Why MCP Breaks the Financial Services Security Stack

A relationship manager asks the firm's AI assistant to "summarize my top wealth clients by AUM and flag anyone with a pending transfer over $500K." The agent calls a CRM MCP server, then a core banking MCP server, then a market data MCP server, and returns a clean answer in twelve seconds. Names, balances, account numbers, pending wire details, all rendered in plain text inside the chat window. No file moved. No email left the network. No DLP channel triggered.

What Is Third-Party Risk Management (TPRM)?

Your security team has hardened your perimeter. You have MFA enforced, endpoint detection running, and your crown-jewel systems are locked down tight. Then a vendor you onboarded two years ago, a mid-size SaaS tool your procurement team signed off on, gets breached. They had access to your customer data. Now it is your problem. This is the third-party risk problem in one paragraph. And it is why TPRM has moved from a compliance checkbox to a board-level conversation.

Exposure vs Vulnerability Management: Is There Actually a Difference?

In this exclusive fireside chat, Seemplicity CPO Ravid Circus and SANS instructor Jonathan Risto break down this critical distinction and why mastering it is vital as AI rapidly reshapes the cybersecurity threat landscape. Here’s a summary of what they covered. If you’ve been in security for any length of time, you’ve probably wondered whether exposure management is just vulnerability management with a fresh coat of paint.

How to detect HTTP/2 abuse in Apache web server logs

Apache HTTP Server is one of the most popular web servers in use today for engineering teams, and its prevalence naturally makes it a frequent target for attackers. In May 2026, the Apache Software Foundation patched CVE-2026-23918, a high-severity double-free vulnerability in Apache 2.4.66’s mod_http2 module. For teams not using Apache’s MPM prefork, the vulnerability would enable an attacker to crash worker processes or achieve remote code execution (RCE) in some specific cases.

Practical MCP Security: A Playbook for Mid-Market Teams

Most guidance published on AI agent security is written for enterprise organizations. It assumes dedicated AI security functions, red teams, platform engineering groups, and the budget to commission purpose-built tooling. If your security team is three people covering five hundred employees and a cloud environment that grows faster than you can document it, that guidance was not written for you. The five posts in this series have established the threat landscape.

Defending Against the Next Generation of Agentic Attacks

The attack lifecycle is compressing. Frontier AI models like Anthropic’s Mythos and OpenAI’s GPT-5.5-Cyber can help bad actors research vulnerabilities, test approaches, adapt code, and change delivery methods at machine speed and scale. That reduces the time, skill, and coordination needed to move from vulnerability discovery to active attack. When attacks behave this way, security needs to operate in real time with full visibility and context across the attack path.

OpenAI Privacy Filter Isn't Enough: The Truth About AI Tokenization

While the new OpenAI privacy filter detects basic PII, true data protection requires a much deeper system. In this video, we expose the hidden security vulnerabilities inside modern AI workflows and explain why aggressive data redaction actually destroys your model's utility. What you will discover in this breakdown: The Redaction Trap: Why simply deleting sensitive data breaks your AI's contextual understanding.