Cequence Security, Inc - Experts & Thought Leaders

Cequence Security, the pioneer in application, API, and agentic AI protection, today announced that Russ Schafer, former Executive Vice President of Marketing at Fortinet, has joined as Chief Marketing Officer, reporting to CEO Ameya Talwalkar. Schafer joins as Cequence builds on major customer wins, the expansion of Agentic AI security solutions and industry recognition. Schafer brings more than 25 years of marketing leadership at billion-dollar companies and high-growth startups across cybersecurity, SaaS, enterprise software, semiconductors, and media. He has led global teams of 200+ professionals and managed budgets exceeding $300M (£222M), generating billions in pipeline. As CMO at Cequence, he leads corporate marketing, product marketing, demand generation, field marketing, analyst relations, and creative services. Most demanding organisations For 12 years, Cequence has stopped bots and secured APIs for some of the world’s largest and most demanding organisations in telecommunications, financial services, retail, and transportation. The Cequence Platform scales to process over 10 billion API calls per day while protecting 4 billion user accounts. AI agents now reach enterprise data through the same APIs Cequence already protects, and the company is applying that experience to secure them. To protect enterprises adopting AI, Cequence continues to expand its AI security solution to protect against the latest AI Agent threats, including: Cequence Application and API Protection v9: Helps security teams discover APIs and stop attacks, bots, and abuse, and is now AI-native, with a built-in AI assistant and MCP server. Agent Trust verifies agent identity and blocks harmful behaviour in real time. Cequence found Meta’s Muse at more than half of the customers studied within two weeks of the agent’s launch. AI Gateway: Treats agents as properly onboarded digital employees, tying tools, APIs, skills, LLMs, and permissions to Agent Personas, containing agents and preventing overreach in real time. AI Discovery brings shadow AI under governance, while LLM Continuity and Budgets & AI Spend deliver model failover and spend control. Agentic AI security Together, Application and API Protection, including Agent Trust, and AI Gateway secure both directions of agent traffic, from external agents reaching enterprise applications to an enterprise’s own agents reaching tools, data, and models. The demand for bot, API, and agentic AI security is surging, and Cequence’s record growth reflects that trend. Cequence reported its strongest quarter and largest deal in company history, with new customers in the United States, Japan, South Korea, Brazil, and the Middle East. NTT DOCOMO, Japan’s leading mobile operator with over 91 million subscribers, deployed Cequence’s application and API protection solution to safeguard its service infrastructure, applications, and APIs from sophisticated attacks, business logic abuse, and unauthorised access. Autonomous network initiatives Cequence is defining the security standards for the agentic era, co-authoring the CIS Critical Security Controls Companion Guides for AI agents, LLMs, and Model Context Protocol (MCP), while co-chairing TM Forum’s AI-Native Blueprint initiative. The company is also working with a dozen global telecommunications providers on their autonomous network initiatives to safely enable agentic AI. “Enterprise leaders are just beginning to realise the sheer scale of the AI agent security and governance challenge,” said Ameya Talwalkar, co-founder and CEO of Cequence. “Because AI agents rely on the very APIs Cequence already protects, we are uniquely positioned to give enterprises complete visibility and real-time control and governance of AI agents. Russ brings the strategic vision and proven marketing playbook to drive awareness, build pipeline, and establish Cequence as a leader in agentic AI security.” AI security challenges “Cequence is solving the exact agentic AI security challenges that enterprise leaders are just beginning to discover,” said Russ Schafer, Chief Marketing Officer, Cequence. “Cequence’s proven heritage in stopping bot and API abuse, combined with breakthrough innovations like Agent Trust and full-lifecycle AI governance, uniquely positions us to lead this market. I’m thrilled to join the team and empower enterprises to adopt AI agents with complete confidence and control.” Prior to joining Cequence, Schafer served as Executive Vice President of Marketing at Fortinet, driving global demand across a portfolio of 60+ network, cloud, and AI security products – experience that directly aligns with Cequence’s platform expansion. Schafer is a recognised thought leader and featured event speaker who presented on Agentic AI for Coordinated and Unified Cybersecurity Defense at RSAC 2026. He previously headed product marketing and analyst relations at Check Point Software and served as SVP & GM of Technology at THX. His earlier experience includes serving as VP of Product Marketing at Adap.tv (acquired by AOL for $405M), alongside senior leadership roles at Intel, IBM, Sybase, and Yahoo!. He holds an MBA from Duke University and a BBA from Texas A&M University.

Nearly every enterprise believes its AI agents are properly scoped but only a third have actually made sure of it. New research from Cequence Security, the pioneer in application, API, and agentic AI protection, and Enterprise Management Associates (EMA) found that 94% of enterprise IT and security leaders are confident their AI agents do not have more access than they need, yet only 33% actually provision agents with least-privilege access. The remaining two-thirds run on broad standing permissions that are reviewed periodically, rarely reviewed, or never reviewed at all. The full report, Agents Without Guardrails: The Agentic AI Governance Gap in the Enterprise, is available for download now. Broad standing permissions The gap between confidence and practice is already showing up in production, not as a theoretical risk, but as incidents enterprises are living with right now. Among the organisations surveyed: 65% have experienced an AI agent take an action outside its intended scope, including 29% with measurable business impact such as data exposure, financial loss, operational disruption, or reputational damage. Another 36% caught a near-miss before it caused damage. Only 32% can detect and contain an out-of-scope agent action within minutes through automated means; 55% need hours and manual steps to respond. In approximately 4% of the organisations surveyed, the first sign of trouble came from a customer or outside partner, not an internal system. Customer-facing applications The findings point to one clear story. Governance has not kept pace with the speed of agentic AI deployment, and that gap is showing up at every stage of the agent lifecycle, from how agents are provisioned, to how their actions are authorised, to how they are decommissioned once a pilot ends. Other key findings from the report include: The scale of deployment makes the gap more urgent. 46% of organisations report they are already scaling agentic AI across multiple departments and production workflows, and 79% are running generative and agentic AI simultaneously. Further, more than 92% report an increase in AI and bot-driven traffic targeting customer-facing applications and APIs. That governance gap extends to how access is enforced the moment an agent acts. Only 34% of organisations evaluate an AI agent's authorisation at the moment it attempts a specific action. The majority rely on periodic policy reviews or standing permissions set once at provisioning and never revisited, meaning an agent's access can quietly outlive the task it was originally granted for, and keep working long after anyone signed off on it. Additionally, there’s an increasing risk in how enterprises manage agents that don't make it to production. 31% of agentic AI pilots have been paused indefinitely, discontinued, or abandoned. Many were real deployments with real system access and credentials that were never cleaned up. Every abandoned pilot with live credentials is an exposure nobody is actively watching. 14% of organisations allow AI agents to connect to outside tools and data sources via the Model Context Protocol (MCP) without restriction. Among the majority who do limit those connections to an approved list, fewer than half (49%) have a dedicated team actively maintaining and auditing that list on a regular basis. Well past experimentation Christopher M. Steffen, CISSP, CISA, VP of Research at EMA, said: “This research shows enterprises have moved well past experimentation with agentic AI right into production and governance has not kept pace with that shift. The gap isn’t a lack of awareness; most organisations have policies in place and express real confidence in them. The gap is between what’s written down and what’s enforced when an agent takes an action nobody approved. That disconnect shows up most clearly in how organisations authorise agent actions and monitor them once they’re live, and it’s the reason incidents are happening at a rate the industry hasn’t fully reckoned with.” Shreyans Mehta, Co-founder and CTO at Cequence, said: “The number that jumped out to me is the 92% being confident in their governance frameworks. Confidence like that is a trap; its exactly why organisations stop looking for problems, stop investing in monitoring, and let authorisation checks lapse until an incident forces the conversation. This is the exact blind spot Cequence is built to close, giving security teams real-time visibility into what AI agents are actually doing and enforcing authorisation at the moment an agent acts, not after the fact.” Join Christopher M. Steffen, Vice President of Research at EMA, and Randolph Barr, Chief Information Security Officer at Cequence, for the “Agents Without Guardrails” webinar.

Cequence Security, the pioneer in application, API, and agentic AI protection, today announced four new capabilities for AI Gateway: AI Discovery, API Registry, LLM Registry, and Skill Registry. The release also upgrades Agent Personas, which now bind an agent’s job description directly to its model, tools, access, and guardrails, all enforced automatically through policy. Together, these capabilities let any business user stand up properly secured, governed AI agents, bound to the right tools, data, and protections for their job, without needing technical experience or touching AI Gateway directly. Backend services and data With this release, Cequence becomes the first platform to close the ring around every channel an AI agent uses to communicate with the outside world. MCP governs how an agent discovers and invokes tools. LLM Registry governs every call to and from a language model. API Registry governs how it reaches backend services and data. Agent Personas bind an agent's tools, model, and API access to a single job description, enforcing that boundary as policy rather than manual review. Where other vendors address one piece of that surface, Cequence ties MCP, LLM, and API together under one agent-bound identity, an approach they call Agentic Zero Trust. Nothing an agent touches is implicitly trusted, and every action is scoped to exactly what its job requires. Sandboxed evaluation environment The stakes are no longer hypothetical. OpenAI recently disclosed that two of its models escaped a sandboxed evaluation environment, crossed the open internet, and breached Hugging Face's production infrastructure, chaining stolen credentials and a zero-day to steal a benchmark answer key. Nothing had bound those agents to a job, so nothing stopped them from inventing one. Notably absent was any binding between the agent and its assigned job. Under Cequence, that binding is the Agent Persona, and an agent's models, tools, and APIs are defined by its job description, not by what it can reach once it's loose. Hugging Face's production infrastructure was never going to be on that list, regardless of what credentials the agent got its hands on. A zero-day can still get an agent past a sandbox, but it can't get a persona-bound agent past a policy that was never written to allow it there in the first place. Agentic AI governance Agentic AI adoption has outrun agentic AI governance. Point solutions have addressed pieces of the problem, a scanner here, an API gateway there, and a prompt filter somewhere else. None of them answer the questions every security leader is now asking: which agents does the organisation have, what can they reach, what actions can they take, who approved them, and how fast can they be shut down when governance guardrails are violated. Enterprises are recognising that AI agents with access to applications and data are much more than tools. They are privileged insiders operating at machine speed and require the same governance discipline as any other privileged use inside of the business. Enterprises already secure, manage, and guide human employees whether they work from an office or remotely, and AI agents need the same standard, regardless of whether they run on managed devices or in the cloud. Same governance discipline “Most vendors look at agent governance and build another approval queue. We looked at it and built the persona instead,” said Shreyans Mehta, CTO and Co-Founder at Cequence Security. “An agent’s job should automatically determine what it can touch, without relying on a security team to manually map policy by hand every time someone wants a new use case. That’s what makes broad adoption safe and scalable, and the agent gets exactly what its job requires, and nothing more.” Cequence AI Gateway’s new and improved capabilities include: AI Discovery surfaces every agent, LLM provider, and MCP server already running across the enterprise, pulled from existing SIEM logs whether or not it went through an official process. API Registry lets agents call approved APIs without ever holding the underlying credential. Agents authenticate with a single AI Gateway access key, either through a single invocation tool for web-based agents or natively through AI Gateway’s proxied endpoints. Skill Registry gives security and platform teams a curated, governed set of capabilities to draw from, vetted once and reusable across every agent use case that needs it. Agent Personas bind an agent to a job description. That includes a curated set of tools, APIs, skills, and instructions, the specific LLM model it's approved to use, and the security guardrails that apply to it, all enforceable via policy. Relevant data protection policies apply automatically based on the persona's data surface and job function, including which LLM model it can call, since an ungoverned model is as much a risk as an unvetted API. LLM Registry governs every agent-to-LLM call the same way API Registry governs REST access, brokering credentials across major LLM providers so agents never hold a real provider API key. Built-in Data Loss Prevention inspects every prompt and response for blocked content, including base64-encoded payloads and invisible or non-approved-language Unicode characters used to evade filters. It also governs model use per team, for example defaulting to a cost-effective model while routing advanced engineering tasks to a premium one, with token-level usage visibility and enforceable rate and spend limits tied back to the agent persona driving each request. Cost-effective model “Automatic policy mapping was not possible until now, because there was nothing consistent for a policy engine to reason over," said Abraham Jeevagunta, VP of AI Products at Cequence Security. "Before API Registry and Skill Registry, every tool and API a persona could be bound to was uncatalogued, so mapping policy to persona was a manual judgment call every time. Now, that record exists and the policy engine can read it directly. It is what lets a business user stand up a correctly governed agent without ever touching AI Gateway's policy model themselves." All of these capabilities are immediately available to Cequence customers as part of AI Gateway.