Beyond Traditional Security: NDR's Pivotal Role in Safeguarding OT Networks

Why is Visibility into OT Environments Crucial? The significance of Operational Technology OT for businesses is undeniable as the OT sector flourishes alongside the already thriving IT sector. OT includes industrial control systems, manufacturing equipment, and devices that oversee and manage...

A whirlwind adventure: Malwarebytes' 15-year journey in business cybersecurity

As we raise a glass to toast Malwarebytes' 15th anniversary of boldly venturing into the realm of business cybersecurity, we're feeling nostalgic. It's time to buckle up and embark on a whimsical journey through the twists and turns of Malwarebytes' evolution. From modest beginnings to becoming a...

Information Disclosure

opensearch-anomaly-detection is vulnerable to Information Disclosure. The vulnerability exists because of the lack of access restrictions in field-level rules in numerical feature aggregations of the library, allowing a user with the Anomaly Detector role to read aggregated numerical data...

CVE-2023-23933

OpenSearch Anomaly Detection identifies atypical data and receives automatic notifications. There is an issue with the application of document and field level restrictions in the Anomaly Detection plugin, where users with the Anomaly Detector role can read aggregated numerical data e.g. averages,...

Design/Logic Flaw

OpenSearch Anomaly Detection identifies atypical data and receives automatic notifications. There is an issue with the application of document and field level restrictions in the Anomaly Detection plugin, where users with the Anomaly Detector role can read aggregated numerical data e.g. averages,...

CVE-2023-23933 Issue in Anomaly Detection with document and field level rules in numerical feature aggregations

OpenSearch Anomaly Detection identifies atypical data and receives automatic notifications. There is an issue with the application of document and field level restrictions in the Anomaly Detection plugin, where users with the Anomaly Detector role can read aggregated numerical data e.g. averages,...

CVE-2023-23933 Issue in Anomaly Detection with document and field level rules in numerical feature aggregations

OpenSearch Anomaly Detection identifies atypical data and receives automatic notifications. There is an issue with the application of document and field level restrictions in the Anomaly Detection plugin, where users with the Anomaly Detector role can read aggregated numerical data e.g. averages,...

CVE-2023-23933

CVE-2023-23933 concerns OpenSearch Anomaly Detection: the plugin improperly applies document- and field-level restrictions, allowing users with the Anomaly Detector role to read aggregated numerical data from restricted fields. This affects authenticated users who already had read access to the r...

CVE-2023-23933 Issue in Anomaly Detection with document and field level rules in numerical feature aggregations

OpenSearch Anomaly Detection identifies atypical data and receives automatic notifications. There is an issue with the application of document and field level restrictions in the Anomaly Detection plugin, where users with the Anomaly Detector role can read aggregated numerical data e.g. averages,...

PT-2023-19306 · Unknown +2 · Opensearch +2

Name of the Vulnerable Software and Affected Versions: OpenSearch versions prior to 1.3.8 OpenSearch versions prior to 2.6.0 Description: There is an issue with the application of document and field level restrictions in the Anomaly Detection plugin, where users with the Anomaly Detector role can...

About Anomalous Data Transfer detection in InsightIDR

By Shivangi Pandey Shivangi is a Senior Product Manager for D&R at Rapid7. Data exfiltration is an unauthorized movement or transfer of data occurring on an organization’s network. This can occur when a malicious actor gains access to a corporation’s network with the intention of stealing or...

The importance of combined user and data behavior analysis in anomaly detection

Muqeet Khan, Head of Sales Engineering Australia and New Zealand For decades security teams have understood the importance of tracking user behavior to identify potential cybersecurity threats. Behavior analysis systems first appeared in the early 2000s, and in 2015 Gartner officially defined Use...

The art and science behind Microsoft threat hunting: Part 2

We discussed Microsoft Detection and Response Team’s DART threat hunting principles in part 1 of The art and science behind Microsoft threat hunting blog series. In this follow-up post, we will talk about some general hunting strategies, frameworks, tools, and how Microsoft incident responders wo...

The art and science behind Microsoft threat hunting: Part 1

At Microsoft, we define threat hunting as the practice of actively looking for cyberthreats that have covertly or not so covertly penetrated an environment. This involves looking beyond the known alerts or malicious threats to discover new potential threats and vulnerabilities. Why do incident...

Enable Security Teams to Leverage Machine Learning Technologies

As on-premises and cloud-hosted data repositories get larger, they are outstripping the ability of traditional data-crunching methods to efficiently analyze the information. As a result, more enterprises have turned to data science and machine learning platforms to create business value. The...

Five Data Security Controls and Processes you Must Bring to Cloud-native Infrastructures

Too frequently, there are significant misunderstandings in organizations with regard to who has the responsibility to protect cloud-hosted data. In Imperva’s recent report, A Data-Centric Cybersecurity Framework for Digital Transformation, IT analyst and author Richard Stiennon explains what...

Anomaly Detection at Scale Using SQL and Facebook’s Prophet Forecasting Algorithm

Anomaly detection is a very important task. At Imperva we use it for threat hunting, risk analysis, risk mitigation, trends detection and more. In a previous post we showed how it can be done in a simple method by SQL. This time we wanted to use Prophet, which is an algorithm for forecasting time...

DeepTraffic - Deep Learning Models For Network Traffic Classification

For more information please read our papers.  Wei Wang's Google Scholar Homepage Wei Wang, Xuewen Zeng, Xiaozhou Ye, Yiqiang Sheng and Ming Zhu,"Malware Traffic Classification Using Convolutional Neural Networks for Representation Learning," in the 31st International Conference on Information...

The Tripod Foundation of a Database Analytics Solution for Today’s Threat Landscape

In the first and second posts in this series, we explained why traditional approaches are no longer viable to take on today’s threat landscape and showed why internally-generated attacks are so difficult to stop. In this post, we’ll identify the critical elements of a highly effective database...

How Wazuh Can Improve Digital Security for Businesses

2021 was a year peppered by cyberattacks, with numerous data breaches happening. Not only that, but ransomware has also become a prominent player in the hackers' world. Now, more than ever, it's important for enterprises to step up cybersecurity measures. They can do this through several pieces o...