MCP Security - Risks and Best Practices

Principaux enseignements

• MCP Architecture Is Here to Stay: MCP architecture offers AI systems increased agility and flexibility while reducing development costs. With the wider range of benefits, the MCP will become central in AI development in the future
• MCP Security is Vital: Although MCP is a powerful open-source system, it does have some inherent security risks that businesses can mitigate
• An MCP Breach Can Lead to Further Issues: A breach that stems from the MCP could lead to downstream infections, damage to your AI model, and the exposure or exfiltration of sensitive data
• Your Business Can Secure the MCP: By using leading security practices like implementing zero trust controls, isolating your systems, using automatic anomaly detection, and encrypting data, you can enhance MCP security significantly

Why MCP Adoption Is Surging

The MCP has been one of the biggest news stories in the artificial intelligence sphere since the early proliferation of this technology. Its ability to streamline the process of connecting to other enterprise applications and platforms breaks down the inherent siloed nature of AI, opening the door to a range of alternative features.

MCP adoption is surging because it offers an extensive range of benefits to companies looking to scale their AI systems and take their AI products to the next level:

• Enhanced AI Interoperability: MCP allows AI and other app ecosystems to work together without the need to lock in to one specific vendor or product system. The incredible flexibility of the MCP allows businesses to connect with tools, systems, new providers, and even cloud technologies without the need to rewrite underlying code, change their AI systems, or spend time developing new pathways
• Improved Developer Efficiency: Connecting artificial intelligence systems to external tools is often a laborious process that can take a developer a long time to set up, test, verify, and bring to market. The MCP allows businesses to expedite this process, bypassing the creation process and instantly making use of available connections to popular tools
• Expanding Number of Integrations: While the MCP already has an impressive number of available integrations, this is only the beginning for the technology. On the MCP roadmap, many more integrations are on the horizon, with the protocol aiming to consistently roll out connection pathways with central tools that enterprises use. This approach means that MCP will continue to become even more useful over time, incentivizing early adoption
• Open Source Software: As the MCP is open source, businesses can audit its code for any security vulnerabilities, making this a highly secure system with verifiable secure coding practices. The transparency of hosting open source software also encourages community-first building, with developers creating and launching integrations for free to MCP. Its open source and collaborative nature make this a fast-growing tool that is continually expanding without causing businesses additional costs
• Accelerates AI Agility: Whenever a new tool or system becomes available that offers the ability to enhance your AI product, connecting to it with the MCP expedites this process enormously. Instead of having to perform an architectural overhaul, the MCP pathway ensures you can access new technology as soon as it becomes available without any hassle

While MCP adoption has had an impressive level of adoption in a short amount of time, this is only the beginning for the technology in the AI sphere.

Key Security Risks in MCP

As an emerging field, there are a few known core attack vectors that threat actors use to interfere with and breach MCP systems. However, due to the recency of this area of cybersecurity, experts should aim to stay as up-to-date with any progression or changes as possible, as new threats could emerge rapidly.

Here are some of the known main security risks in MCP:

• Injection Attacks: Injection attacks, whether through prompt injection, malicious metadata, or context poisoning to damage connected AI systems, are all common attack vectors that MCP security defends against. MCP security will work to require user and input authentication before any model executes a command, preventing any malicious command execution that stems from code injection. Experts should be especially aware of OAuth MCP security authorization endpoints, as this is a common vulnerability
• File Exposure and Context Leakage: As MCPs are still a developing technology, many security experts do not have full visibility over connected elements, reducing their understanding of their company’s attack surface. If there are any file vulnerabilities in this system, that lack of visibility can lead to file exposure and exfiltration
• Tool Poisoning Attacks: Tool poisoning attacks are a relatively new attack vector that threat actors have created specifically for AI systems. There are a number of MCP-specific tool poisoning vectors that trick these models into executing unauthorized actions and commands.
• Credential Leakage: Another major MCP security concern stems from its misconfiguration. When MCPs are poorly structured and configured, malicious actors may be able to locate unrestricted plaintext files that include user credentials. They can use these public records to sign into accounts and gain direct access to your systems

By understanding how these vectors and attack systems work, cybersecurity teams can work to defend against them and continuously fortify their attack surface.

How to Secure MCP Servers: MCP Security Best Practices

While MCP security is still evolving and developing, it’s important to implement the current best practices to ensure your business protects itself from potential breaches that stem from this technology.

Here are some of the MCP security best practices to follow:

• Utilize Context Encryption for all Data: Data that flows through the MCP is highly valuable, as it represents both a direct pathway into AI systems and also likely contains elements of user data. Be sure to use industry-standard encryption for all data that flows through the MCP and data at rest. Any information that could be valuable or falls in line with data privacy compliance initiatives must be encrypted
• Automatically Identify Anomalies: There are several cybersecurity systems, both AI-driven and less comprehensive, that are able to monitor your security posture to detect any potential anomalies and trigger a response. Your business should endeavor to flag any unusual behaviors or patterns, especially those that contain strange context, as this is a typical threat vector for MCP environments
• Isolate Systems Where Possible: As you would in cloud environments and network systems, it’s useful to segment your AI architecture to prevent an MCP breach from infecting the rest of your system. If you isolate each MCP component from any unrelated services, then you are able to minimize the scope of any breaches
• Implement Zero Trust Controls: Zero trust security involves using verification and authentication systems to ensure only those that can actively prove their identity can access your systems. If any account has permission to interact with MCP architecture, you should ensure that the privilege hierarchy of your company limits their account’s ability to move laterally and abides by zero trust policies
• Keep an MCP Event Log: Another important security practice to follow is ensuring you have enough visibility over the MCP that you can generate logs of all the data and interactions that move through or occur within your system. If you’re able to create these logs, then it’s much easier to audit your own records, identify anomalies, and streamline security compliance. Doing this as early as possible will also help you get ahead of any open source security framework regulations that you may need to follow in the future
• Use OS-Level Controls: Where possible, apply OS-level controls to your profiles, like Windows Defender Application Control or kernel-level syscall monitoring, to prevent access by unauthorized parties, identify any anomalies as early as possible, enforce best practices, and maintain security controls at the OS level

By adopting these MCP security best practices, your business can scale its AI software and make use of this technology without worrying about the potential security risks.