Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

MCP security is non-negotiable for AI-driven organizations

Model Context Protocol (MCP) is gaining traction because it enables LLMs to interact with live systems and enhance context by retrieving and managing relevant real-time information. LLMs can’t query Salesforce, trigger an Okta password reset, or fetch context from your SIEM, for example. MCP bridges that gap by connecting AI models to real-world APIs, powering AI applications like retrieval-augmented generation and multi-step agent workflows. They’re fast to deploy.

Beyond the Prompt: Securing the "Brain" of Your AI Agents

Imagine an autonomous AI agent tasked with a simple job: generating a weekly sales report. It does this reliably every Monday. But one week, it doesn't just create the report. It also queries the customer database, exports every single record, and sends the file to an unknown external server. Your firewalls saw nothing wrong. Your API gateway logged a series of seemingly valid calls. So, what happened? The agent wasn't hacked. Its mind was changed.

IBM 2025 Cost of a Data Breach Report: Lessons for API and AI Security

IBM’s 2025 Cost of a Data Breach Report offers one of the clearest and most comprehensive views yet of how AI adoption is shaping the security landscape. While breach numbers are relatively low – only 13% of organizations reported breaches involving AI models or applications – the report reveals a troubling pattern: APIs and integrations are often the real entry point, and they’re frequently under-secured. At Wallarm, we’ve been banging this drum for a while.

The Role of AI Custom Solutions in Modern Financial Services

AI has been hard at work redefining the limits of what can be done in almost every industry, but in finance, the stakes and the payoff are especially high. Algorithms are used to make decisions that used to be made by experienced analysts, such as in fraud detection and portfolio optimization. However, the distinction between merely applying AI and actually taking advantage of it is sometimes as simple as a single factor - customization.

Introducing the Riscosity AI Firewall

AI is moving through enterprises faster than security teams can track. Over the past year, AI privacy incidents have risen 56%, and most of those stem from tools security never knew were in use. 84% of SaaS tools are purchased outside IT, and 62% of CISOs say fewer than a quarter of AI tools in use have been approved through procurement. That means sensitive, regulated, or confidential data is often flowing to AI services invisibly, sometimes across borders, without governance or guardrails.

Securing LLM Superpowers: Navigating the Wild West of MCP

The Model Context Protocol (MCP) is a standardized framework that enables large language models (LLMs) to interact with external tools, APIs, and data sources. While MCP offers powerful integration capabilities across software development, data analysis, automation, and security operations, it also introduces serious security risks. This post provides a technical overview of how MCP works, its architecture, and real-world use cases.

Automate Repetitive Work With No-Code AI Agent Builder

Egnyte AI agents are smart, task-specific AI assistants built to automate repetitive, time-consuming work, so that your team can stay focused on high-impact and strategic tasks. From reviewing documents to researching topics or translating content, these agents act like always-on digital coworkers who execute task-specific instructions while securely leveraging information contained in your private documents and on the web.

The Unopinionated AI Advantage

Most AI security solutions lock you into their way of doing things. The result? You can't differentiate, you can't innovate, and you can't build the solutions your organization actually needs. LimaCharlie's approach to AI is fundamentally different. Instead of forcing you into rigid workflows, we give you the building blocks to create exactly what your environment demands. Why this matters: The result: Security teams that build custom AI solutions perfectly tailored to their environment, their workflows, and their unique challenges.