The SMLS team enables Splunk customers to find obscure and buried threats in large amounts of data through expert analytics. This work is part of a set of machine learning detections built by a specialized team of security-focused data scientists working in concert with Splunk’s threat research teams to help Splunk customers sift through vast amounts of data to identify and alert users of suspicious content.

Ransomware attacks are on the rise. Many organizations have fallen victim to ransomware attacks. While there are different forms of ransomware, it typically involves the attacker breaching an organization’s network, encrypting a large amount of the organization’s files, which usually contain sensitive information, exfiltrating the encrypted files, and demanding a ransom.

Phishing is one of the most common online security threats. A phishing website tries to mimic a legitimate page in order to obtain sensitive data such as usernames, passwords, or financial and health-related information from potential victims. Machine learning (ML) algorithms have been used to detect phishing websites, as a complementary approach to signature matching and heuristics.

Security is a data problem. One of the most touted benefits of artificial intelligence (AI) and machine learning (ML) is the speed at which they can analyze potentially millions of events and derive patterns out of terabytes of files. Computational technology has progressed to the point where computers can process data millions of times faster than a human could.

The Splunk Vulnerability Disclosure SVD-2022-0604 published the existence of an attack where the dashboards in certain Splunk Cloud Platform and Splunk Enterprise versions may let an attacker inject risky search commands into a form token.

Contrary to what you might have read on the Internet, machine learning (ML) is not magic pixie dust. It’s a broad collection of statistical techniques that allows us to train a computer to estimate an answer to a question even when we haven’t explicitly coded the correct answer into the program.