Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

How Salt Security & AWS Simplify API Security

See your Blind Spots in Minutes, not Months: How Salt Security & AWS Simplify API Security AI agents and cloud-native architectures have unleashed a wave of APIs and with them, new attack surfaces. Most security teams are struggling to keep up, especially in dynamic AWS environments where shadow and zombie APIs can easily go undetected. This Salt Security and AWS webinar explores a better approach to API discovery and security in AWS without the burden of in-line traffic collection or sensor deployments.

When Al Agents go Rogue: What you're Missing in your MCP Security

No Fluff, Just Real-World Threats This isn’t your typical marketing webinar. We cover what Agentic AI actually looks like in production, how MCP servers work to broker instructions, and what kind of new threats are emerging. Agentic AI isn’t coming. It’s already here. Autonomous agents are now operating in production environments, reasoning, remembering, and taking real actions across your systems. They’re not just generating content. They’re triggering workflows, modifying records, and making decisions. And they’re doing it over APIs.

Securing AI Agents: How to See MCP Servers and A2A Traffic with Salt Security

AI agents have moved past conversation into action. They book transactions, pull sensitive data, and chain tools together through the Model Context Protocol (MCP) and Agent-to-Agent (A2A) traffic. Every one of those actions runs on APIs, and that connective tissue is where the risk sits. Salt Security Co-Founder and CEO Roey Eliyahu and VP of Product Strategy Nick Rago walk through the risks in the agentic action layer and show what Salt does about them.

You Can't Have AI Security Without API Security: The Agentic Action Layer

AI agents run on APIs, and that is where most security programs have a gap. Salt Security Co-Founder and COO Michael Nicosia and CMO Michael Callahan explain why you cannot secure AI without securing the APIs underneath it. An AI agent uses an LLM to reason and an MCP server to broker calls out to other systems, and every one of those calls is an API interaction. Deploy one agent and the traffic multiplies. Deploy hundreds, and the internal east-west traffic climbs to several times what a pre-AI environment carried.

API Security for AI Agents: What CISOs Need to See, Govern, and Protect

AI agents are moving into every part of the business, and each one runs on APIs. Salt Security Co-Founder and COO Michael Nicosia and CMO Michael Callahan walk through what that shift means for security leaders. A single AI agent can generate thousands of API calls, and once agents start talking to each other through MCP servers and agent-to-agent protocols, the number climbs into the millions. That growth widens the attack surface and turns prompt injection into a common entry point.

Agentic AI Security: The Emerging Fourth Pillar of Cybersecurity

For decades, cybersecurity has been organized around three dominant pillars: endpoint security, network security, and cloud security. These domains have shaped technology categories, vendor ecosystems, and enterprise budgets. They have matured into multi-billion-dollar markets, each responding to successive waves of digital transformation. However, a tectonic shift is underway.

Critical vLLM Flaw Exposes the Soft Underbelly of AI Infrastructure

While the world worries about "jailbreaking" LLMs or preventing them from hallucinating, a critical new vulnerability has just reminded us of a fundamental truth: AI is just software, and software has bugs. A newly discovered critical flaw (CVE-2025-62164) in vLLM, one of the most popular libraries for serving large language models, allows attackers to achieve Remote Code Execution (RCE) or crash servers simply by sending a malicious API request. This isn't a failure of the AI model.

Securing the New AI Edge: Why Salt Security Is Bringing MCP Protection to AWS WAF

The definition of the "edge" is changing. For years, security teams have focused on the traditional perimeter: web applications, public APIs, and user interfaces. We built firewalls, deployed WAFs, and established strict access controls to keep bad actors out. But with the rapid adoption of Agentic AI, the perimeter has expanded. Today, your "edge" isn't just where users connect to your apps; it's where AI agents connect to your data.

Say Hello to Ask Pepper AI: Turning API Security into a Conversation

In the world of cybersecurity, we have a "data" problem. We have more of it than ever before, more logs, more alerts, and definitely more APIs. But recently, this challenge has compounded. The rise of Agentic AI and Model Context Protocols (MCPs) has exploded the number of machine-to-machine connections in our environments. These agents spin up new pathways and access data in ways that are often invisible to traditional monitoring.

Find the Invisible: Salt MCP Finder Technology for Proactive MCP Discovery

The conversation about AI security has shifted. For the past year, the focus has been on the model itself: poisoning data, prompt injection, and protecting intellectual property. These are critical concerns, but they miss the bigger picture of how AI is actually being operationalized in the enterprise. We are entering the era of Agentic AI. AI is no longer just generating text; it is taking action. Autonomous agents read customer tickets, query databases, update financial records, and trigger workflows.