The dialog round AI and its enterprise purposes has quickly shifted focus to AI brokers—autonomous AI methods that aren’t solely able to conversing, but in addition reasoning, planning, and executing autonomous actions.
Our Cisco AI Readiness Index 2025 underscores this pleasure, as 83% of corporations surveyed already intend to develop or deploy AI brokers throughout a wide range of use instances. On the identical time, these companies are clear about their sensible challenges: infrastructure limitations, workforce planning gaps, and naturally, safety.
At a cut-off date the place many safety groups are nonetheless contending with AI safety at a excessive degree, brokers develop the AI danger floor even additional. In spite of everything, a chatbot can say one thing dangerous, however an AI agent can do one thing dangerous.
We launched Cisco AI Protection firstly of this yr as our reply to AI danger—a very complete safety answer for the event and deployment of enterprise AI purposes. As this danger floor grows, we need to spotlight how AI Protection has developed to satisfy these challenges head-on with AI provide chain scanning and purpose-built runtime protections for AI brokers.
Under, we’ll share actual examples of AI provide chain and agent vulnerabilities, unpack their potential implications for enterprise purposes, and share how AI Protection allows companies to immediately mitigate these dangers.
Figuring out vulnerabilities in your AI provide chain
Trendy AI improvement depends on a myriad of third-party and open-source parts resembling fashions and datasets. With the appearance of AI brokers, that record has grown to incorporate property like MCP servers, instruments, and extra.
Whereas they make AI improvement extra accessible and environment friendly than ever, third-party AI property introduce danger. A compromised part within the provide chain successfully undermines your entire system, creating alternatives for code execution, delicate information exfiltration, and different insecure outcomes.
This isn’t simply theoretical, both. Just a few months in the past, researchers at Koi Safety recognized the primary recognized malicious MCP server within the wild. This bundle, which had already garnered hundreds of downloads, included malicious code to discreetly BCC an unsanctioned third-party on each single e-mail. Comparable malicious inclusions have been present in open-source fashions, instrument recordsdata, and numerous different AI property.
Cisco AI Protection will immediately tackle AI provide chain danger by scanning mannequin recordsdata and MCP servers in enterprise repositories to determine and flag potential vulnerabilities.
By surfacing potential points like mannequin manipulation, arbitrary code execution, information exfiltration, and gear compromise, our answer helps forestall AI builders from constructing with insecure parts. By integrating provide chain scanning tightly inside the improvement lifecycle, companies can construct and deploy AI purposes on a dependable and safe basis.
Safeguarding AI brokers with purpose-built protections
A manufacturing AI software is inclined to any variety of explicitly malicious assaults or unintentionally dangerous outcomes—immediate injections, information leakage, toxicity, denial of service, and extra.
After we launched Cisco AI Protection, our runtime safety guardrails had been particularly designed to guard towards these eventualities. Bi-directional inspection and filtering prevented dangerous content material from each consumer prompts and mannequin responses, retaining interactions with enterprise AI purposes protected and safe.
With agentic AI and the introduction of multi-agent methods, there are new vectors to contemplate: better entry to delicate information, autonomous decision-making, and complicated interactions between human customers, brokers, and instruments.
To satisfy this rising danger, Cisco AI Protection has developed with purpose-built runtime safety for brokers. AI Protection will perform as a kind of MCP gateway, intercepting calls between an agent and MCP server to fight new threats like instrument compromise.
Let’s drill into an instance to raised perceive it. Think about a instrument which brokers leverage to go looking and summarize content material on the internet. One of many web sites searched incorporates discreet directions to hijack the AI, a well-recognized state of affairs often called an “oblique immediate injection.”
With easy AI chatbots, oblique immediate injections may unfold misinformation, elicit a dangerous response, or distribute a phishing hyperlink. With brokers, the potential grows—the immediate may instruct the AI to steal delicate information, distribute malicious emails, or hijack a linked instrument.
Cisco AI Protection will shield these agentic interactions on two fronts. Our beforehand current AI guardrails will monitor interactions between the applying and mannequin, simply as they’ve since day one. Our new, purpose-built agentic guardrails will study interactions between the mannequin and MCP server to make sure that these too are protected and safe.
Our purpose with these new capabilities is unchanged—we need to allow companies to deploy and innovate with AI confidently and with out worry. Cisco stays on the forefront of AI safety analysis, collaborating with AI requirements our bodies, main enterprises, and even partnering with Hugging Face to scan each public file uploaded to the world’s largest AI repository. Combining this experience with many years of Cisco’s networking management, AI Protection delivers an AI safety answer that’s complete and executed at a community degree.
For these focused on MCP safety, try an open-source model of our MCP Scanner that you would be able to get began with as we speak. Enterprises in search of a extra complete answer to handle their AI and agentic safety considerations ought to schedule time with an knowledgeable from our group.
Lots of the merchandise and options described herein stay in various levels of improvement and might be supplied on a when-and-if-available foundation.
