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Artificial Intelligence (AI) has served as a great resource for cyber defenders by enabling real-time detection and response through advanced pattern recognition and predictive analysis that traditional methods weren't able to achieve. However, AI has recently become a dangerous and widely available enabler for attackers to leverage. CISOs now face adversaries who easily scale large-scale cyberattacks like spear-phishing and polymorphic malware at machine speed.  This article examines the rising AI-driven cyberthreat landscape and presents the browser, the enterprises' new endpoint, as the most strategic control plane for defense. By adopting a Secure Enterprise Browser (SEB) into the security stack, enterprises can reduce their attack surface, contain incidents at scale, and future-proof themselves against these advanced attacks.  Why Traditional Defenses Struggle Against AI  Most organizations have robust defense in place against cyberattacks, such as firewalls, EDR...

These days, there are plenty of ways to run DDoS simulation testing and make sure you're protected against attacks. You can do it on your own using commercial software or open-source tools—whatever works best for you. That said, there are a few must-haves when it comes to running DDoS tests. For one, you'll need a platform that allows you to easily start and stop attack simulations as needed. Plus, don't forget to notify and get approval from relevant parties, such as your cloud provider or tool vendor, before you begin testing. Beyond these basics, there are some best practices that can help you get the most out of your  DDoS testing . 1 – Plan tests to validate the protection of your most critical assets  While it may be easier to run black box testing (basically launching attacks without looking at the internal structure, architecture, and configuration of your protection), a white box testing approach is much more effective when it comes to uncovering serious vulnera...

Security teams today live in two different realities. On one side, platforms like ServiceNow create order: every vulnerability has a ticket, every incident has a workflow, and everything ties back to the CMDB. On the other side, attackers create chaos. They don't follow workflows. They look for the easiest way in, chaining together whatever exposures they can find until they reach something valuable. A vulnerability marked as "medium" in a ticketing system can still be the critical link in an attack path that leads straight to a company's crown jewels. In the ticketing system, the issue appears in isolation, yet attackers see how it connects to everything else. Without visibility into how exposures link together, teams risk wasting effort while the actual attack paths stay open. This is where ServiceNow's integration with XM Cyber comes in. By layering attack graph analysis onto VR and SIR , the platform lets teams see each issue through an attacker's eyes. Tickets and incidents ar...

Automated tools give you visibility. Adversarial testing gives you clarity. In Salesforce environments, you need both. The Problem with Checkbox Security in a Platform-Centric World Salesforce has become more than just a CRM—it's the backbone of how many organizations operate. It holds customer data, governs workflows, drives revenue, and connects to dozens of internal and third-party systems. But that complexity is exactly what makes it hard to secure. And too often, security teams rely solely on generic scans or scheduled audits that were never designed to handle the nuance of Salesforce's layered permissions, custom logic, and evolving integrations. The result? A lot of surface-level findings—and a lot of assumptions about what those findings actually mean. Automation Is Essential—But It's Only One Layer There's no question that modern scanning tools play a vital role in Salesforce security. The right platforms can surface deeply nested permissions, cross-object access paths,...

As AI continues to make inroads into enterprise security, it's easy to see the appeal: faster triage, smarter detection, and fewer manual workflows. From SOAR platforms streamlining alerts to AI-enhanced identity systems approving access requests in milliseconds, the value proposition is clear — greater efficiency, speed, and scale. But here's the rub: speed without scrutiny can lead to security drift. AI is a powerful enabler, not an autonomous guardian. And in corporate security — where stakes include sensitive employee data, internal intellectual property, and privileged infrastructure — the absence of human oversight isn't just risky; it's potentially catastrophic. AI as a Copilot, Not a Commander In modern corporate security environments, AI-driven tooling is increasingly embedded into day-to-day operations. Triage systems leverage AI to correlate alerts, automation scripts to remediate routine issues, and IAM platforms auto-approve low-risk access. These advancements undenia...

Compliance is often treated as a paper exercise, something to tolerate, check off and forget. But in a threat landscape shaped by ransomware-as-a-service, AI-augmented phishing campaigns, and supply chain breaches, delaying compliance doesn't just create business and operational friction. It creates risk.  When compliance is layered late, organizations face mounting costs: duplicated controls, misaligned security priorities, reactive remediation efforts, and worst of all, security blind spots that attackers can exploit. Treating compliance as an afterthought is a gamble.  In this post, we highlight the real cost of sidelining compliance and why embedding compliance into your security strategy from the start is not just good hygiene, it's essential engineering.  Security and Compliance: Not Opposites, but Allies It's easy to think of security as "protecting" and compliance as "documenting". But that split is artificial. Frameworks like ISO/IEC 27001, NIST CSF, PCI ...

With thousands of endpoints, cloud instances, remote users, and third-party integrations, securing the enterprise has become a massive target. Each change in the IT environment - whether driven by digital transformation, M&A activity, or routine system updates - creates new opportunities for adversaries to leverage. Yet, the network is the backbone of business operations. It must always be available to support production, collaboration, and growth.  In this article, we'll explore the specific challenges large enterprises face when validating their security posture and how leading security teams are evolving their testing strategies to match the scale, speed, and sophistication of large, multi-faceted IT networks.  The Challenges of Validating Enterprise Network Security Enormous attack surface - In large enterprises, the attack surface spans countless assets across on-prem, cloud, and hybrid environments, making comprehensive security validation incredibly complex. Ac...

Security and compliance professionals are no strangers to complexity. From staying ahead of ever-evolving threat landscapes to navigating an expanding web of regulatory requirements, the day-to-day demands often feel like a game of whack-a-mole. Enter AI copilots—powerful tools that, when used thoughtfully, can dramatically streamline operations and supercharge your security and compliance programs. While much of the hype around AI focuses on futuristic capabilities, the real magic today lies in using these tools to augment existing workflows. Think of copilots not as replacements for security teams, but as force multipliers—always-on assistants that help reduce toil, improve consistency, and enable teams to focus on higher-value initiatives. AI Copilots in Action: Security & Compliance Use Cases AI copilots are no longer just experimental toys. Here are a few ways forward-thinking security teams are using generative AI tools—like OpenAI's custom GPTs and Google's Gemini Gems...

For many organizations, managing IT assets is like trying to complete a jigsaw puzzle without all the pieces. Despite massive investments in security tools and controls, many companies still have critical gaps in their ecosystems that leave them vulnerable to breaches. Often, these gaps stem not from a lack of tools—if such a thing exists in security—but from incomplete visibility and integration across those tools. By aggregating and analyzing data from multiple systems, security leaders can gain a more robust picture of their IT inventory and subsequently, their security posture. The challenge with disparate security tools It's not unusual for enterprises to deploy a wide array of security tools. The average organization uses roughly 10 security tools, covering everything from endpoint management to identity and access control. These tools, however, often operate in silos, creating fragmented and occasionally contradictory reports. Let's look at a practical example. Conside...

Shadow AI is presenting new challenges for security leaders. While AI tools have already revolutionized how we work, they've also created unprecedented security challenges that our traditional strategies or tools simply weren't designed to handle. I've spent the last decade working with organizations grappling with emerging tech risks, and I can tell you that this is different. In this post, we'll talk about why, and more importantly, what you can do about it. The Hidden Risks of AI Adoption: Shadow AI The Wiz research team recently uncovered a publicly exposed DeepSeek production ClickHouse database , leaking chat history, API secrets, and other sensitive data—raising serious concerns for any organization using DeepSeek's models. Truth is that many teams rushed to try out DeepSeek given the hype around its truly advanced technologies. While the DeepSeek situation has been surrounded by FUD, drama, and misinformation, it has also set important precedents for privacy ...