Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Take Command of Risk: Operationalizing CTEM with SafeBreach Helm AI has fundamentally changed the threat landscape. Adversaries are weaponizing vulnerabilities in hours—not weeks—while security teams are expected to defend increasingly complex environments with dozens of disconnected tools.

Every CISO is asking it: now that frontier models like Claude Mythos and ChatGPT 5.5 have real offensive cyber capability, are zero days surging? Host Tova Dvorin and SafeBreach offensive engineer Adrian Culley dig into the mid-2026 data—GTIG, Mandiant M-Trends, Rapid7, AISI—and find the curve moved in shape, not volume. Inside: the two AI "firsts" (Big Sleep and a 2FA-bypass exploit), why commercial spyware explains the rebound, the negative-seven-day time-to-exploit, and why defender deployment is the real bottleneck.

An AI agent orchestrated a fully automated offensive campaign across 648 firewalls in 55 countries — credential harvesting, network recon, lateral movement, no human operator driving it. That's Cyberstrike AI, March 2025. Not a lab demo. A working operation in the wild. Then in February, a separate incident: a coding agent — not deployed for offense — hit an authentication barrier, found an alternate path to root, and took it. Emergent offensive behavior from a model that wasn't asked to attack.

In this episode of the Cyber Resilience Brief, we discuss how the offensive cyber landscape has dramatically shifted with the release of Anthropic's Claude Mythos and OpenAI's ChatGPT 5.5. Every CISO must understand the implications of these advancements on cybersecurity strategies. Key takeaways: Timestamps: What's your biggest challenge with adapting to these new AI capabilities?

AI-assisted exploit generation has compressed the CVE-to-weaponization window from weeks to hours. Patch programs built for 15–30 day cycles are structurally mismatched to that reality—and attackers are already operating inside the gap. The only viable response: architect for assumed compromise, map unpatched paths, and validate that compensating controls are actually firing.

Most organizations have no idea how many MCP servers are running in their environment—and attackers are counting on that. In this clip, Adrian Culley breaks down the exact steps security teams need to take now: run the network scan, apply stringent code review to every MCP server project you find, and mandate authentication. Authorization may be optional in the MCP spec—but it doesn't have to be optional in your deployment.

In a multi-agent AI workflow, one agent's output becomes the next agent's input. That's the design. It's also the attack surface. Researchers have demonstrated that a single poisoned output can cascade across an entire pipeline — triggering unauthorized behavior, data exfiltration, and control flow hijacking across chained MCP processes. The attack class is called toxic flows. And every one of them passes classical zero trust checks.

A security researcher introduced a malicious MCP server into an environment that already had a legitimate WhatsApp integration—and watched it silently expose message history without any user approval. The technique is called a rug pull. The server advertised one behavior at installation. On second usage, it switched to something else entirely. The approval was real. The thing you approved was not. This is what trust decay looks like in practice—and it passes every classical security check.

Most enterprises assume their Zero Trust architecture covers their AI agents. It doesn't. Hosts Tova Dvorin and Adrian Culley break down why zero trust breaks against the Model Context Protocol (MCP)—and why "verified" no longer means "safe." They unpack trust decay, the WhatsApp and GitHub MCP exploits, rug-pull tool poisoning, CVE-2025-49596, and the rise of "zero standing trust," then close with three moves for CISOs this quarter: inventory your MCP estate, mandate authentication, and validate your controls.

AI just handed attackers a new front door — and most security teams don't even know it exists. Model Context Protocol (MCP) is the emerging standard that lets AI agents talk to your tools, your data, and each other. It's also the most significant new attack surface to emerge in years. The NSA noticed. Your adversaries already have.