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Old Malware, New Tricks

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There’s been an explosion in new malware over the past two years. But how new is this malware, really? How serious is the threat, and how should it be countered?  DOROS HADJIZENONOS of Check Point South Africa looks at the issues.|There’s been an explosion in new malware over the past two years. But how new is this malware, really? How serious is the threat, and how should it be countered?  DOROS HADJIZENONOS of Check Point South Africa looks at the issues.

Taking the path of least resistance is natural – it’s why rivers flow around mountains, and electricity finds the easiest route to earth.  It also explains why there has been such an explosion in new malware in the past couple of years.  While there remains a select handful of coders who will painstakingly develop sophisticated, advanced and complex new threats the vast majority of would-be hackers are taking a much easier route to achieve their goals.

They’ve seen the rewards that are possible from a malware attack, and they’re also aware of the easily-available tools that automate the assembly of new malware, or enable small modifications to existing malware types, rendering them undetectable by conventional antivirus products.  The result is that malicious code is now being mass-produced and unleashed on an industrial scale, by people with little or no coding skills.

In fact, Check Point’s latest annual Security Report shows that more unknown malware has been found in the past two years than in the previous 10 years combined.  While new malware introductions were relatively static in 2010 and 2011, at 18 million per year, this nearly doubled to 34 million in 2012, rose to 83 million in 2013, and reached 142 million in 2014.  What’s worse is the speed at which this is occurring.  On average, organisations were downloading 106 unknown malware types every hour – that’s 48 times more than in 2013.

In a majority of cases, these were existing, known types of malicious files that had simply been modified with minor alterations to a couple of lines of their code – literally, old malware with a new trick, that enabled it to bypass even the most up-to-date antivirus detection.

Building a better trap

To avoid being fooled by these new tricks, an additional method of detection known as threat emulation, or sandboxing, is recommended.  Early versions of this technology worked by intercepting suspicious files as they arrived at the organisation’s gateway, and inspected their contents in a virtualised, quarantined area (the sandbox) for any unusual behaviour, in real time.  If the file’s behavior was found to be malicious, for example attempting to make abnormal registry changes or network connections, it would be quarantined, preventing the infection from reaching the network.

While this approach considerably boosts malware detection rates, criminals have already recognised that the technology is deployed on a percentage of networks, and have responded by implementing further evasion techniques.  As such, a next-generation approach is being introduced:  CPU-level sandboxing.  This enables a deeper, more insightful look at a suspicious file’s activity.

It takes advantage of the fact that there are only a handful of exploitation methods that can be used to download malware and execute it on a host PC.  As it operates at the chip level, below the application or operating system layers, CPU-level sandboxing detects the use of malware exploitation methods by examining activity on the CPU, and the execution flow at the assembly code level while the exploit occurs.  As a result, it strips away any disguises applied to the malware, and pre-empts the possibility of hackers evading detection.

While the speed and accuracy of detection make CPU-level sandboxing a powerful method for detecting unknown attacks, especially existing malware that has been altered using obfuscation tools, it also enables detection of the far more sophisticated (and much rarer) zero-day exploits.  Zero-day malware is effectively hand-built to exploit software vulnerabilities that vendors aren’t even aware of yet.  The ability to block both common and rare, targeted attacks adds a strong, extra defensive layer to organisations’ networks.

Taking the sting from malware

Taking this approach a step further, another emerging threat prevention technique can combine with OS- and CPU-level sandboxing, to virtually eliminate the risk of threats.  This technique is called threat extraction.

It involves a direct approach to threat removal:  as the majority of malware is distributed in infected documents (our Security Report shows that 55% of all infected files were PDFs or Office files), then all documents arriving at an organisation by email should be intercepted, and content that is identified as malware, such as macros, embedded objects and files, and external links, removed.  The threat-free document can then be reconstructed with known safe elements, and forwarded to the intended user, either in the original format or as a locked-down PDF, according to the organisation’s policies.

With the pace of malware attacks showing no signs of slowing down and the evasion techniques and tricks used by malware authors always evolving, the technology deployed to keep businesses secure also needs to evolve, to keep them ahead of new threats.  What was cutting edge in 2014 will simply be the standard for 2015.

* Doros Hadjizenonos, Country Manager, Check Point South Africa

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Smart home arrives in SA

The smart home is no longer a distant vision confined to advanced economies, writes ARTHUR GOLDSTUCK.

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The smart home is a wonderful vision for controlling every aspect of one’s living environment via remote control, apps and sensors. But, because it is both complex and expensive, there has been little appetite for it in South Africa.

The two main routes for smart home installation are both fraught with peril – financial and technical.

The first is to call on a specialist installation company. Surprisingly, there are many in South Africa. Google “smart home” +”South Africa”, and thousands of results appear. The problem is that, because the industry is so new, few have built up solid track records and reputations. Costs vary wildly, few standards exist, and the cost of after-sales service will turn out to be more important than the upfront price.

The second route is to assemble the components of a smart home, and attempt self-installation. For the non-technical, this is often a non-starter. Not only does one need a fairly good knowledge of Wi-Fi configuration, but also a broad understanding of the Internet of Things (IoT) – the ability for devices to sense their environment, connect to each other, and share information.

The good news, though, is that it is getting easier and more cost effective all the time.

My first efforts in this direction started a few years ago with finding smart plugs on Amazon.com. These are power adaptors that turn regular sockets into “smart sockets” by adding Wi-Fi and an on-off switch, among other. A smart lightbulb was sourced from Gearbest in China. At the time, these were the cheapest and most basic elements for a starter smart home environment.

Via a smartphone app, the light could be switched on from the other side of the world. It sounds trivial and silly, but on such basic functions the future is slowly built.

Fast forward a year or two, and these components are available from hundreds of outlets, they have plummeted in cost, and the range of options is bewildering. That, of course, makes the quest even more bewildering. Who can be trusted for quality, fulfilment and after-sales support? Which products will be obsolete in the next year or two as technology advances even more rapidly?

These are some of the challenges that a leading South African technology distributor, Syntech, decided to address in adding smart home products to its portfolio. It selected LifeSmart, a global brand with proven expertise in both IoT and smart home products.

Equally significantly, LifeSmart combines IoT with artificial intelligence and machine learning, meaning that the devices “learn” the best ways of connecting, sharing and integrating new elements. Because they all fall under the same brand, they are designed to integrate with the LifeSmart app, which is available for Android and iOS phones, as well as Android TV.

Click here to read about how LifeSmart makes installing smart home devices easier.

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Matrics must prepare for AI

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students writing a test

By Vian Chinner, CEO and founder of Xineoh.

Many in the matric class of 2018 are currently weighing up their options for the future. With the country’s high unemployment rate casting a shadow on their opportunities, these future jobseekers have been encouraged to look into which skills are required by the market, tailoring their occupational training to align with demand and thereby improving their chances of finding a job, writes Vian Chinner – a South African innovator, data scientist and CEO of the machine learning company specialising in consumer behaviour prediction, Xineoh.

With rapid innovation and development in the field of artificial intelligence (AI), all careers – including high-demand professions like engineers, teachers and electricians – will look significantly different in the years to come.

Notably, the third wave of internet connectivity, whereby our physical world begins to merge with that of the internet, is upon us. This is evident in how widespread AI is being implemented across industries as well as in our homes with the use of automation solutions and bots like Siri, Google Assistant, Alexa and Microsoft’s Cortana. So much data is collected from the physical world every day and AI makes sense of it all.

Not only do new industries related to technology like AI open new career paths, such as those specialising in data science, but it will also modify those which already exist. 

So, what should matriculants be considering when deciding what route to take?

For highly academic individuals, who are exceptionally strong in mathematics, data science is definitely the way to go. There is, and will continue to be, massive demand internationally as well as locally, with Element-AI noting that there are only between 0 and 100 data scientists in South Africa, with the true number being closer to 0.

In terms of getting a foot in the door to become a successful data scientist, practical experience, working with an AI-focused business, is essential. Students should consider getting an internship while they are studying or going straight into an internship, learning on the job and taking specialist online courses from institutions like Stanford University and MIT as they go.

This career path is, however, limited to the highly academic and mathematically gifted, but the technology is inevitably going to overlap with all other professions and so, those who are looking to begin their careers should take note of which skills will be in demand in future, versus which will be made redundant by AI.

In the next few years, technicians who are able to install and maintain new technology will be highly sought after. On the other hand, many entry level jobs will likely be taken care of by AI – from the slicing and dicing currently done by assistant chefs, to the laying of bricks by labourers in the building sector.

As a rule, students should be looking at the skills required for the job one step up from an entry level position and working towards developing these. Those training to be journalists, for instance, should work towards the skill level of an editor and a bookkeeping trainee, the role of financial consultant.

This also means that new workforce entrants should be prepared to walk into a more demanding role, with more responsibility, than perhaps previously anticipated and that the country’s education and training system should adapt to the shift in required skills.

The matric classes of 2018 have completed their schooling in the information age and we should be equipping them, and future generations, for the future market – AI is central to this.

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