When it comes to threat prevention and mitigation, there is no such thing as a one-size-fits-all solution. The legacy anti-malware techniques gained a lot of popularity over the years, but they come with their share of glitches. Most anti-malware and anti-ransomware solutions rely on signatures and common threat indicators for threat detection and are not equipped to identify hidden or zero-day stealth attacks.

Sandboxing is a technique that caters to this growing need of unmasking the hidden and obscure threats in code, file attachments, weblinks, and the like. In a nutshell, where the legacy anti-malware and anti-virus solutions fail, the sandboxing takes over.

What is Sandboxing and a Cloud Sandbox?

 Just like a sandbox mimics the beach, the sandboxing technique impersonates the end-user operating environments in an isolated test environment. By cutting access to the rest of the network, a “sandbox” or an isolated test area is set up which is then ingested with malicious code and malware to observe their behavior patterns and capabilities without giving them a chance to spread. The observed patterns are classified as “safe” or “unsafe” after the mock test. This is where the beauty of sandboxing comes into play because legacy security methodologies are mostly reactive and only look for pre-identified patterns in known instances of malware. However, sandboxing adds another dimension of security by observing both old and new patterns alike, thus effectively protecting a network against zero-day and hidden attacks. As an example, https://urlscan.io/ is a public sandbox that allows you to detonate a potentially malicious URL after which it passes a verdict on whether it is benign or malicious. Anyone can access these types of public sandboxes to scan for malicious URLs and get instantaneous feedback on their status.

A cloud sandbox is essentially the same thing – it is where a sandbox software is utilized in a virtual environment. This ensures complete separation of URLs, downloads, or code from the network devices during and at the time of testing.

Now let us peek into the zero-day threats in the next section.

What are the Zero-Day Threats?

 New malicious threats without a historical record that can sneak in through the legacy content filters are known as zero-day threats. The legacy inbound content filters do a good job at scanning emails, URLs, and files for recognized threats but so many new threats pop up every single day that it is beyond the scope of these traditional filters to keep track of.  Zero-day threats are recently discovered vulnerabilities in a system that hackers can potentially exploit to attack a system. These exploits are called “zero-day” before they are discovered and on the day of their discovery by the vendor – where “zero” refers to the number of days since the vendor discovered this exploit. Once the vendor starts working to rectify the threats, they are no more considered to be zero-day threats but are then listed as “known” threats.

If you are interested in learning more about known threats, then check out the comprehensive Common Vulnerabilities and Exposures database that lists each known security vulnerability in the world of cybersecurity.

Now let us transition back to sandboxing in the next section and discuss a few potential issues that can arise with it.

Issues with Sandboxing

Sandboxing is a robust method for threat mitigation but it comes with a few downsides including extreme resource utilization and time consumption. Setting up a mock sandbox environment requires ample time, effort, and resources, and even then, the adept cybercriminals can find ways to skirt around it and go undetected. As an example, the threat actors can program a threat to remain dormant until a future time just to pass the sandbox test. They can also program the malware to detect whether it is running in a sandbox or on a virtual test environment to remain inactive until it comes across a real endpoint device. Another major problem is that sometimes a sandbox is introduced with each file entering the network, which can degrade network performance and increase costs.

The bottom line is that the stealthy zero-day malware is smart enough to wait for the right environment to inject their malicious code into, thus staying undetected and duping the sandbox.  In the next section, let us discuss some effective ways of implementing sandboxing.

Strategies to Implement Effective Sandboxing

The zero-day threats are growing at a rapid pace and effective sandbox strategies are needed to prevent these sneaky attacks right in their tracks. Here are some effective strategies to consider:

Limit the Number of Files Going to the Sandbox

Sifting through the files before dumping all of them into a sandbox is a good approach. This not only prevents network congestion but also ensures your incident response team is not overwhelmed with the inspection of thousands of potentially malicious files. This strategy also discourages wasteful spending and provides effective security protection by only focusing on the real problem areas.

Prioritize Operational Efficiency and Workflow Integration

When setting up a sandbox, it is important to consider a sandbox that integrates a high detection rate with minimal to no false positives. The forensics teams need access to the details regarding suspicious malware, but too much underlying information can overwhelm and dull their productivity levels. On the same token, it is important to ensure that the sandbox of choice also easily integrates with your current and existing tools and workflow.

Use New or Unknown Malware Samples

The main premise behind sandbox testing is that it should closely resemble a live production environment. This requires the use of malware samples that are foreign to your network infrastructure and that can evade your security parameters as they would in a real-life intrusion. However, it can be quite a bit of a challenge to obtain new malware samples, and to overcome that, some security teams develop their samples, while others use helpful resources like virustotal.com.

Check for False Positives

 Using the sandboxing to your advantage is a balancing act – on one end you want your sandbox to correctly identify each malicious file, while on the other hand, you do not want it to incorrectly classify innocent files as malicious. Remembering that not all sandboxes are created equal and implementing a sandbox that checks for false positives consistently is imperative as false positives can cause unnecessary backlogs. Most vendors pay a lot of attention to their sandbox’s detection rates while ignoring the false positives it might generate. Therefore, doing extensive research before investing in a sandbox or a cloud-based sandbox software is the key.

Conclusion

 Sandboxing and zero-day threats go hand in hand. As far as zero-day threats keep emerging, the importance of sandboxing will keep gaining momentum.

Exium’s loud-based sandboxing solution, offered as a service, runs in a dedicated virtual environment providing effective protection against zero-day threats without degrading your network performance or being easily evaded by clever hackers. Moreover, their xScale Security Analytics Platform applies machine learning algorithms, statistical analysis, and Artificial Intelligence (AI) techniques to classify the samples as “safe” or “unsafe” and then moves them further upstream for closer determination.