The field of malware file threat detection research has evolved considerably over the last few decades. Signature-based file scanning has proven to be one of the most popular threat detection methods during that time – though its efficacy as a stand-alone solution has diminished in recent years due to increasingly fast-paced improvements in malware authoring.

How does signature-based file scanning work?

Signature-based file scanning revolves around the idea that most malware files used in real world cyberattacks can be categorized in groups – or “families” – based on certain shared characteristics. By reviewing samples of known malware threats in depth, cybersecurity professionals can create referenceable “signatures” of various malware families and use them to detect infected files when scanning file storage locations for threats.

Over the years, communities of cybersecurity research professionals have accumulated myriad samples of known malware threats and rigorously studied their commonalities, grouping threats together by identifying shared characteristics such as data bytes, file hashes, printable strings, imported/exported functions, and more.

What are the primary benefits of signature-based file scanning?

The most prominent benefit of signature-based file scanning is the ability to identify multiple file threats belonging to larger malware families with a single signature match. This baseline consistency makes it easy to quickly detect & mitigate a large portion of widely distributed & overused malware files at once, such as those commonly attached in mass spam emails.

Another considerable benefit is scanning speed. Malware signatures are typically stored as text strings, and this lightweight interoperable format greatly increases the number of signatures that can be stored in one database & the speed at which signatures can be referenced during a scan.

What are the main disadvantages of signature-based scanning?

There are considerable drawbacks to signature-based scanning in the present-day cybersecurity threat landscape, and it’s important not to depend solely on signature-based file scanning for malware threat detection as a result.

These drawbacks largely stem from steady increases in cybercrime and the resulting faster-paced innovations in malware authoring. Much in the same way cybersecurity researchers study cybercrime trends to improve malware detection capabilities, threat actors study cybersecurity trends to overcome threat detection policies.

The most fundamental shortcoming of signature-based scanning is the lack of predictive capability. Relying on databases of established threat signatures can preclude the detection of zero-day threats, which are often deliberately designed to differ from known malware families.

Another limitation of signature-based scanning is the difficulty signature detection processes have with compressed malware files. Infected files can be masked from static signature-based file scanners during the file scanning process, only to reveal & execute malicious code once file decompression takes place. Custom malware delivery methods involving powerful file compression technologies (such as .ZIP and .RAR) are becoming more and more common.

File size can present an issue, too, if signature-based scanners are only configured to scan files below a specific size threshold. It’s becoming more common place for threat actors to bloat malware files with large volumes of useless code to throw off performance-oriented scanning features.

How can we appropriately utilize signature-based scanning?

Despite its drawbacks as an independent solution, signature-based file scanning remains an integral part of any dynamic malware file threat detection solution. It can be leveraged effectively alongside a variety of other modern threat detection techniques which balance out its deficiencies.

365-Degree scanning with the Cloudmersive Virus Scan API

The Cloudmersive Virus Scan API references a continuously updated list of more than 17 million virus and malware signatures in the initial stages of its 365-degree content protection scan. It additionally leverages heuristic analysis, file hashing, pattern matching, whitelisting, bytecode analysis & certificate analysis to identify a wide range of evolving threat types, and it allows for protection against custom content threats with in-depth content verification policies.

For more information about the Cloudmersive Virus Scan API, please do not hesitate to reach out to a member of our sales team.