Bottom Line Up Front Adversarial machine learning (AML) is the practice of identifying, exploiting, and defending against weaknesses in AI and ML systems — everything from evasion attacks that fool a fraud-detection model to data poisoning that corrupts a training pipeline before the model ever ships. If your organization deploys ML models for fraud detection, … Read more
Bottom Line Up Front If your organization is deploying large language models — whether that’s a customer-facing chatbot, an internal copilot, or an LLM-powered feature embedded in your product — you’ve introduced a new attack surface that traditional application security controls weren’t designed to catch. LLM security risks like prompt injection, data leakage, and model … Read more
Bottom Line Up Front Multi-factor authentication (MFA) is the single highest-leverage control in your security stack. It stops the vast majority of credential-based attacks — phishing, credential stuffing, password spraying — that would otherwise walk straight past a strong password policy. If your organization hasn’t deployed MFA universally, it’s the first gap you should close, … Read more
Bottom Line Up Front By the time you see encrypted file extensions and ransom notes, you’ve already lost. Ransomware detection is about catching the attack in its earlier stages — initial access, privilege escalation, lateral movement, and staging — before the encryption payload ever executes. Modern ransomware operators spend days or weeks inside a network … Read more
Bottom Line Up Front SD-WAN security determines whether your distributed network edge is a compliance asset or your biggest unmanaged risk. As organizations replace MPLS with software-defined WAN to connect branch offices, cloud workloads, and remote sites, they’re often trading a physically isolated network for one that routes sensitive traffic across the public internet — … Read more
Bottom Line Up Front Secure code review is the systematic process of examining source code to identify security vulnerabilities before they reach production — whether through manual peer review, automated static analysis, or a hybrid of both. It’s one of the highest-leverage controls in your security program because it catches defects at the point they’re … Read more
Bottom Line Up Front Your CI/CD pipeline is a privileged system. It holds your source code, your secrets, your deployment credentials, and a direct path to production — which makes it one of the highest-value targets in your entire environment and one of the most under-scrutinized by security teams who are busy chasing endpoint alerts. … Read more
Bottom Line Up Front Container image scanning identifies known vulnerabilities, misconfigurations, embedded secrets, and license issues in container images before they reach production — and increasingly, before they even reach your registry. If you’re shipping software in containers, this control isn’t optional; it’s the primary mechanism for catching the vulnerable base images, outdated packages, and … Read more
Bottom Line Up Front Cloud native security is the set of architectures, controls, and practices that protect applications built specifically to run in cloud environments — containers, Kubernetes, serverless functions, microservices, and the CI/CD pipelines that ship them. It’s not “cloud security” with a different label. Traditional cloud security assumes long-lived virtual machines behind a … Read more
Bottom Line Up Front Network forensics is the practice of capturing, recording, and analyzing network traffic to detect, investigate, and reconstruct security incidents. When your EDR agent flags a suspicious process, or your SIEM correlates an unusual login pattern, network forensics is what tells you where the attacker went next, what data left your environment, … Read more
