Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Top 5 Strategies to Reduce Dwell Time with XDR: Accelerating Threat Detection and Response

Cyber adversaries operate with one goal in mind—stealth. The longer they go undetected in an environment, the more damage they can cause. Dwell time is the total amount of time that a threat remains unnoticed in a system, from initial compromise to discovery. According to the most recent threat reports, the average dwell time for undetected breaches has reduced but remains at 10-15 days, providing attackers enough time to exfiltrate data, launch ransomware, or establish persistent access.

Adventures in monitoring a hostile network: Black Hat Europe 2024

Working in the network operating center (NOC) at Black Hat Europe, we’re never quite sure what we’re going to see. The anxiousness I feel there is similar to what I’d experience when I was blue-teaming for a corporate network. I could prepare all I wanted, read all the blogs about the current threat trends people and companies were tracking on the Internet, and review all the red team and vulnerability scanner reports to identify likely targets.

Operationalizing TLSH for Detection with David Burkett

David Burkett, Cloud Security Researcher at Corelight, joined Defender Fridays to discuss operationalizing TLSH for detection which enables fast, scalable, and resilient identification of near-duplicate files, helping to uncover malware variants and similar threats with minimal false positives.

The Importance of Identity Threat Detection and Response (ITDR) in 2025

As cyber threats continue to evolve, organizations face a growing challenge: protecting their most critical assets – identities. With identity now at the heart of security strategies, 2025 marks a pivotal year for addressing identity-centric risks, making Identity Threat Detection and Response (ITDR) a vital component of enterprise security.

Enhancing API Security with Automated Threat Detection

As digital ecosystems continue to grow, APIs have become vital to business operations, enabling seamless data exchange and service integration. However, this increased reliance on APIs also makes them obvious targets for malicious actors. Some common threats such as credential stuffing, scraping, and denial of service (DoS) attacks pose significant risks, leading to data breaches, financial losses, and a decline in customer trust.

Sweet Security Introduces Patent-Pending LLM-Powered Detection Engine, Reducing Cloud Detection Noise to 0.04%

Sweet Security, a leader in cloud runtime detection and response, today announced the launch of its groundbreaking patent-pending Large Language Model (LLM)-powered cloud detection engine. This innovation enhances Sweet's unified detection and response solution, enabling it to reduce cloud detection noise to an unprecedented 0.04%. Sweet uses advanced AI to help security teams navigate complex and dynamic environments with improved precision and confidence.

The Critical Evolution of Cloud Detection and Response

Cloud security has reached an inflection point. Organizations have accelerated their cloud adoption and must navigate a complex threat landscape where workloads spin up and down in seconds, applications deploy continuously and identities span multiple services and providers.