Dive into CVSS Scores
Understand CVSS by examining the Atlassian CVE-2023-22515 and CVE-2023-22518.
A Risk Based Approach To Vulnerability Scoring
An in-depth exploration of EPSS, its data-driven approach to assessing cybersecurity threats, and how it complements CVSS.
When Bots Break Bad
Even 'good' bots can end up abusing your site and impacting performance, learn why and how to stop it.
Advanced Anomaly Detection
Deep dive into Robust Random Cut Forest (RRCF) implementation for real-time anomaly detection in Application Security Platforms. Learn how advanced machine learning algorithms enhance threat detection and automated response capabilities.
Double MAD?
This article explores the use of Double Median Absolute Deviation (Double MAD) for anomaly detection in time series data, particularly in skewed or non-symmetric distributions.
Double MAD vs the Rest
A look at the limitations of Double MAD for anomaly detection, and a comparison with the Z-score method, to help you choose the right approach for your data.
Scaling anomaly detection with RRCF
Discusses strategies for scaling the Robust Random Cut Forest (RRCF) algorithm for large-scale anomaly detection, including using summary statistics, buffering input, and parallelisation.
Applied RRCF - thresholding techniques.
Explores various thresholding techniques like Median Absolute Deviation (MAD), Min/Max, and Z-Score for interpreting Robust Random Cut Forest (RRCF) anomaly scores, crucial for classifying data points as normal or anomalous.