Why Predictive Technology is Essential for Modern Email Security

There are an endless number of buzzwords currently trending throughout the cybersecurity industry. From AI and automation to machine learning, threat hunting and offensive cyber, every month a new term takes shape and spreads across marketing materials like malware on a mission.

One such term currently gaining in popularity is “prediction” or “predictive technology.” While ambiguous in sound, truly predictive technology is helping some security companies, like IRONSCALES, move beyond reactive (detection) to introduce proactive (prediction) innovations that are transcending the industry’s history of response over anticipation.

Predictive technology is the use of machine learning to calculate with confidence a future event. Driven by user-led intelligence sharing, predictive technology empowers organizations to proactively prepare for trending email phishing attacks by leveraging an entire virtual global analyst community. Overall, threat prediction can help businesses use data to prepare for what the next attack will look like, and to proactively prevent similar or trending attacks from infiltrating or repeat attacks from occurring.

An example of predictive technology:

Based on what we know about the five previous email phishing attacks from just seconds ago, we can predict with high confidence what the next attack will look like.

In other words, predictive technology must be based on real-time decisions done by real human experts on a minutely basis. For busy security and SOC teams, the capacity to predict future events with a high-level of certainty is a potential resource savior and a major risk reducer to their number one threat – email phishing attacks.

The Benefits of predictive tech to email security

Organizations that only try to predict based on yesterday’s attack will always remain behind as more than 1,150 new secure phishing sites come online every day, according to an article in SC Magazine. In a whack-a-mole security environment, staying ahead and anticipating the next attack is the only way to reduce risk.

As cybercriminals constantly exploit email vulnerabilities and create new attack methods, organizations must process threat data as quickly as possible. Propelled by machine learning, predictive technology can log attack details and cross-reference users’ emails in near real-time to search for similar patterns. Whereas in many companies this burdensome and time-consuming responsibility would fall directly onto SOC and IT security teams, organizations using predictive technology benefit from the analysis and recommendations of not just machine analysis, but also the analysis by a global SOC community of analysts that have already been exposed to such an attack.

Likewise, predictive tech can operate in a sandbox environment to determine how new exploits may unfold then flag suspected emails throughout the system the instant a threat is detected. With predictive technology, organizations can improve their decision making by turning complex data into visual and actionable intelligence. As stated by Gartner, “defending as a pack has advantages over defending yourself in isolation.”

Specifically, for email security, prediction capabilities allow IT security and SOC teams to:

• Automatically remove trending attacks – Based on our research, predictive technology can identify at least 30 percent of attacks that are missed by technical and/or human controls. That’s because once one company reports an attack, machines can synthesize the attack signature, binaries etc. and automatically share that information with other companies, turning that data into actionable intelligence on trending attacks before the attack reaches other organizations. This means that an attack trending worldwide may never impact your business simply because it has already impacted a business within the community.
• Automatically remove polymorphic attacks – Polymorphic attacks average 8.3 permutations. For security tools that aren’t predictive by nature, polymorphism is more likely than not to go undetected. With predictive technology, polymorphic attacks can be automatically removed, as machine learning technology can proactively predict how an attack may evolve, based on the prior patterns of exploits, and can then cluster these similarities in attacks to stop repeat or similar looking attacks instantly.
• Reduce Time and Noise – Why waste time on incident investigation and response if another organization has already confirmed a threat as malicious and/or set the precedent for how to respond? With predictive technology, companies can reduce the noisiness of manual, semi-manual or rules-based threat investigation and response and focus on tasks that require more immediate attention. Whereas manual response is cumbersome, and semi-manual and rule-based methods work with partial automation capabilities, they cannot proactively predict incidents and are purely reactive. Therefore, in order to reduce time and noise and implement an automated response, actionable data derived from predictive technology is necessary to effectively detect, classify and remediate phishing attacks.

IRONSCALES predicts email phishing attacks with uncanny accuracy

With the full IRONSCALES platform, we help our customers prepare for and automatically detect and respond to new phishing incidents. In essence, we help predict for what our customers will see based on what other users on the platform have already seen.

Our platform significantly reduces the risk of emerging phishing campaigns by leveraging the power of collective intelligence to prepare for phishing attacks before they hit inboxes. The platform provides high quality; real-time human verified phishing detection and threat intelligence - and reduces security teams’ resource strains by leveraging a threat intelligence community of security professionals that scales as more companies join.

As more advanced phishing threats arise, the IRONSCALES platform will continue to have the best protection by leveraging that collective human intelligence within the community, along with the platform’s machine learning algorithm capabilities to quickly identify logged threats and share that information automatically and anonymously.

To learn more about the entire IRONSCALES platform, contact us.