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… and how do we know it works?
What’s the difference between artificial intelligence and machine learning? Put simply, artificial intelligence is the area of study dedicated to making machines solve problems that humans find easy, but digital computers find hard. Examples include driving cars, playing chess or recognising sarcasm.
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IoT security is a mess, but who’s to blame? The tech industry must improve security for the internet of things.
The internet of things is quickly becoming every cybercriminal’s wet dream, especially given the release of the Mirai botnet source code. The cause is shockingly insecure devices, but can shaming manufacturers avert the coming chaos?
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Why does software seem so insecure? Massive software companies seem incapable of fixing their products for any length of time. Is it their fault, or are they fighting a battle they can’t win?
At its core, Windows is the result of several decades of constant development. Despite this, Microsoft is still obliged to observe Patch Tuesday each month, when users receive the latest fixes to installed products. A large number of these updates fix security vulnerabilities.
This month, for example, Patch Tuesday includes 16 security update bundles covering in excess of 40 new security holes found in products as diverse as IIS, Microsoft’s web server, and the supposedly secure Edge browser. How can it be that this monthly ritual is still required? After all, it’s not like Microsoft is a small company caught out by sudden success, while trying to manage a huge ball of undocumented code. On the contrary, it is literally one of the biggest, best funded tech companies in the history of the planet.
Let’s take another case. Adobe’s Flash and Reader products are also mature, stable software. Yet black hat hackers love them as the gifts that keep on giving. This week brought news of yet another critical Flash vulnerability, which is already being exploited in the wild.
The complexity of some software, despite its maturity, makes it vulnerable. It needs to be all things to all (wo)men at all times. In the case of Adobe Reader, every PDF document it loads must display perfectly, regardless of its complexity or the limitations of the software used to create it. Anything not explicitly forbidden is, therefore, permissible. Reader will always try to render the file you give it.
Such complexity leads neatly to a fundamental question: If companies such as Adobe and Microsoft can’t find all the exploitable bugs in their code, how come private researchers and black hats can?
The answer lies in a technique called fuzz testing, or fuzzing.
In his presentation to CodenomiCON 2010 , Charlie Miller showed that with a little thought, a few lines of Python code and some time, it’s possible to use fuzzing, in the form of completely random mutations to a file, to find a number of hitherto unreported and potentially exploitable crashes in Adobe Reader.
He took 80,000 PDFs from the internet and reduced that total to just over 1,500 based on their uniqueness from each other. From these files, he generated 3 million variations containing random mutations.
When loaded into Reader, these corrupted files caused crashes in over 2,500 cases. Miller showed that several crashes revealed exploitable situations, some of which were subsequently found, reported and patched by Adobe, but others were new.
Given that there are a total of 2 ^ NUMBER_OF_BITS theoretical mutations that can be made to a PDF, and the ease with which each mutation can be automatically evaluated, PDF readers alone should remain a goldmine for new exploits for some time. Meanwhile, there are many other programs and file types that can be also attacked with various fuzzing methods.
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| Bugtraq has been highlighting software vulnerabilities for years |
Take a look at the Bugtraq mailing list archive and you’ll see what I mean. Every day brings a new crop of reports and proofs of concept for all kinds of software. In fact, another six were added while I wrote this blog post. Buried amongst the plethora of obscure libraries and applications are often complete howlers in major products. How are these bugs being found? In the case of closed source software, fuzzing techniques can be the primary tools.
Fuzzing comes in many forms, with some methods and frameworks being more intelligent and guided than others, but the aim is always to automate the discovery of exploitable bugs by finding situations for which complex software either hasn’t been tested or cannot be tested.
You may be wondering why, with their wealth and resources, major software manufacturers don’t fuzz their products to death, as well as performing more traditional testing. The short answer is that they do, but due to the sheer number of possibilities and the time required, all they can do is fuzz as much as possible before the release deadline. The overwhelming majority of possible tests may still remain to be run by other, potentially malicious individuals and groups.
Security holes in software are not going away any time soon, so ensure that the security software you run is capable of protecting you. How? Checking out good anti-malware reviews that include exploit attacks such as ours would be a good start.
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