Heuristics is a decision-making process with origins predating the field of cybersecurity. It was conceptualized by psychologists in the 1950’s to overcome perceived limitations in rational decision making, and it promotes educated guesses & trial-and-error methods to find solutions to problems where incomplete information is a major limiting factor. In the context of cybersecurity, heuristic analysis concepts are used to balance out the deficiencies absolute threat detection methods like signature-based threat detection by focusing on rules, patterns and behaviors.

How does heuristic threat analysis work?

Heuristic threat analysis is, first and foremost, a proactive approach to malware threat detection, while signature-based threat detection is a fundamentally reactive approach. The heuristic model aims to identify characteristics of unknown or modified malware threat types without relying on referencing a definitive database of threat signatures.

Heuristic threat analysis often incorporates a rule-based approach to identify suspicious files. For example, if a heuristic threat detection scan identifies a file which is attempting to make changes to the files around it, it might deduce that this file is a threat purely based on its behavior. The concept of behavioral analysis doesn’t end there; heuristic threat analysis can also be used on a much broader scale to identify inconsistencies and suspicious actions in network traffic.

It's also important to note that the heuristic threat detection model isn’t limited to static threat analysis. Heuristic threat analysis can be dynamic – particularly when it involves sandboxing. By deploying a specialized virtual machine and opening suspicious files within that environment, it’s possible for cybersecurity professionals to play out a controlled execution of a potential malware threat and analyze the suspicious file for threatening behavior. Infected files without known signatures are still likely to exhibit common malware behaviors – such as file duplication & file overwriting – and careful analysis of these behaviors in a sandbox can mitigate zero-day threats.

What are the main benefits of heuristic threat analysis?

As previously outlined, the primary benefit of heuristic threat analysis is zero-day threat detection. This inherently predictive threat detection model helps cast a wide net in any malware scanning process, and it can be used effectively in continuous around-the-clock threat monitoring to catch new threats instantly.

What are the limitations of heuristic threat analysis?

Heuristic threat analysis can sometimes suffer from turning out false positive results on non-threating files. If heuristic threat rules monitor file behaviors too stringently, it’s likely that dozens of clean files will be flagged, quarantined, or deleted when they shouldn’t be, which only makes a cybersecurity professional’s life more difficult.

In comparison, signature-based threat detection policies have the exact opposite issue, often flagging too few files and missing zero-day threats with unique or modified characteristics. This is one of the major reasons why heuristic threat analysis and signature-based detection policies are used together (among various other threat detection methods) in modern threat detection solutions.

Heuristic analysis with the Cloudmersive Virus Scan API

The Cloudmersive Virus Scan API scans files for viruses, malware, and additional threats within a sandbox. This sandbox layer includes several layers, including file hashing, signal extraction, pattern matching, heuristics, whitelisting, bytecode analysis, and certificate analysis. This dynamic approach to virus scanning ensures efficient, accurate detection of existing & zero-day threats while greatly reducing the likelihood of false positives.

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