Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Earlier this year, FedRAMP RFC-0012 signaled a coming shift in how cloud service providers (CSPs) working with the U.S. federal government are expected to handle vulnerabilities. It outlined plans to move FedRAMP away from simple CVSS-score thresholds and toward continuous, context-aware, exploitability-driven, and automation-first vulnerability management.

Like any other global industry, financial services companies face tremendous challenges of scale and complexity when it comes to managing cyber risk across their digital supply chain. The financial services supply chain is composed of more than 1.6M third-party relationships across the industry ecosystem.

Modern engineering teams ship fast. Attackers move faster. CI/CD pipelines are no longer just build systems; they are a critical part of production infrastructure. A compromised pipeline can allow attackers to inject malicious code, poison dependencies, leak secrets, or deploy compromised builds directly to production. As Engineering Managers, we’re expected to maintain high delivery velocity while reducing security risks.

Applicability thresholds of state privacy laws often hinge on size or scale. TDPSA is different. It puts no revenue thresholds like CCPA or CPRA. So if your business operates in Texas or reaches the state’s residents, you’re most likely inside the scope already. The law took effect on July 1, 2024, and by January 2025, the universal opt-out obligations became fully enforceable. That transition is what moved TDPSA from a policy update to a website-level requirement.

From intelligent chatbots to autonomous agents, innovation has never moved faster thanks to GenAI. But with the rate of velocity comes a massive new challenge: a class of complex, non-deterministic security risks that traditional cybersecurity methods are simply not equipped to handle. AI-native applications are already running in production. Across industries, teams are deploying copilots, RAG systems, autonomous agents, and AI-powered workflows faster than traditional security processes can keep up.

AI agents are moving fast. They book meetings, draft emails, summarize calls, search internal knowledge bases, and increasingly act on behalf of users. And as more teams adopt these systems, a familiar question surfaces almost immediately: How does GDPR apply to AI agents? What we’ve learned—working with startups rolling out AI features across support, sales, HR, and engineering—is that GDPR is not a blocker.

On April 8, 2025, the National Security Division (NSD) of the US Justice Department (DOJ) implemented the Data Security Program (DSP).

In this episode of Security Matters, host David Puner welcomes back David Higgins, senior director in CyberArk’s Field Technology Office, for a timely conversation about the evolving cyber threat landscape. Higgins explains why today’s attackers aren’t breaking in—they’re logging in—using stolen credentials, AI-powered social engineering, and deepfakes to bypass traditional defenses and exploit trust.

Application Security, WAF, and OWASP form an interconnected defense strategy for web applications. OWASP (Open Web Application Security Project) provides the framework for identifying critical vulnerabilities through resources like the OWASP Top 10, while WAFs act as the protective layer that detects and blocks attacks targeting these vulnerabilities in real-time.

In times of geopolitical and economic instability, no organization would consider running without backups, additional support, clear end goals, and company-wide communication. Within business, the wisdom of strength in numbers and power in unity is widely understood. However, when it comes to its cybersecurity, a critical pillar that reputation, safety, and resilience rely upon, the opposite often happens.