Introducing Levo’s API Threat Detection for API Security

We at Levo.ai, are excited to announce the launch of our Runtime API Threat Detection module!

Developed on our visibility and governance modules, this solution aims to reduce breaches and deliver measurable improvements in security posture, developer velocity, and security productivity.

This represents a significant advancement over legacy detection platforms, which often fail to prevent incidents and may even contribute to their increase.

Legacy systems overwhelm SOC teams with numerous alerts lacking context, exploitability, or urgency. This can desensitize or overwhelm teams, leading to real threats being missed.

Managing excessive alerts also increases resource demands and often raises the total cost of ownership without delivering sufficient return on investment.

With comprehensive visibility into an enterprise’s API footprint and runtime context, Levo provides low volume, high value alerts with minimal mean time to detect.

Go through this blog to understand how Levo accelerates Mean Time to Repair (MTTR), remediation of the root cause, i.e. insecure code, freeing up security bandwidth to secure, not triage more.

How Levo’s Runtime API Threat Detection Works 

When detection fails, everyone suffers. 

Overly aggressive, network centric tools generate high false positives that block legitimate user requests and degrade revenue and customer experience. 

At the same time, they miss low‑and‑slow or business‑logic attacks, giving a false sense of security and leaving breaches undetected. 

Beneath these outcomes lie structural flaws: legacy WAFs and API firewalls rely on static signatures and regex rules that can’t parse rich JSON/GraphQL payloads or encrypted east–west traffic. 

They watch only documented, high traffic external endpoints and require constant rule tuning to avoid breaking releases; with no runtime context, they can’t tell whether an attack succeeded or which user and data flow were involved. 

Shadow APIs and microservices slip past them, and each deployment update risks a window of exposure. The result is a detection program that slows development, burdens security teams and still lets attackers through.

Levo’s Runtime API Detection Differentiators

1. Runtime, Pre‑Encryption API Visibility Using eBPF Sensors: Levo instruments APIs at the kernel level with eBPF sensors, observing every call exactly where it runs. This includes encrypted TLS/mTLS traffic and east–west microservice calls, so nothing is hidden by proxies or certificates. By tying each request to its user, token and data flow, Levo makes every alert specific and actionable.
   
   
2. Continuous Runtime API Discovery and Comprehensive Coverage: Built on Levo’s discovery engine, detection starts automatically for every API: internal, external, partner and shadow. There is no manual onboarding and no “unknown API”. As environments evolve, new APIs are automatically observed at deploy time, ensuring complete coverage across the estate.
   
   
3. Behavioral and Version Aware Runtime API Threat Detection: Levo learns normal behaviour for each service and flags misuse, schema drift or unapproved auth flows without brittle signatures. Rich contextual alerts show who attacked, what was hit and where the problem lies. Analysts no longer chase generic alarms; they trace threats directly back to the code that introduced them.
   
   
4. Shift left Runtime API Security Integration and Detection Automation: Runtime anomalies automatically feed new test cases and baselines into the CI/CD pipeline. Developer-centric automation through Levo’s MCP Server turns every signal into a readymade Jira or GitHub ticket. Dev and Sec teams fix the root cause quickly instead of chasing ghosts, collapsing remediation from months to hours.
   
   
5. Accurate Runtime API Threat Detection with Reliable Application Performance: All data is processed within your environment, so no payloads leave for inspection. This eliminates egress costs and data residency headaches and ensures negligible latency. Security scales with your application without introducing bottlenecks or outages.

Measurable Improvements Across Every Runtime API Threat Detection Metric

Levo enhances the API threat detection and improves different runtime detection metrics for better results:

1. Highest True Positive Rate (TPR), Real API Attacks Detected, Not Assumed

Levo observes every API call at runtime, directly where execution occurs, before encryption, proxies, or sampling reduce visibility.

Because detection is rooted in actual behavior and data flow, not pattern matching heuristics, it reliably distinguishes real attacks from background noise, ensuring meaningful threats are surfaced proactively.

2. Near-Zero False Positives with Context-Aware Runtime API Detection 

By combining runtime context (kernel level, pre-encryption telemetry, call graphs, traces) with application context (user/session identity, tokens, API schema lines, data classification, business workflow). By validating exploitability against both layers, Levo suppresses benign anomalies and surfaces only alerts that truly matter. Signals arrive explainable and provenance rich, so analysts skip noisy triage and developers avoid unnecessary interruptions, keeping teams focused, responsive, and engaged.

3. 100% API Threat Detection Coverage by Default

Continuous runtime discovery ensures every API:  internal, external, partner, shadow, zombie, is automatically identified and monitored. There are no manual onboarding steps, gateway dependencies, or spec prerequisites.

This eliminates the single biggest source of missed breaches: the API you didn’t know existed.

4. Near-Zero Detection Latency (MTTD), Real-Time Runtime API Threat Alerts

Because analysis happens within enterprise environments, passively, at runtime (not in a vendor cloud), alerts are generated in sub-millisecond timeframes.

This shortens attacker dwell time and prevents lateral movement inside microservice meshes, protecting revenue, uptime, and data integrity.

5. Rapid Runtime API Threat Remediation with Root Cause Fixes

Every detection is mapped to the owning service, API and responsible team, eliminating the typical triage backlog. Developers can query Levo’s MCP Server to receive remediation guidance, like the patch code closing the loop from detection >> understanding >> fix.

Levo’s Privacy Preserving Security Architecture

Every Levo module is designed to be effective, lightweight, and aligned with business growth. Security shouldn’t compromise developer velocity, violate compliance, or inflate infrastructure costs.

The detection module follows the same principles. It avoids traffic mirroring, full payload ingestion, and costly inline deployments that strain production systems.

Our eBPF-based sensors, one of twelve available instrumentation methods, passively observe API traffic across environments, including encrypted flows.

This traffic is processed locally within the Levo Satellite, which can be self hosted or deployed instantly across environments. 

After analysis, the traces are discarded.

Only sanitized metadata and OpenAPI specifications are sent to the cloud. No raw payloads, no sensitive fields, and nothing that violates data residency requirements.

Because analysis and enforcement are handled entirely within your infrastructure, there’s no round trip to an external SaaS for decision making. 

This keeps latency near zero, maintains application performance even at scale and avoids $500k+ in annual egress costs, making monitoring cost effective and predictable as usage grows.

Hence, financial services, healthcare, and other regulated sectors trust Levo to deliver real time detection without sacrificing compliance, performance or over running security budgets. 

Book a demo through this link to see this live in action!