Autonomous Endpoint Management Isn’t Just Efficiency, It’s a Security Imperative

Autonomous Endpoint Management cuts exposure time by matching patch speed to attacker breakout timelines, reducing risk, workload delays, and breach costs...

What is Patch Management Automation and Why It Matters

Executive Summary Environments rarely stay as orderly as they begin. New workloads, faster releases, and growing attack surfaces stretch manual patching beyond its limits. The real risk emerges in the widening gap between spotting a vulnerability and fixing it. Automated patch management closes...

An Efficient Recommendation Filtering-Based Trust Model for Securing Internet of Things

Trust computation is crucial for ensuring the security of the Internet of Things IoT. However, current trust-based mechanisms for IoT have limitations that impact data security. Sliding window-based trust schemes cannot ensure reliable trust computation due to their inability to select appropriat...

Inside Grammarly’s AI-driven automation with the MCP Server for Wiz

Meet the system that cut manual triage times by 90% and enables engineers to focus on strategic thinking...

Accelerating Automatic Program Repair with Dual Retrieval-Augmented Fine-Tuning and Patch Generation on Large Language Models

Automated Program Repair APR is essential for ensuring software reliability and quality while enhancing efficiency and reducing developers' workload. Although rule-based and learning-based APR methods have demonstrated their effectiveness, their performance was constrained by the defect type of...

Hybrid Privacy Policy-Code Consistency Check Using Knowledge Graphs and LLMs

The increasing concern in user privacy misuse has accelerated research into checking consistencies between smartphone apps' declared privacy policies and their actual behaviors. Recent advances in Large Language Models LLMs have introduced promising techniques for semantic comparison, but these...

DYNAMITE: Dynamic Defense Selection for Enhancing Machine Learning-Based Intrusion Detection against Adversarial Attacks

The rapid proliferation of the Internet of Things IoT has introduced substantial security vulnerabilities, highlighting the need for robust Intrusion Detection Systems IDS. Machine learning-based intrusion detection systems ML-IDS have significantly improved threat detection capabilities; however...

How to Automate Security Questionnaires and Reduce Response Time

Security questionnaires take a lot of time and repetitively answering the same questions manually chews up business time…...

Suppressing the Adversary via Threat Hunt Teams

What a brave new world. Global cyber insurgencies continue unabated. Decreasing dwell time is imperative in 2018. In order to achieve this goal, we must embrace the hunt. Every organization should stand up a threat hunt team. The team must be multidisciplinary with experience in e-forensics and...

[Arachni v0.4.6 - Web User Interface v0.4.3] Open Source Web Application Security Scanner Framework

Arachni is a feature-full, modular, high-performance Ruby framework aimed towards helping penetration testers and administrators evaluate the security of web applications. Arachni is smart, it trains itself by learning from the HTTP responses it receives during the audit process. Unlike other...