COMMENTARY: It has been said enough times that AI is changing the speed and scale of security work, or that AI has completely changed the scale of it. Attackers are moving much faster with AI, and so are vulnerability discovery, exploit development, identity abuse, and automated probing. The reality is that enterprises can't catch up. Customer environments are still built around slower patch cycles, weak identity controls, and limited visibility. And they need help with figuring out where AI agents are running, what access they have, how quickly vulnerabilities can be contained, and whether their current detection and response model can keep up. The MSSPs and MSPs can turn this into a practical roadmap around identity, patching, XDR, and incident response - this will also help them to better position themselves than those treating AI as just another tool discussion.
Claude Mythos, Anthropic’s latest frontier model, has become the centerpiece of a new debate over AI safety and the risks tied to its development. Unlike its predecessors, Mythos isn’t being marketed as a faster chatbot or a better creative writing assistant. Instead, it’s being described as a high-autonomy engine capable of discovering and exploiting thousands of high-severity software vulnerabilities – some of which have remained hidden in major operating systems for decades.For managed service providers (MSPs), the Claude Mythos narrative isn’t just another product launch to track. It represents a fundamental shift in the agentic era, as AI moves from a static tool to a persistent, autonomous actor. This transition introduces a new layer of systemic risk for customers that traditional security models weren’t designed to handle.
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Beyond the hype: What Mythos actually signals
While the general public is currently restricted from accessing Mythos through Anthropic’s Project Glasswing initiative, the model’s capabilities offer a glimpse into the near future of cyber defense. In pre-release testing, Mythos autonomously identified a 27-year-old bug in OpenBSD and successfully exploited vulnerabilities in modern web browsers.For MSPs, the takeaway is clear: The window between vulnerability discovery and exploit development is narrowing. If an AI agent can take a CVE identifier and produce a working exploit in hours at negligible cost, the traditional patch Tuesday cycle is effectively dead. We’re moving toward a world where your customers’ infrastructures will be under constant, automated probing by agentic AI systems that never sleep.Navigating the visibility and liability gap
As customers begin to ask about agentic AI and autonomous workflows, MSPs must transition from productivity facilitators to strategic architects of resilience. This shift introduces three specific security challenges you’ll need to address in your advisory sessions:The visibility gap: Autonomous agents don’t cleanly map to existing identity categories. Is the agent a user, a service account, or an application? Existing monitoring tools often struggle to attribute activity and enforce policies for agents interacting with a customer’s API.The compressed attack timeline: When an adversary exploits an agent framework, reconnaissance and lateral movement occur at machine speed. The dwell time we relied on to catch an intruder is disappearing.The identity crisis: Attackers are moving away from simple smash-and-grab tactics toward sophisticated identity-focused strategies designed to bypass traditional defenses.Expanding threat landscape: As agentic AI scales, so does the attack surface. Always-on autonomous systems enable continuous, automated probing at a volume humans can’t match. Barracuda’s recent Mythos Hype Index, published in early June, projects 77k CVEs in 2026, up from 49k in 2025, underscoring how threat velocity and volume are outpacing traditional detection and response models.Proactive strategies for the MSP roadmap
To support safe, accountable AI adoption without increasing your operational or liability risk, your security stack must evolve alongside these models. Barracuda’s research into the automation risks demonstrated by Mythos highlights the importance of identity security, patching and incident response as the highest-impact priorities.- Implement kill-switch capabilities: Any agentic system deployed in a customer environment should include hard-coded constraints. If an agent exhibits anomalous behavior, such as attempting to connect to untrusted external networks, it must be automatically quarantined.
- Shorten patch windows: If your vulnerability management cadence was designed for a world where exploit development took weeks, it needs to be reevaluated. Move toward automation and pre-approve mitigation steps, such as blocking public access, so your team has options during patch testing.
- Enforce phishing-resistant MFA: In an era when AI-driven kits can bypass traditional defenses in milliseconds, standard SMS or push notifications are no longer sufficient. Implementing FIDO2 security keys or biometric authentication is becoming an operational requirement.
- Leverage managed XDR: The sheer volume and velocity of AI-driven attacks demand an automated, multilayered response. By combining real-time threat intelligence with a 24/7/365 SOC, MSPs can bridge the gap between detection and remediation.
