Levo Runtime Application Security Platform: Production Module Release Notes

Buchi Reddy B

CEO & Founder at LEVO

Buchi Reddy B

CEO & Founder at LEVO

Levo Runtime Application Security Platform: Production Module Release Notes

We’re thrilled to announce the launch of Levo’s Production Security modules!

The first modules available are Runtime API Threat Detection and Runtime API Protection. Soon, we’ll unify detection and protection across your entire software backend, including AI agents, MCP Servers, LLMs, and RAG.

With these additions, Levo has evolved from a shift-left security pioneer to a comprehensive, end-to-end Runtime Application Security Platform.

Legacy security tools work in isolation, compromising either application or runtime context. As a result, traditional solutions like SAST, DAST, and WAF often overlook complex access-control and business-logic issues. This leads to alert fatigue, missed threats, weakened security posture, and ongoing friction between DevSecOps teams.

Levo changes the game by delivering context, clarity, and control for modern applications, providing high-signal, low-volume alerts that matter.

Its runtime context, white-box approach, and efficient architecture ensure that security teams spend more time securing applications than triaging alerts.

With Levo, real attacks are never missed, false alerts don’t halt launches, security posture strengthens continuously, and Security becomes a growth enabler, not a cost centre.

Go through this release note to understand how we make this possible.

Why Levo.ai launched Runtime Application Security Modules

Levo.ai may have begun as a shift-left, proactive API Security Platform, but our vision has always been to be a one-stop, comprehensive security platform for modern software backend.

The paradigm that set out to challenge and transform was that of under-investing in shift-left security and using production controls as the sole line of defense.

Not only does this worsen breach risk, frequency, and impact, but it does so while driving cloud, human overhead through the roof. An insecure API in production will likely trigger a flurry of alerts, contributing to the noise that legacy tools already create.

By automating shift-left best practices like cataloging, documentation, security testing , Levo had already solved one piece of the puzzle. A lot of the efficacy of our platform is a result of being built from the ground up for modern API-first, AI-native applications.

By extending the same foundations to our runtime security modules, we address all of the foundational issues that plague legacy tools and thereby undo their impact as well.

The table below showcases how, with each transformation rendered legacy security tools more ineffective.

Architectural shift	Key characteristics	Why legacy security struggles	Consequence
Monolith → Microservices	Hundreds of independently deployed services; each exposes its own API, often using REST/JSON, gRPC, or GraphQL; services communicate east–west inside a cluster	Perimeter‑based WAFs see only the gateway/edge traffic and can’t inspect internal service‑to‑service calls; static rules can’t keep up with frequent changes and dynamic endpoints	Explosion in attack surface; blind spots inside service mesh; rule drift leading to high false negatives and noisy false positives
On‑prem → Cloud & Hybrid	Elastic containers and functions spin up and down; workloads spread across multiple clouds, regions, and AZs; all traffic is encrypted end‑to‑end	Traditional appliances expect fixed IPs and a defined perimeter; they can’t see traffic inside zero‑trust networks or across clouds; sending all traffic to a central sensor adds latency and costs	Coverage gaps across clouds, inconsistent policies, runaway egress costs, and missed attacks hidden inside encrypted east–west flows
Traditional code → AI‑native	LLM‑driven agents and autonomous services make decisions and call APIs and MCP tools on behalf of users; behaviour is non‑deterministic, and input can contain adversarial prompts	Signature‑based tools don’t understand prompts or model outputs; ACLs allow machine‑to‑machine calls without checking context; hard to baseline “normal” for an AI agent	Emergence of new attack vectors (prompt injection, data‑poisoning, AI‑assisted exfiltration) that go undetected; legitimate AI actions misclassified or vice versa, causing business disruption

These shifts demand that visibility and context be dramatically improved: security must observe every call, across distributed components and even into the logic of AI decisions – capabilities that first‑generation runtime controls simply cannot deliver

How Levo Closes Security Gaps in Runtime Security

As software has evolved, each shift has added new layers of abstraction, pushing visibility further away from the edge. Security tools originally built to monitor the perimeter have been pushed outward with each technological shift.

As a result, they have gradually lost sight of what truly happens inside applications. When visibility moves out of reach, precision is lost. You cannot detect exploits if you don’t see the communication threats, and you certainly cannot protect what you don’t know exists.

Visibility is not just another capability; it is the foundation upon which every security control stands.

When runtime visibility is compromised, detection devolves into noise without context, protection turns into blind enforcement, and every other security layer inherits the same blindness.

At Levo, we realized the only way to break this cycle was to go deeper, to the one layer that has remained consistent through every wave of software evolution. The operating system i.e. kernel has remained the common thread. It’s the heartbeat through which every process, every packet, and every API call eventually passes.

By anchoring our visibility at this stable layer using eBPF-based runtime instrumentation, we unlocked a perspective no legacy tool could achieve.

Levo’s kernel-level sensor observes application behavior before encryption, within east–west service calls, and across all environments, without code changes or intrusive agents. It’s a single, universal vantage point that provides the context legacy tools have spent decades chasing and never truly captured.

By reimagining visibility itself, Levo solved the root cause of production security’s failures. The table below outlines how this kernel-powered foundation allows Levo to overcome the blind spots, noise, and brittleness that have long defined legacy detection and protection systems.

Legacy pain point	Levo’s adaptation
Encrypted & east–west blind spots	Levo’s eBPF sensors hook into the operating system's network stack before encryption happens. By intercepting packets at this pre‑TLS layer, they can see every API call in clear text and identify which process generated it. This means both north–south and east–west flows, even those protected by mTLS, are visible to our detection engine and enforceable by our protection module. There is no need to terminate TLS or share keys, and nothing hides behind proxies or load balancers.
Contextless detection logic	Each eBPF event carries rich metadata: the exact process on the host, the user or token behind the request, the API schema and payload, and the downstream data flow. Levo correlates these details across services, so the detection engine knows when a spike in calls is a feature rollout versus an attack. The protection module enforces rules with the same context, blocking only malicious behaviour and never generic anomalies.
Rule brittleness & constant tuning	Because eBPF sensors stream continuous telemetry, Levo baselines normal behaviour for every service and automatically adapts as APIs evolve. There are no brittle signatures to maintain; detection learns new endpoints and parameters on the fly, and protection policies are version‑aware. This behavioural approach eliminates the manual rule tuning that plagues legacy WAFs and reduces both false positives and negatives.
Incomplete API coverage	Our instrumentation runs everywhere. When we can install on the host, eBPF sensors capture every inbound and outbound call with zero code changes. Where that isn’t possible, Levo offers plug‑ins for CDNs, load balancers, and API gateways. Together, they discover and monitor internal, shadow, and third‑party APIs, so detection and protection modules always operate on a complete inventory instead of a curated subset. Every endpoint is protected by default without the need for tedious routing.
High false positives & alert fatigue	Full context and behavioural baselines allow Levo to suppress harmless anomalies and surface only exploit‑backed threats. Detection distinguishes between a legitimate traffic burst and a DDoS, and protection acts only on confirmed malicious requests. Analysts see a handful of actionable alerts instead of thousands of noise events, and developers can trust that blocking mode won’t break their applications.
High false negatives & missed attacks	Because eBPF sensors see all traffic, there are no blind spots where an attacker can hide. Behavioral analytics built on this complete view detect low‑and‑slow exploits, data exfiltration, and business‑logic abuse that signature‑based systems miss. Protection policies close the loop by blocking those attacks in real time.
Vulnerabilities shipping to prod	Runtime findings feed back into automated tests and provide remediation guidance, enabling root-cause remediation so it can never be exploited in production again.
Microservices complexity	Sensors deploy on each node where microservices are running and observe east–west traffic, scaling seamlessly with microservice growth.
Cloud & hybrid sprawl	Distributed enforcement processes data locally across multi‑cloud and hybrid environments, avoids expensive traffic mirroring, and maintains consistent policies.
AI & modern app readiness	Levo monitors AI agents and LLM‑powered services alongside traditional APIs, detecting prompt injection and M2M anomalies so AI is never a blind spot.

Levo’s Privacy Preserving Runtime Security Architecture

Many runtime security products claim minimal latency and low TCO, yet their architecture betrays this claim: they mirror entire API payloads to vendor clouds for off‑site analysis and then send enforcement decisions back.

This “phone‑home” model creates a dangerous trifecta:

latency that breaks user flows
egress charges that balloon to hundreds of thousands of dollars each year
uncontrolled exposure of sensitive data to third parties.

In regulated industries, it’s a non‑starter: the security tool itself becomes a compliance risk.

Levo takes a fundamentally different approach.

Our eBPF sensors and lightweight satellites run inside your environment, execute all detection and protection locally, and discard raw payloads immediately.

The only thing that ever leaves your infrastructure is sanitised metadata; no PII, no secrets, no large payloads.

Because there is no round‑trip to a SaaS vendor, enforcement happens in near real time, and enterprises avoid the six‑figure egress bills that plague legacy deployments.

This design makes powerful runtime security not just feasible but cost‑effective and compliant, giving teams confidence to deploy microservice and AI workloads without fear of runaway costs or data breaches.

Book a demo through this link to see our production security modules live in action!

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