Predicting vulnerabilities with ESOF Prediction

At TAC Security, our security experts work hard to broaden our leading technology in risk-based vulnerability management. Our ESOF Prediction Model predicts the new vulnerabilities of the upcoming month. To advance the cyber security sector, the prediction model acknowledges innovation and insights behind our platform.

We use machine learning to predict the vulnerabilities immediately when the exposures are declared. Later on, its exploit is released, though whether or not the exploit will be used in attacks or not.

Demonstrate why this matters and what makes us different from the competition.

• A sheer learning curve is there in machine learning. To do something insightful, it includes a teaching box contrived with silicon chips and electrical impulses. In our Prediction Model case, when a vulnerability is likely to become deploy acknowledgment.

• Machine learning takes a lot of detail and time to give actionable outcomes. We’ve created a prediction model that shows how and when the vulnerability has been exploited. Besides, we run thousands of inspections through those models to help us make our platform calibrate. However, this takes an abundance of time out of the gate. With time, we’re getting ahead of our competitors and improving.

• Our platform is a database skeptic, making it one of our defining identifiers for us. TAC clients can get an advantage from our wide range of available data sources, which eventually increases the number of inspection feeding into our machine learning algorithm and provide various inspections to meet real-world circumstances.

• Our work speaks to numerous companies with machine learning and predicting potential. Most of them don’t do that. We provide a high level of clarity regarding our Prediction Model. Our machine-learning algorithm is based on several factors: our employees, data scientists, competitors, and customers can learn about it here. Our experts have worked on making it an effective ESOF prediction model against common remediation strategies, using the entire database of CVEs.

This builds trust in our clients and customers. Customers can see exactly how our prediction model work on the ARIMA model, so they know exactly what they are getting.

TAC’s ESOF prediction model is based on the idea that risk does not come from vulnerabilities but from attackers who exploit them. With so many vulnerabilities on networks, companies need help to keep up. Predicting which vulnerabilities for the upcoming month saves your system from these vulnerabilities’ attacks.

ESOF Prediction Feature

The ESOF Prediction feature predicts how many vulnerabilities will be discovered in the coming month. Based on that number, it will also predict the ESOF cyber score for the upcoming month. 
For more details or solutions, download our ESOF Prediction Solution Brief.