Expert perspectives on application security, compliance, and emerging threats
GuidesAI is already writing code in your environment. The real question is: who verifies it when your junior developer uses Copilot, your contractor deploys Claude-generated infrastructure scripts, or your
GuidesYour AI infrastructure likely uses RSA-2048 or ECDSA P-256 for authentication and encryption. Both will become vulnerable when large-scale quantum computers arrive. The timeline is uncertain, but the
GuidesLast week, three different Slack threads raised similar concerns. A developer questioned if ChatGPT was a sanctioned tool. An engineer wondered if copying code into Claude breached data handling polic
GuidesThe Problem Your open-source dependencies are maintained by volunteers who now spend 12 times longer reviewing AI-generated pull requests than it takes to generate them. That s not a productivity gain
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GuidesThe question at hand Your organization relies on thousands of API keys, service accounts, OAuth tokens, and machine credentials. Every CI/CD pipeline, microservice, and monitoring agent needs credenti
GuidesYou re running penetration tests quarterly, but your developers ship code daily. That gap is where vulnerabilities live. Continuous offensive security (COS) uses recurring and event-driven testing to
GuidesIf your organization is deploying AI models through APIs, you re managing two attack surfaces: the AI model itself and the API layer that exposes it. While most teams focus on model security, their AP
GuidesYou ve got an AI agent writing production code. It passes the linter and looks clean. Then it ships a dependency that phones home to an expired domain, or it refactors an authentication check into a d
GuidesThe Question at Hand Your security team is evaluating AI agents for threat detection, incident response, or vulnerability analysis. The vendor pitch sounds promising, but here s what they won t tell y
GuidesYou re running quarterly pen tests, patching critical CVEs within 30 days, and checking the compliance boxes. Then you discover a vulnerability that s already being exploited in production. The pen te
GuidesIf you re building or deploying AI agents that access production systems, you need an identity governance policy that works at agent speed. Traditional access control policies assume you re managing h
GuidesYour Kubernetes cluster is running inference endpoints that make thousands of external API calls per minute. Your AI agents are spinning up containers to execute code they generated. Your security pol
GuidesYour pentest vendor sends a 47-page PDF. Your team triages it into Jira tickets. Developers ask clarifying questions via Slack. The vendor responds three days later via email. By the time you verify t
GuidesYour team adopted Burp Suite six months ago to enhance your web application security testing as part of your SOC 2 Type II preparation. Yet, your scans keep missing SQL injection vulnerabilities that
GuidesYour CI/CD pipeline is the most privileged account in your infrastructure. It deploys to production, accesses secrets, and runs on every commit. Yet, many security policies treat it like any other sys
GuidesYour developers are already using AI coding assistants. Some of these assistants connect to external servers through Model Context Protocol (MCP). You likely have no visibility into which servers they
