Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

How Trust Centers and AI are replacing security questionnaires and accelerating B2B sales

As Anna say in the podcast, “Security reviews show up just when you think the deal is about to close. It’s like a final boss that no one wants to fight.” The last-mile friction caused by security diligence isn’t new, but it’s becoming more painful as deal cycles tighten and expectations around transparency rise. Buyers want answers faster. Vendors want to close faster. And security teams, stuck in the middle, are often left juggling risk, reputation, and revenue timelines.

What is Data Lineage?

In this video, we break down the concept of data lineage — a way to track how data moves, changes, and is used across your organization. Data lineage provides visibility into the lifecycle of sensitive information, from where it originates to where it flows, and who interacts with it. Understanding data lineage helps organizations improve security, ensure compliance, and reduce insider risk. Watch now to learn what data lineage is, why it matters, and how it helps protect your most valuable data.

What is Insider Risk Management?

In this video, we explain the basics of insider risk management — the practice of identifying, assessing, and reducing the risks that come from employees, contractors, or partners who have access to sensitive data. Insider risk management goes beyond traditional data loss prevention by addressing both malicious and accidental insider threats. From protecting intellectual property to preventing data leaks, insider risk management helps organizations secure their most valuable information.

Insider Risk vs Insider Threat: What's the Difference?

In this video, we break down these two important but often-confused terms in cybersecurity. Insider risk refers to the potential for harm that comes from employees, contractors, or partners who have access to sensitive data — whether accidental or intentional. Insider threat is when that risk becomes an actual malicious or negligent action that puts your organization at risk.

Boost trust with HIPAA compliance: proven strategies for healthcare

Imagine this: a single breach that exposes a few patient files, and suddenly your organization is facing multi-million dollar fines, legal scrutiny, and eroded trust from the public. Now add regulatory audits, internal investigations, and the constant stress of proving compliance at every turn. The stakes are simply too high to treat HIPAA as an afterthought.

The Cybersecurity Lifecycle: How Torq Automates Detection, Response, and Recovery

The cybersecurity lifecycle is the foundation of how security teams protect, detect, and recover from threats. From asset discovery to post-incident recovery, the lifecycle defines the processes organizations rely on to safeguard data and systems. But here’s the challenge: While the lifecycle provides a roadmap, operationalizing it in modern SOCs is messy. Disconnected tools, alert fatigue, and endless manual tasks slow down response times and create gaps that attackers exploit.

How Can NDR Help You Detect Exploitation-and Fix Vulnerabilities Faster?

Many organizations struggle to address network security vulnerabilities in time. By the time vulnerabilities are discovered, attackers may already be exploiting them across your infrastructure, especially in areas where visibility is limited. That delay leaves you scrambling patches get applied too late, remediation workflows are disjointed, and attackers can move laterally or exfiltrate data before containment begins.

The Hidden Risk in Enterprise AI, and the Smarter Way to Safeguard Data

AI exploded into the workplace overnight, reshaping how we work. Today, nearly every employee is experimenting with tools to move faster and think bigger. However, that acceleration comes with risk. According to Cyberhaven Labs’ latest research, nearly three-quarters of AI apps in use pose high or critical risks, and only 16% of enterprise data sent to AI ends up in enterprise-ready apps. The rest flows to personal or unvetted tools.

Adversarial AI and Polymorphic Malware: A New Era of Cyber Threats

The state of cybersecurity has always been in flux, but the arrival of tools like ChatGPT heralded one of the most significant challenges for security teams in years. AI has the potential to unlock incredible potential in data processing and malware detection, but in the wrong hands, Large Language Models (LLMs) and other adversarial AI tools can be used to develop polymorphic malware that can escape detection, gain access to sensitive data, and poison data sets.