There’s one thing that every business, irrespective of size, sector, or geography, would have noticed in the last couple of years: Cyber threats are evolving and becoming more potent than anyone could have imagined. A large part of that has to do with an increase in more sophisticated strains of malicious software, which we also know as malware.
Malware can infiltrate your systems in many different ways, from social engineering attack techniques like phishing to corrupted hardware and misconfigured software. Today, adversaries are increasingly using AI-driven automation capabilities to launch elaborate malware campaigns. They also use similar technologies to exploit vulnerabilities across enterprise IT environments, whether that’s on-premises, in the cloud, or a mix of both.
Due to the speed and scale of new malware attacks and exploits, businesses need to move beyond legacy malware analysis tools and embrace a completely new and next-gen approach. In this article, we’re going to tell you all about automated malware analysis and why you should prioritize it.
What is Automated Malware Analysis?
Before we get into automated malware analysis, we need to understand the fundamentals of malware analysis. The objective of malware analysis is to identify and understand how a particular strain of malware works, why it was deployed, and what impact it has on your IT environments and organization. Remember that malware is an umbrella term for a wide variety of malicious files, applications, and types, including ransomware, viruses, and spyware.
Malware analysis typically involves pinpointing indicators of compromise or IoCs, assigning the discovered strains into malware families, and identifying the threat actors who designed and deployed them. Effective malware analysis ensures that security operations center (SOC) teams and incident response teams can quickly and effectively kickstart remediation processes.
To understand why you need AI-driven automation capabilities across your malware analysis tools and workflows, you need to remember how AI-powered technologies have grown in the last few years. Unfortunately, AI technologies don’t just help the good guys; they also help threat actors. According to a 2024 Gartner survey, AI-powered cyberattacks were a top concern for senior managers and risk executives.
For threat actors, AI and automation lower the bar of entry, make large-scale attacks possible with minimal resources, and help with the creation of advanced forms of malware like polymorphic malware. Polymorphic malware is a type of malicious software that can change over time to evade traditional detection systems like antivirus applications.
To defend against this new wave of potent, fast, and sophisticated malware, security teams simply can’t rely on manual processes for threat detection and reverse engineering. They need automation.
The Primary Techniques Used in Automated Malware Analysis
Different techniques are used in automated malware analysis, depending on the context. In this section, we’ll look at some commonly used malware analysis techniques. These malware analysis approaches aren’t mutually exclusive. You can use them all or pick between them. Which option to use will depend on the nature of the malware and your objectives.
Static Analysis
Static analysis enables the detection of malware by analyzing code and file structures without executing the malicious software. This is a useful method to scan malicious files and libraries. Static analysis will help reveal hashes, file names, IP addresses, and other embedded strings: consider these the fingerprint of a particular strain of malware.
While static analysis is a useful technique, it’s not without limitations. Since it doesn’t execute the malicious code, advanced strains like polymorphic malware can slip past undetected.
Dynamic Analysis
This malware analysis technique involves creating isolated and controlled environments called sandboxes and conducting malware tests within them. The reason for conducting these analyses in sandboxes is so that the executed malware files don’t affect the rest of the enterprise’s IT environments. By using dynamic analysis techniques, security teams will also get a firsthand look at the real-world and real-time effects of malware.
Another benefit of dynamic analysis is that security teams don’t need to spend a lot of time and resources on reverse engineering malware. They can simply execute it in a sandbox and study how it works.
Overall, dynamic analysis makes life a lot easier for incident response teams, especially when dealing with advanced malware like polymorphic malware. However, it’s important to remember that dynamic analysis isn’t foolproof. Threat actors are constantly honing their skills and finding ways to evade dynamic malware analysis.
Hybrid Analysis
Since neither static analysis nor dynamic analysis offers 100% protection against malware attacks, this third option involves combining the two. By using hybrid analysis, threat hunting teams can more easily hunt down known threats and also unveil a plethora of hidden and unknown threats.
Most contemporary approaches to malware detection and response involve a lot of hybrid analyses, quite simply because they offer the best of both worlds.
Before we move forward, remember that static, dynamic, and hybrid analyses aren’t inherently automated. In fact, these techniques were used even before AI-driven automation was prevalent. The key to battling current-day malware attacks is to power these methodologies with high degrees of automation.
Automated Malware Analysis Use Cases
Here, let’s take a look at some of the most high-potential use cases of automated malware analysis in your cybersecurity program:
Proactive Threat Hunting
Automated malware analysis allows threat hunters to extract IoCs from a diverse range of sources, including endpoint telemetry and historical logs. By doing so, your SOC and security teams can stay one step ahead of threat actors.
Endpoint Detection and Response (EDR) Integration
By integrating automated malware analysis with your EDR tools, you can more efficiently isolate infected devices and systems. Most importantly, you can do so without manual intervention or triage.
Malware Threat Intelligence and Research
Automated malware analysis can significantly enrich research initiatives. With automated malware analysis, your company will learn more about emerging malware threats and how to protect mission-critical resources from them. You should also share this malware research with various threat intelligence communities in your sector or region.
Phishing Security
Most cyberattacks begin with a simple phishing email. Automated malware analysis automatically flags suspicious emails and attachments and sends them to sandboxes for deeper analysis.
Security Information and Event Management (SIEM) Optimization
SIEM tools gather tons and tons of data about threats, vulnerabilities, and misconfigurations in enterprise environments. But most of these threats are either irrelevant or lack meaningful context, meaning you won’t really have an idea of how certain threats will impact you. By creating an automatic data exchange between SIEM tools and malware analysis tools, you’ll have a more thorough understanding of the real-world implications of malware-related cyber threats.
What are the Benefits of Automated Malware Analysis?
By shifting to an automation-driven approach to malware analysis, you can unlock the following benefits:
Higher Volume of Malware Analysis
Since automation either removes or reduces the need for manual intervention, automated malware analysis will allow you to scan thousands of malware samples every day.
More Efficient Triage
Since AI-driven automation can generate and decipher analysis results at speed and scale, security teams can quickly triage cybersecurity incidents based on severity and criticality.
Advanced Threat Detection
Automated malware analysis will help you shine a light on both known and unknown malware strains. Crucially, it will also help you identify the newest and most cutting-edge kinds of malware, which could have potentially bypassed legacy security tools.
Reduced Error Rate
The more automation you introduce, the fewer human errors you’ll have to deal with. When it comes to malware analysis, there’s simply no time or resources to deal with false positives, which makes automation particularly valuable.
Swifter Incident Response
Given the volatile nature of the contemporary cloud landscape, it’s a safe bet that every business will have its fair share of cybersecurity incidents to deal with. While not all incidents are critical, it’s absolutely essential for incident response teams to identify, contain, and remediate critical incidents as quickly as possible.
Best Practices for Implementing Automated Malware Analysis
Here are some recommendations and best practices that can help you efficiently adopt automated malware analysis.
Use Top Automated Malware Analysis Tools
Automation, in theory, is always a good idea, but remember that not all tools are equal. Therefore, your first step is to build a solid malware security stack. Some useful malware analysis tools include:
- Ghidra
- Cuckoo Sandbox
- YARA
- VirusTotal
- Wireshark
Integrate Malware Threat Intelligence
For your tools and teams to function optimally, you need the most advanced and up-to-date knowledge on malware. Therefore, it’s important to leverage and integrate some leading malware threat intelligence feeds. Examples include:
- FBI InfraGard
- SANS Internet Storm Center (ISC)
- Abuse.ch URLhaus
- Open Threat Exchange (OTX)
- MISP
- Yeti
Additionally, taking part in larger threat intelligence sharing initiatives is a great way to enrich your automated malware analysis capabilities and help other organizations defend themselves. When it comes to battling today’s advanced malware, “strength in numbers” should be the guiding philosophy.
Automate Malicious File Submissions
Malware can be found everywhere, from suspicious email attachments to infected endpoints. To ensure that malware doesn’t escalate into full-fledged security issues, you need to establish automated API-driven workflows across your IT ecosystem. Basically, this will ensure that malicious files and attachments will automatically be submitted to sandboxes for analysis.
Integrate and Orchestrate Your Security Stack
Automation, in isolation, can only do so much. However, by integrating every single tool and workflow in your security program, you can make sure that your malware analysis tools aren’t working in isolation. Instead, they would be working along with multiple other platforms to find, triage, and mitigate potent malware. From ticketing and alerting tools to SIEM and SOAR platforms, everything must be highly orchestrated and tightly integrated.
Educate Staff About Malware Threats
In addition to cutting-edge automation-driven tools, you need to get every single employee in your company on the same page about malware risks and IoCs. This means educating staff regularly to improve awareness. Furthermore, automation doesn’t mean the complete removal of manual processes. To make the most of automated malware analysis, you need the support of intuitive and highly skilled professionals who are well-versed in malware security.
Constantly Improve Your Malware Security Program
Swapping out manual malware detection and response processes with automated malware analysis will immediately improve your security program. However, it’s very important that you can keep a close eye on the efficacy of your automated malware program. Threat actors are constantly creating new kinds of malware that can bypass even the most advanced security systems. Therefore, at every given opportunity, you must sharpen your malware security capabilities and optimize your tools and processes.
Conclusion
Automated malware and exploit analysis is the need of the hour and something that can truly elevate your cybersecurity program. With emerging malware threats more dangerous than ever, you need to say goodbye to manual malware analysis and embrace automation across your malware security activities.
Top use cases for automated malware analysis include threat hunting, EDR integrations, threat intelligence, phishing security, and SIEM optimization. To unlock benefits across these use cases, you must use the right malware analysis tools and threat feeds, automate malicious file submissions, integrate all your tools, train employees, and focus on constant optimization.
Lastly, by working with a managed security services provider (MSSP) with expertise in automated malware analysis, you can enrich your entire cybersecurity program and keep even the most potent strains of malware away from your organization.
