Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Mobile security has always been complex, but LLM technology has added a whole new dimension to the field. Behind every popular generative AI (genAI) tool is a comprehensive large language model (LLM) that provides data and parses queries in natural language. When used responsibly, LLMs can be useful tools for ideation and content generation. In the wrong hands, though, LLMs can help threat actors supercharge their social engineering scams.

If your organization hasn’t encountered a vishing attack yet, it’s probably only a matter of time. Vishing, or voice phishing, is a sophisticated type of social engineering that adds a whole new dimension to common scams. Rather than emails or text messages, threat actors employ phone calls or online voice calls to carry out vishing schemes. Particularly savvy attackers can even copy a real person’s voice to deceive, coerce, or manipulate potential victims.

We’re excited to share the findings of our commissioned Forrester Consulting Total Economic Impact (TEI) study, published in January 2026. This study examines the return on investment (ROI) that organizations realized by deploying a unified platform for managing and securing the software supply chain.

See how Torq harnesses AI in your SOC to detect, prioritize, and respond to threats faster. Request a Demo For the last decade, the cybersecurity industry has attempted to solve a technology problem with a human solution.

What are the three types of cloud compliance tools? Audit-prep platforms (Drata, Vanta) automate evidence collection for certifications. Security posture management/CSPM (Wiz, Prisma Cloud) scan configurations at a point in time. Runtime compliance verification (ARMO, Sysdig) monitors actual workload behavior continuously. Choosing the wrong type means solving for the wrong problem. What is compliance drift and why does it matter? The gap between your last scan and your current state.

What’s the difference between container scanning and container security? Scanning finds vulnerabilities in images before deployment—it’s container auditing, not container security. Real security requires runtime visibility: seeing what processes execute, what network connections occur, and what files get accessed while containers run. Most teams have scanning covered. Most teams are blind at runtime.

Your CNAPP dashboard shows 10,000 critical findings from last night’s scan. Your CSPM flags misconfigurations every hour. Yet when the SOC asks what actually happened during last week’s incident, you’re still stitching together logs from five different tools to build a timeline that makes sense. Sound familiar? We recently spoke with a platform security lead at a fintech company running 400+ microservices on Kubernetes. Their CNAPP generated 47,000 findings in Q3.

In cybersecurity, incidents test more than just technical resilience ‒ they also test trust. As a managed service provider (MSP), the preventive measures you implement are critical. However, the strength of your support during your clients’ most critical times is what truly defines the trust they have in you. A cybersecurity incident may be precisely the moment when your client evaluates whether you are delivering on your promises as a quality partner for their business.

Managed service providers (MSPs) manage multiple client environments at the same time. It’s not an easy task, as threats move quickly and alerts never stop. It poses a big challenge for human-only SOC teams to handle such huge volumes of alerts and threats. This is where AI SOC changes how security operations are conducted for MSPs. An AI SOC uses artificial intelligence to monitor activity and identify threats in real-time.