudo is an absolute life saver. Once again, Lucas provides a good book on utilising sudo for access control & auditing in Sudo Mastery.

You must keep any services you run up to date. This is everything, database, web server, remote access, kernel, etc. This will entail some downtime. A little and often goes a long way towards preventing major outages.

Often, people have perfectly good intentions, but fail to keep up with patches. There are three main causes.

The first is wanting to avoid any and all scheduled downtime. If you plan correctly, and notify your users ahead of time, this is no issue. People largely don't mind the service disappearing at a well-known time for an hour a month.

The second is harder to combat. Ignorance of the updates existence, the security implications of not applying the patch, or knowledge of how to apply them. You need to collate a list of your dependencies (web servers, databases, OS patches, etc.) and their security announcement pages. This list then needs to be checked, and any relevant issues assessed. You should also be aware of how you actually update each piece of software. Many operating systems from the unix family make this easy with a package manager, but I don't know how the rest of the computing world fares in that arena.

Typically, Mitre will provide an assessment of the risk posed to organisations by a vulnerability, which is normally a reasonable estimate of the risk posed to your organisation. High risk vulnerabilities may need re-mediation outside your normal downtime cycle, lower risk ones may be able to wait.

The third is that many people fear updates as they can break things. This risk only gets worse with time. If you're not keeping up with the latest security patches, then when things break, you need to work out which of the 17 patches you just applied did it. With just one or two patches, you can file a bug report, or determine if you're mis-using the dependency much more easily.

A hidden set of dependencies are those of your own bespoke software, which are pulled in by some form of build process. Many organisations simply ignore is the dependencies of their bespoke software. For instance, with a large Java application, it's all too easy to get left behind when ORMs and IoCs get updated regularly. You must be regularly checking your dependencies of your bespoke software for updates, and the same arguments regarding OS level patching apply. Get too far behind, and you'll get bitten -- hard.

I'd recommend turning on OS-level exploit mitigation techniques provided by your OS. This is typically things like address-space layout randomisation (ASLR) and W^X, but plenty of others exist. Should you be on holiday when a problem arises, these will buy you some time to either put a phone call in to someone to get the ball rolling, or get to an internet cafe and open a connection with a one-time password (don't trust the internet cafe!). They also tend to frustrate attackers, and may prevent some specific vulnerabilities from being exploitable at all.

This is a huge field, and some systems don't have all of these protections turned on by default, or simply lack the feature at all. Look very closely at your OS, and the dials that you can turn up.

Other systems of policy enforcement, such as SELinux may also help, but I've not had much chance to use them. Read up on them, both pros and cons, and work out if they're of much use to you, and if they're worth your time.

The next class of problems is running obviously bad software. Even if you keep your dependencies up to date, lots of people will fall prey to this. One of the worst offenders is WordPess (and it's plugin ecosystem), but other system have not had a clean run.

Check out the history of a project before utilising it. If you've decided that it's bad, but nothing else works for you, segregate, segregate, segregate. Then monitor it for when it does get compromised. This can be done with a simple chroot, or for beefier solutions, a separate system with an aggressive firewall between it and any user data can help. For monitoring, you'll probably want something like Nagios, but there's plenty of alternatives.

If possible, you should try to segregate and monitor your bespoke software as if it were in the class of services with a poor history, but this may not be possible.

On the subject of monitoring, you should be monitoring lots of performance metrics, such as database load, queries per second, errors/second in logs, etc. These will help tell if you something funny (security related or otherwise) is up, before it becomes a major problem for you.

You may also chose to deploy an intrusion detection system (IDS). Snort is widely recommended, and comes with a whole bunch of basic rules. You'll need to tune this to filter out the noise and leave the signal. This is no small task, prepare yourself for some serious documentation divin' with most IDS/

Once you're at this point, you should be have a relatively decent security posture. But there's two crucial things I've not covered, relating to recovery from an incident.

The first is backups. Make them, store the offline (at least one business has gone under from this), and test them, and your restore processes regularly. If something bad happens, you need these to be out of reach of the threat, whether it's deliberate or otherwise.

Secondly is general incident response. However, the one I'd most like to bring to the fore is a breach communications package. This is a set of templates covering several scenarios which can be used to notify customers, fend off the press, and put on your website to explain the situation. If you're a big company, and you expose customer data, the press will call. If you expose a lot of user data, the press will call. If you are compromised by a highly news-worthy adversary (e.g. ISIL), the press will call.

Do not waste your time trying to talk to journalists, and do not waste time writing a press release under pressure. You'll do a bad job of it, and things will go from bad to worse very quickly; especially if reporters think you're available for comment.

And finally, what's the point of all this, if you're not going to be developing some bad-ass web app to scratch a particular itch.

I strongly recommend that you use some variety of a secure development lifecycle, such as OpenSAMM, BSIMM, or Microsoft's SDL. Obviously, these won't solve your issues, but they should help alleviate them.

One of the most important things on each lifecycle is developer training. Without that, you're leaving a very large, obvious and attractive target for attackers.

Many of the things in a lifecycle will overlap with, and go beyond these recommendations. That's good and fine, but most of them discuss things in very abstract terms, and hopefully this post puts some of the requirements down more concretely.

Hopefully, that should give you a good place to start. The important thing is discipline. The discipline to check for & apply patches, follow a secure development lifecycle, impose some reasonable restrictions on yourself and therefore your attackers.

Developing software is very hard. Developing secure software is maddeningly hard. For this reason, there is no security silver bullet. Anyone trying to sell you a one-stop solution is full of it. It requires careful research and implementation; and it will take time. It is easiest to do this from the start, but by injecting quality control activities into an existing process, you can begin to improve an organisation's security posture, but it will be slow. In many cases, bespoke software will have to be reviewed or simply thrown away, services migrated to better-configured infrastructure, and so on. It takes time, a lot of time.

Tuesday, 10 February 2015

Madness from the C

So, I've decided to take the plunge.

C is so widely used that not being quite intimately acquainted with it is a definite hinderance. I can read C comfortably for the most part, ably wielding the source of a few kernels or utilities to track down bugs and determine exactly how features are used is something that's not beyond my remit.

I might actually try to write some C. Originally I was going to be all hipster and show how to build your web 2.0 service in C using FastCGI, because the 90s are still alive and well. Also, you can do some pretty awesome things relating to jailing strategies (e.g. chroot+systrace, chroot+seccomp or jail+capsicum), and the performance can be good.

Unfortunately, when it comes to writing C, I freeze up. I know there is so much left to the imagination; so much to fear; so much lurking in the shadows, waiting to consume your first born. And I hate giving out advice that could lead to some one waking up to find ETIMEDOUT written in blood on the walls; even if the "advice" is given in jest. (Thanks to Mickens for the wording)

I speak of the dreaded undefined behaviour.

Undefined behaviour is a double edged sword. In tricky situations (such as INT_MAX + 1), it allows the compiler to do as it pleases, for the purposes of simplicity and performance. However, this often leads to "bad" things happening to those who transgress in the areas of undefined behaviour.

I suggest that if you are a practicing C developer, and you don't think this is much of a problem, or you don't know much about it, you read both Regehr's "A Guide to Undefined Behaviour in C and C++" and Lattner's "What Every C Programmer Should Know About Undefined Behaviour" in full.

I was in the camp of "undefined behaviour's bad, but not too much of a problem since it can be easily avoided" camp, since I am more security-oriented than performance-oriented. I much prefer Ada to C.

That was, until I started in on Hatton's "Safer C".

The book is well written, clear, and direct.

Broadly speaking, all was going well, until I got to page 49. Page 49 contains a listing of undefined behaviour, as do pages 50, 51, 52, 53, 54, 55, and about one third of 56. That's over 7 pages of undefined behaviour.

It could be made better, if these were all weird, corner cases, that the compiler clearly could not detect and throw out as "obviously bad," and not even just semantically bad (for example, dereferencing a null pointer); but those that are syntactically bad.

Things like "The same identifier is used more than once as a label in the same function" (Table 2.2, entry 5) and "An unmatched ' or " character is encountered on a logical source line during tokenization" (Table 2.2, entry 4) and my current favourite, "A non-empty source file does not end in a new-line character, ends in a new-line character immediately preceded by a backslash character, or ends in partial preprocessing token or comment" (Table 2.2, entry 1).

Just look at those three. Syntactic errors, which, according to the standard, could bring forth the nasal demons.

Let me put it more bluntly. A conforming compiler may accept syntactically invalid C programs, and then emit (in effect) any code it wants.

Now, clearly, most compilers do not do this; they give define these undefined behaviours as syntax errors. The thing which really scares me is that the errors presented are from the first page of the table, and there's another six pages like that to go.

Further, I think I must come from a really luxurious background. I expect compilers to do everything reasonable to help program writers avoid obvious bugs, rather than simply making the compiler writers life easier.

A compiler is to be written for a finite set of hardware platforms. It needs to be used by countless other (probably less experienced) programmers to produce software which may then go on to be used by an unfathomable number of people. It's no small thing to claim that a large fraction of the world's population have probably interacted, in one way or another, with the OpenSSL code base, or the Linux kernel.

The reliability of these programs is directly correlated to the "helpfulness" of the language they are written in, and as such, C needs to be revisited with a view to "pinning down" many of the undefined behaviours; especially those which commonly lead to serious safety or security vulnerabilities.

Wednesday, 4 February 2015

Last Christmas, I gave you my HeartBleed

With HeartBleed well and truly behind us, and entered into the history books, I want to tackle the idea that HeartBleed would've definitely been prevented with the application of formal methods -- specifically those that culminate in a proof of correctness regarding the system.

Despite sounding really good, this is actually a false statement, and the reasoning isn't actually all that subtle.

To demonstrate, I'm going to use a common example, the Bell and LaPaulda model for mandatory access control.

The model is, roughly, that everything is a resource or a subject. Both resources and subjects have classifications (we'll just limit ourselves to two), for example, "low" and "high". Subjects with low classification can only read low resources. Subjects with high classification may read both high and low resources.

The specification of the write operations is not currently relevant.

So, let's try and specify this in (something like) the Z notation; we need two operations, ReadOk and ReadError. ReadOp is a combination of both of them.

I apologise in advance, this is the bastardisation of Z that I could work into a blog post without inclining images.



(SubjectClassification? = high) || (classificationOfResource(resourceFromId(resourceId?)) = low)
Result! = resourceFromId(resourceId?)

What this can be read as is, given inputs SubjectClassification and ResourceId, and an Result output; and the predicate (SubjectClassification? = high) || (classificationOfResource(resourceFromId(resourceId?)) = low), then the Result output is the resource.

This embodies the "Read down" property of Bell & LaPaulda. If a subject has high classification, then they can read, otherwise, the resource must have a low classification.

The ReadError operation is similarly designed;



(SubjectClassification? = low) && (classificationOfResource(resourceFromId(resourceId?)) = high)
Result! = error

This basically, roughly, very poorly, states that if you're a low classification subject, and you try to read a high classification resource, you'll get an error.

We now know that, for our specification, we're done.

This looks really good! A decent specification that we can really work to! Let's implement it!

public class BLPFileSystem {

  public enum Classification { LOW, HIGH }

  private final Map<ResourceId, Resource> resourceMap;

  public Resource readById(final ResourceId id, Classification subjectClassification) {

    assert id != null;

    assert resourceMap.contains(id);

    Resource r = resourceMap.get(id);

    Classification resClass = r.getClassification();


    if (subjectClassification == HIGH) {

      return r;

    } else if (resClass == LOW) {

      return r;

    } else {

      throw new IllegalAccessException();



Also, imagine the rest of the infrastructure is available and correct...

Well, this is obviously broken. If you've skipped the code, the offending line is "r.setClassification(LOW);"

That's right, this method declassifies everything as it goes along!

Interestingly, this completely meets our specification. Now, if this was an automatically verified (engage hand-waving/voodoo), I could push this to production with no hassle.

This isn't just a contrived example, but a demonstration of a general issue with these sorts of things.

A specification is usually a minimum of what your software must do -- it usually does not declare a maximum. In OpenSSL's case, the software did the minimum that it was supposed to, it also went above and beyond it's specification to work in new and interesting ways; which turned out to be really bad.

Even with our file system, we can add predicates to ensure that the state of the read file is not changed by reading it; but then the state of other files could be modified. A bad service could declassify every other file when reading any file.

It's not easy to just put "must not" into the spec. Many cryptography systems must run in adversarial situations, for example, sharing virtual machines sharing hardware with adversaries. These systems must protect their key material despite a threat model in which the adversary can measure the time, power and cache effect of the system.

In our example, the system can still violate the "spirit" of the specification by leaking information based on timing-dependant operations.

In part, this exists because the specification is a "higher level" of abstraction, and the abstraction is not perfect.

Now, that is not to say that we should abandon formal methods. Far from it, these, and related formalisms are the kinds of things which save lives, day in, day out. The overall quality of most projects would be vastly improved if some degree of formal methods had been applied from the start. Doubly so if it's something as unequivocally bad as the OpenSSL source. It's just that, in the face of security, our tools need some refinement.

Monday, 26 January 2015

Software Testing with Rigour

Previously, I've heard a lot about test-driven design (TDD) and why TDD is dead. Gauntlets have been thrown down, holy wars waged, and internet blood spilled.

This has resulted in widespread disaffection with TDD, and in part, some substantial disillusion with testing as a whole. I know that I suffer this; some days, I just want to cast the spear and shield of TestNG and Cobertura aside, and take up the mighty bastard-sword of SPARKAda.

I can sympathise with the feeling that testing is ineffective, that testing is a wast of time, that testing just doesn't work. When I get another bug report that the bit of code that I worked so hard to test is "just broken," I want to find the user and shake them until they conform to the code.

Clearly, assaulting end-users is not the way forwards. Unfortunately, tool support for the formal verification of Java code is also lacking in the extreme, so that route is right out too.

My own testing had been... undisciplined. Every class had a unit tests, and I even made quite a lot of integration tests. But it seemed lots of bugs were getting through.
It seems to me, that there are two things that really need to be said:
  1. Testing is extremely important.
  2. Creating tests up front was, at one point, basically common sense. Meyers covers this in the 1979 book, "The Art of Software Testing"
Following in Meyers' footsteps, I'd also like to make a big claim: Most people who do TDD aren't doing testing right.

TDD is often used as a substitute for program requirements, or program specification. Unfortunately, since the tests are almost always code, when a test fails, how does one really decide in a consistent way if it's the tests or the program that's broken? What if a new feature is to be worked into the code base that, on the surface looks fine, but the test suite shows it to be mutually exclusive with another feature?

Agile purists take note; a user story can work as a piece of a system's specification or requirements, depending on the level of detail in the story. If you're practicing "agile", but you don't have some way of specifying features, you actually practicing the "ad-hoc" software development methodology, and quality will likely fall.

Testing is "done right" when it is done with the intent of showing that the system is defective.

Designing Test Cases

A good test case is one which stands a high chance of exposing a defect in the system.

Unlike Meyers,  I side with Regehr on this one: Randomised testing of a system is a net good, if you have:
  1. A medium or high strength oracle.
  2. The time to tweak your test case generator to your system.
  3. A relatively well-specified system.
If you want to add even more strength to this method, combinatorial test case generation, followed by randomised test case generation looks to be a very powerful methodology.

However, I also feel strongly that time and effort needs to be put into manually designing test cases. Specifically, designing test cases with a high degree of discipline, and the honest intent to break your code.

Meyers recommends using boundary value analysis to partition both the input domain and output range of the system, and designing test cases which exercise those boundaries, as well as representative values from each range.

Oddly, he also discusses designing test cases which will raise most coverage metrics to close to 100%, which struck me as odd; although he tempered it by using boundary value analysis to slot into the high-coverage tests. I'm not sure I can recommend that technique, as it destroys the coverage metrics as a valid proxy of testing effectiveness, and Meyers acknowledges this earlier in the book.

For a really good run down of how to apply boundary value analysis (and lots of other really interesting techniques!), I really can't do any better than referring you to Meyers' book.

Testing Oracles

Testing oracles are things which, given some system input, and the system's output, decides if that output is "wrong".

These can be hand-written expectations, or simply waiting for exceptions to appear.

The former is a form of strong oracle, the latter is a very weak oracle. If your system has a high quantity of non-trivial assertions, you've got yourself a medium-strength oracle, and can rely on that to some degree.

What To Test

Meyers and Regehr are in agreement: Testing needs to be done at many levels, though it's not as clear in Meyers' book.

Unit testing is a must on individual classes, but this is not enough. Components need to be tested with their collaborators to ensure that there are no mis-communications or mis-understandings of a unit's contract.

I guess the best way to put this across is to simply state this: unit testing and integration testing are looking for different classes of errors. It is not valid to have one without the other, and claim that you may have found a reasonable amount of errors, as there are errors which you are simply not looking for.

I, personally, am a big fan of unit testing, then bottom-up integration testing. That is, test all the modules individually, with all collaborators mocked out, then start plugging units together starting at the lowest level, culminating in the completed system.

Other methods may be more effective for you; see Meyers' book for more methods.

This method allows you to look for logic errors in individual units, and when an integration test fails, you have a good idea of what the error is, and where it lies.

How to Measure Testing Effectiveness

A test is effective if it has a high probability of finding errors. Measuring this is obviously very hard. One thing that you may need to do is work out an estimate of how buggy your code is to begin with. Meyers has a run down of some useful techniques for this.

Coverage is a reasonable proxy -- if and only if you have not produced test cases designed to maximise a coverage metric.

It would also seem that most coverage tools only measure a couple of very weak coverage metrics: statement coverage and branch coverage. I would like to see common coverage tools start offering condition coverage, multi-condition coverage, and so on.

When to Stop Testing

When the rate at which you're finding defects becomes sufficiently low.

This is actually very hard, especially in an agile or TDD house, where tests are being run constantly,  defects are patched relatively quickly with little monitoring, and all parts of development are expected to be a testing phase.

If your methodology has a testing phase, and you find that at the end of your (for example) 4 week testing window is finding more and more defects every week, don't stop. Only stop when the defect-detection rate is dropping down to an acceptable level.

If your methodology doesn't have a testing phase, this is a much harder question. You have to rely on other proxy methods of whether your testing is effective, and if you've discovered most of the defects your end users are likely to see. Good luck.

I, unfortunately, am in the latter category. I just test as effectively as I can, as I go along and hope that my personal biases aren't sinking me too badly.


Do testing with the intent of breaking your code, otherwise you're not testing -- you're just stroking your ego.

If possible, get a copy of Meyers' book and have a read. The edition I have access to is quite small, coming in at ~160 pages. I think that if you're serious about having a highly-effective test suite, you need to read this book.

Regehr's Udacity course, "Software Testing" is also worth a plug, as he turns out to be both very capable of effective systems testing teaching; a rare trait. Take advantage for your benefit. The course also provides a nice, more modern view on many of Meyers' techniques. His blog is also pretty darn good.

Saturday, 13 December 2014

Securing Strings

This is not about String as in Java, or std::string in C++. This is about the program strings, part of the GNU Development tools.

The strings program takes a file and prints out the printable strings.

Recently, the author Michal Zalewski (aka, icamtuf) used his American Fuzzy Lop (afl) tool to fuzz a variety of GNU tools, one of which was the strings program. The outcome of this was that it's a very bad idea to run strings on untrusted input.

I should make it clear, I don't think that they author of strings should've undertaken these when it was written. Most software starts off as a personal prototype or tool and grows. It's silly to start demanding the most rigorous secure software development methodology from one author and their pet project.

Once the pet project escapes and starts being relied on by other people, the dynamic obviously changes, more questions about who is responsible for the correctness of the program start being asked -- even if anyone is responsible for it, since most software comes with a disclaimer of warranty.

I will not cover program verification tools. They're often just overkill for most problems, and I think this may well be one of them.

Anyways, onto my main point. How do we go about solving this problem once and for all?

Audit ALL the things!

This is OpenBSD's primary approach. All commits must be reviewed, and almost all of the code base was reviewed somewhere around version 2 or 3, when Theo De Raadt's own OpenBSD machine was compromised (Shock, horror!).

This is a timely process, and there are no guarantees. If one person misses a subtle bug, what's the chance that the next person misses the bug? I'd wager that the chance is "high," but I'm mostly speculating.

I'm actually very pro-code review/audit. I like that TrueCrypt (now VeraCrypt) is getting audited, and at my work, I'm pushing hard for code review before any code goes live. I'm also aware that it is by no means a perfect tool, and it does slow down the process to go from design to deployment.

Use a Memory Safe Language

We could use (for example) Java, or even Ada (with the right GNATs flags) to re-write the strings tool and completely avoid memory safety vulnerabilities.

I like this idea for new projects; I would never suggest starting a new project in C, Objective-C or C++ because they all inherit C's badness with memory.

But... Java requires a runtime (The JVM) and it's startup time is non-trivial. Most people don't know Ada, and Haskell has even fewer engineers to its name.

Further, for Java especially, you're relying on the security of the underlying runtime, which hasn't had a great track-record.

I'd argue that Ada is the best choice out of the lot, but I'm biased. I really like Ada.

Obviously, re-writing extant programs in an entirely new language is not the smartest idea, unless there's really good reason. It's time consuming, and you're likely to re-introduce bugs that you coded out in the original.

Apply Good Security Principles

What I actually mean by this is that you should ensure that you apply the principle of least privilege. That means restricting exactly what the program can do, so that if compromised, the program can't do much more harm, even if the attacker manages to gain complete control over the program.

On Linux, this can be achieved to a very fine-grained level with the seccomp system call, and on FreeBSD, there is the Capsicum subsystem.

What these allow you to do is to enter a "secure" mode, where by all but a few, specified system calls are completely disabled. An application attempting to run the banned system calls is killed by the kernel. Often, you're allowed to enter the secure mode with a file descriptor.

For strings, you'd read the command line, open your target file read only (check it exists, is readable, etc.) and then enter secure mode whereby you can only read the single opened file. Should an RCE be found, the adversary would be able to read as much of the open file that they like, but they would be contained within that single process. They could not open a new shell (that would involve a banned system call), the could not open file descriptors to sensitive files (/etc/passwd, browser caches, etc.) since that would involve creating a new file descriptor, which is banned. It couldn't open a network socket and send any data to a C&C host, as it would be banned from creating sockets.

The only way out would be to find a privilege escalation exploit in the kernel using the system calls that aren't immediately filtered.

I actually like this idea best, since it can easily be combined with code review. You aim to reduce the number of security relevant bugs using code review (and testing, but you're unlikely to cover a large amount of the state space). Any that slip through the net become safe crashes, not full compromises.

First, you implement the minimal "jail" (not like chroot jails or FreeBSD jails, but seccomp or Capsicum per-process jails), and have the implementation use it. You then get your colleagues to review the jail implementation in your program.

Saturday, 6 December 2014

A Simple Mail Merge Application

My other half has just finished writing their first full-length novel. As such, they'd like to send it off to agents.

My first thought was OpenOffice Base. Have her enter the agent details into a table, and use OpenOffice Writer's mail merge facility. This however, did not work, since Writer's mail merge facility lacked the all-important attachments functionality.

If OpenOffice had this functionality, we'd have been up and running in about 15 minutes. I'm surprised it doesn't, it's the ultimate way to automate the job search, surely an unemployed programmer would've provided the functionality at some point...

But, leaving that by the way side, I wasn't about to give up on OpenOffice just yet. I know that OpenOffice Base's files are just cunningly zipped HSQL databases, with some metadata surrounding it.

So, I thought I'd unzip the OpenOffice Base file and have a small Java application read the HSQL database, put the results through the Velocity template engine and send off the email.

This would've involved sneaker-netting the ODB file back and forth between my machine and my partner's, but that seemed ok. They'd enter many agents in during the day, and I'd "send" them all over night. No biggy.

This was also a bust. Once my Java application with it's all-mighty HSQL JDBC jar had touched the database, it seemed to taint it. I think it bumped a version field in the database. This meant that OpenOffice Base refused to open it after even one round with my Java program.

So, plan C. SQLite is an amazing embedded database. Far faster and nicer than HSQL -- it even comes with a neat little command line interface.

I set up some test data in an SQLite database and pointed my Java program at it. Success!

So then I told OpenOffice Base to look at the file, so my partner could enter some data. Failure! OpenOffice Base had an issue with (I think) the scrolling modes available. So that was right out, wouldn't even show the data in the OpenOffice interface. Sad times.

Plan D. Remember, you've always got to have at least 3 fall-back plans when developing software, otherwise nothing will ever work.

PostgreSQL to the rescue! I setup Postgres on my machine and opened a port for it. On my partner's machine, I tested that they could connect their OpenOffice Base to my Postgres. I then tested dropping some test data in the Postgres database and trying my Java program, configured to use Postgres... Success!!

Now all I need to do is figure out how to send MIME multi-part HTML emails correctly ... ugh.

Anyway, this has been a day or so worth of work on my part.  I suspect I'll have another half-day to get HTML emails working correctly, and then I'll be sorted. Hopefully it'll enable my partner to effectively reach a whole host of agents without writing out the same damn cover letter, attaching various PDFs, and DOC files, etc. over and over.

Once this is all wrapped up, I may open source it. I'll need to tidy the code, add tests and documentation, but it may be of use to someone.

The moral of the story is that HSQL is a difficult database to work with, SQLite is always awesome but somethings don't support it, and PostgreSQL is the best RDBMS since sliced bread.

Sunday, 28 September 2014

How I fixed Shellshock on my OpenBSD Box

Well, I am on a "really old" OpenBSD, and I couldn't be bothered updating it right now. It was really arduous:

[Sun 14/09/28 10:52 BST][p0][x86_64/openbsd5.2/5.2][4.3.17]
zsh 1044 % sudo pkg_delete bash
bash-4.2.36: ok
Read shared items: ok

In reality, this is only possible, because, as a sane operating system, there's no dependencies on anything other than a POSIX-compliant sh, of which there are several available.

To me, just another reason to avoid specific shells and just target POSIX. When the shit hits the fan, you'll have somewhere to hide.

When I tried to do the same on my work (FreeBSD) box, I came up against several issues. The main one being that lots of packages specify bash as a dependency.

At some point, I'll write a blog post about the functions of that server, and how I've hardened it.