Autonomous AI agents are being deployed across enterprise environments faster than security teams can track them. Omdia’s latest “On the Radar” report calls out Rein Security for tackling the problem nobody else has fully solved: what your AI agents are actually doing at runtime.
Agentic AI has changed the threat surface in ways that most security tools weren’t designed to handle. An AI agent isn’t a static piece of software sitting in a repository – it’s autonomous, it acts, it calls APIs, accesses databases, executes code, and does all of it based on inputs that are, by nature, unpredictable. When something goes wrong, traditional security tools often can’t tell you what happened, because they never had visibility into the execution in the first place.
That’s the gap Rein Security was built to close. And in January 2026, independent analyst firm Omdia took notice – publishing an “On the Radar” report by Chief Cybersecurity Analyst Rik Turner that puts Rein’s runtime context approach in the spotlight.
Why Agentic AI Is a Security Problem Most Tools Can’t See
The Omdia report traces the evolution of application security through waves of acceleration: Agile development, open-source component reuse, cloud infrastructure, and now AI. Each wave brought speed – and new blind spots.
Agentic AI is the latest and most complex of these. The report is direct about the risk: a badly configured or compromised agent introduces a new type of threat into the environment. Agents can be granted broad access by design – that’s what makes them useful – and that same access becomes dangerous when behavior goes off-script.
Then there’s Model Context Protocol (MCP). MCP servers give agents real-time access to local files, web APIs, databases, and development tools, including resources the organization deploying them doesn’t fully control. The combination of autonomous action, broad access, and external connectivity creates an attack surface that looks nothing like traditional application risk.
Most security tools respond to this by monitoring incoming prompts. That’s a start, but it’s a narrow view. It tells you what an agent was asked to do. It doesn’t tell you what it actually did.
What Rein Sees That Other Platforms Miss
Rein’s architecture is fundamentally different from EDR tools, eBPF-based platforms, and ASPM solutions. Rather than operating as an external process or observing at the kernel level, Rein deploys as a library — a dependency that runs as part of the application’s own execution process. That means it sees everything: every function called, every API invoked, every resource accessed, in real time.
For agentic AI environments specifically, this matters enormously. The Omdia report highlights that Rein can baseline and understand the two most critical dimensions in the non-deterministic world ushered in by AI: not just what a prompt looks like, but who performed the action and what its actual impact was. It knows which resources were accessed and by whom – giving security teams the context they need to distinguish expected agent behavior from a genuine threat.
Rein can also block internal MCP servers from accessing external resources they shouldn’t be reaching. That’s active enforcement, not just observation.
The Library Approach: No Agents, No Configuration, Full Context
The platform requires no agent deployment, no configuration, and no SDK. The Rein library is added at the build phase of an application’s lifecycle – via CI/CD pipeline, a package delivery framework, or the base build package – and immediately begins providing visibility that external tools can’t replicate.
Once running, it discovers all APIs in the environment (including shadow and zombie APIs that network-level monitoring misses), tracks all asset usage, inspects every HTTP request and identifies the code behind it, and determines precisely which libraries are reachable versus dormant. For agentic applications — where code paths shift based on live inputs – that real-time reachability picture is the difference between meaningful security and noise.
Teams can start in observe mode to build confidence, then switch to enforcement when ready.
Three Use Cases, One Platform
Omdia identifies three areas where Rein is already competing and winning:
Agentic AI and MCP Security. Rein is operating in near-virgin territory here. While MCP gateway solutions exist, their visibility stops at incoming prompts. Rein sees the full execution chain – what the agent did, what it accessed, and whether that behavior is within baseline. For organizations deploying autonomous AI workflows connected to sensitive systems, this is the capability that matters.
API Security. Traditional API security tools infer which APIs exist from network sampling. Rein sees the actual routes traffic takes, giving it authoritative knowledge of every API present – including ones that were never formally documented.
Software Composition Analysis (SCA). Beyond flagging vulnerable libraries, Rein identifies which vulnerable functions are actually being executed and whether they’re reachable via public-facing APIs. That triage capability lets teams stop chasing theoretical CVEs and focus on what’s genuinely exploitable.
The Omdia Verdict
Omdia’s analyst concludes that Rein’s platform is “a salutary development that should not only attract the attention of developers and SecOps teams, but also spur other vendors to come up with new ways to address the need to secure application environments.” The report expects Rein to gain customers and make headway in an increasingly competitive market.
Founded in 2024 by CEO Matan Bar Efrat and CTO Netanel Rubin – both Unit 8200 alumni, with pedigrees spanning Check Point, Cyberbit, and Elbit Systems – Rein is headquartered in New York and Tel Aviv and currently serves customers in financial services, insurance, critical infrastructure, and B2B SaaS across North America and EMEA.
Download the Full Report
The Omdia “On the Radar” report goes deeper on Rein’s architecture, competitive landscape, and analyst commentary. If agentic AI security – or the broader question of what your applications are actually doing in production – is on your team’s agenda, it’s worth reading in full.
Download the Omdia On the Radar report on Rein Security →
Tags: agentic AI security, MCP security, Model Context Protocol, AI agent risk, application security, runtime security, AppSec, API security, software composition analysis, SCA, application detection and response, ADR, runtime context, reachability analysis, AI application security, autonomous agent security, Omdia, On the Radar, Rein Security
FAQs
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Enterprise agents created a new security category because they operate inside production business systems where autonomous actions directly affect customers, regulated data, and operational outcomes.
- Identify which enterprise agents can access payment systems, healthcare infrastructure, customer records, or internal operational workflows
- Trace how autonomous actions propagate across APIs, MCP servers, databases, and downstream services during runtime execution
- Prioritize audit-grade visibility into what enterprise agents actually do instead of relying on prompt inspection alone
- Build security processes around business impact, operational continuity, and compliance exposure
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Traditional security tools fail because they observe inputs, network traffic, or static code without understanding the full execution chain of enterprise agents in production.
- Investigate which APIs, tools, and resources enterprise agents actually access during runtime execution
- Correlate prompts, API calls, model behavior, MCP activity, and downstream system interactions into a single execution chain
- Validate whether suspicious behavior resulted in real operational impact instead of theoretical risk
- Reduce investigation delays caused by disconnected logs and fragmented tooling
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Runtime execution visibility is critical because enterprise security teams need deterministic evidence of every action an agent performed and the exact business outcome it created.
- Trace execution behavior across prompts, APIs, MCP servers, libraries, databases, and external services in real time
- Investigate which users, workflows, or systems triggered sensitive enterprise agent activity
- Validate whether enterprise agents accessed unauthorized resources or deviated from expected operational behavior
- Accelerate incident response using complete runtime context instead of isolated telemetry
Find out how Rein defeats Claude Mythos.
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MCP security is becoming critical because enterprise agents increasingly rely on external tools, APIs, and data sources that expand operational attack surfaces far beyond traditional applications.
- Inventory which MCP servers can access sensitive systems, internal data, or external internet-connected resources
- Monitor how enterprise agents interact with MCP-connected tools during runtime execution
- Detect unauthorized resource access, unsafe tool usage, or unexpected downstream behavior
- Apply dynamic guardrails to prevent enterprise agents from reaching systems outside approved operational baselines
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Rein captures the complete execution chain of every enterprise agent action and directly connects runtime behavior to operational business impact.
- Observe prompts, APIs, libraries, MCP activity, stack traces, and downstream resource access in real time
- Investigate how enterprise agents affect payments, approvals, customer workflows, or regulated business processes
- Correlate runtime behavior with specific users, systems, and operational outcomes
- Replace fragmented AppSec assumptions with deterministic execution evidence grounded in production reality
Learn how Rein Security protects agentic AI workflows.
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Rein operates as a code-native sidecar inside the application execution environment without introducing gateways, proxies, eBPF dependencies, or external data exposure.
- Maintain complete in-org privacy by ensuring execution data never leaves enterprise infrastructure
- Deploy runtime visibility across enterprise agents, APIs, MCPs, libraries, and applications through a single deployment model
- Avoid latency and operational blind spots caused by network interception architectures
- Enable immediate runtime visibility without requiring extensive tuning or operational overhead
Find out why we started Rein Security.
