A threat intelligence platform is typically equipped with a number of tools designed to help security teams identify threats before they create big problems. Threat scoring is one such tool. Once considered an advanced feature by some platform developers, threat scoring makes it possible for security teams to assess and prioritize potential threats.
DarkOwl, producers of one of the cybersecurity industries best threat intelligence platforms, recommends threat scoring for a number of reasons. First, cybersecurity threats are ongoing. Second, threat actors target their victims from multiple angles. And third, without the ability to assess and prioritize, organizations can find themselves chasing down too many threats all at once.
Some Threats Are Worse Than Others
Despite the ongoing nature of the modern threat landscape, not every threat identified by organizations like DarkOwl actually comes to fruition. Many do not. This suggests an obvious truth that may be lost on security teams that don’t use threat scoring: some threats are worse than others.
Threats with the highest scores are the most serious and usually the most imminent. They are the ones that need to be addressed first. As security teams go down the score sheet, they prioritize based on seriousness. Those with the lowest scores pose minimal risk.
Integration With Threat Intelligence Platforms
The threat scoring concept is neither new nor limited to threat intelligence platforms. It has been around since the dawn of cybersecurity. But in more recent years, integrating the concept into threat intelligence software has led to a number of different ways to leverage threat scoring.
For example, confidence scoring is fairly common. A platform assigns a confident score based on what are known as indicators of compromise (IOCs). Scores are calculated on a scale of 0-100. A score of 100 indicates a highly malicious threat while a score of 0 suggests non-malicious activity.
Today’s threat intelligence platforms are equipped with artificial intelligence (AI) models capable of automatically calculating scores based on preconfigured parameters. The main benefit here should be obvious: eliminating the need to manually assess threat data makes detection and response faster, more efficient, and more productive.
Threat Scorings Key Parameters
Threat scoring is based on a number of key parameters. Each of the parameters affects confidence. They are:
- Relationships – Relationships are seen as connections between threat indicators expressed through what is known as the Structure Threat Information Expression (STIX).
- Scoring Source – An objective analysis of the reliability of data intelligence sources.
- External Enrichment – External data gleaned from third-party enrichment sources.
- Sightings – An assessment of appearance frequency across different channels.
By utilizing a broad list of key parameters, threat scoring can be made more consistent and stable. The proper parameters keep things in perspective so that minor threats do not get blown out of proportion while serious threats are ignored.
Customizing Threat Scoring
One of the most attractive aspects of threat scoring is that it does not have to be static. A threat intelligence platform should allow security teams to customize their scoring parameters to align with their priorities. And because threat landscapes can look vastly different from one organization to the next, customization allows for better scoring.
Included in customization is the ability to establish confidence score thresholds. These thresholds determine which potential threats require immediate attention.
Although threat scoring is nothing new in cybersecurity, it has taken on a whole new life with the introduction of AI-powered threat intelligence platforms. Comprehensive platforms capable of gathering reams of data and analyzing it at breakneck speed allow for a scoring system that gives organizations an upper hand in the fight against cyber threats.
