Traceable AI

Traceable AI is an API security platform that leverages distributed tracing technology to discover, test, and protect APIs while tracking sensitive data flows across microservices architectures. Harness acquired Traceable in March 2025, merging API security with its DevSecOps platform.

What is Traceable AI?

Traceable AI provides comprehensive API security through a platform that was purpose-built around distributed tracing.

While other API security tools observe traffic at network boundaries, Traceable follows requests through your entire application stack, understanding how data flows between services, databases, and external APIs.

The platform was founded by Jyoti Bansal, who previously created AppDynamics (acquired by Cisco for $3.7B).

This background shows in Traceable’s deep understanding of service meshes, microservices communication patterns, and the challenges of securing distributed applications.

Traceable covers the complete API security lifecycle: discovering APIs automatically, testing them for vulnerabilities during development, protecting them at runtime, and providing forensic investigation capabilities when incidents occur.

Key Features

Distributed Tracing-Based Discovery

Traceable discovers APIs by analyzing distributed traces rather than just network traffic:

• Complete service maps: Sees every service-to-service API call, including internal APIs never exposed externally
• Data flow tracking: Follows sensitive data from ingress through every service it touches
• Dependency mapping: Understands which services depend on which APIs
• Change detection: Identifies when API behavior changes between deployments

This trace-based approach catches shadow APIs and internal services that perimeter-focused tools miss entirely.

Sensitive Data Flow Tracking

The platform tracks sensitive data as it moves through your applications:

• Identifies where PII, financial data, and credentials enter your system
• Maps how that data propagates across services
• Detects when sensitive data appears in unexpected locations
• Alerts when data reaches services that should not have access

This data lineage capability helps with compliance requirements (GDPR, CCPA) and reduces data exposure risk.

API Security Testing

Traceable tests APIs for vulnerabilities using context from production traffic:

• OWASP API Top 10: Comprehensive coverage of API-specific vulnerabilities
• Business logic testing: Uses learned API behavior to test authorization and access controls
• Attack surface analysis: Identifies API endpoints that accept sensitive data
• Fuzzing: Generates test payloads based on observed data patterns

Tests run against staging environments but benefit from production traffic analysis.

Runtime Threat Detection

Real-time protection identifies attacks against your APIs:

• Behavioral anomaly detection: Alerts when API usage patterns deviate from baseline
• Attack signature detection: Identifies known attack patterns (injection, enumeration)
• Account takeover prevention: Detects credential stuffing and session hijacking
• Rate limiting evasion: Catches distributed attacks that circumvent simple rate limits

The platform can operate in detection or blocking mode depending on your risk tolerance.

GenAI API Security

Traceable provides specific protections for LLM and GenAI applications:

• Identifies API endpoints connected to LLM services
• Detects prompt injection attempts
• Monitors for data exfiltration through AI responses
• Tracks which data is sent to third-party AI APIs

Integration

Deployment Options

Traceable integrates with your infrastructure through multiple methods:

Tracing Agent: Deploy alongside your existing OpenTelemetry or Jaeger setup:

# Kubernetes deployment with tracing agent
apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-service
spec:
  template:
    spec:
      containers:
        - name: my-service
          env:
            - name: OTEL_EXPORTER_OTLP_ENDPOINT
              value: "http://traceable-collector:4317"
            - name: OTEL_SERVICE_NAME
              value: "my-service"
        - name: traceable-agent
          image: traceable/agent:latest
          env:
            - name: TRACEABLE_API_KEY
              valueFrom:
                secretKeyRef:
                  name: traceable-config
                  key: api-key

Traffic Mirroring: Analyze mirrored traffic without inline deployment:

# AWS Traffic Mirroring configuration
Resources:
  TraceableMirrorTarget:
    Type: AWS::EC2::TrafficMirrorTarget
    Properties:
      NetworkLoadBalancerArn: !Ref TraceableNLB
      Description: Mirror to Traceable analyzer

API Gateway Integration: Native connectors for Kong, AWS API Gateway, and Apigee.

CI/CD Pipeline Integration

Run API security tests during development:

# GitHub Actions — using the official Traceable AST Action
name: API Security Testing

on:
  pull_request:
    branches: [main]

jobs:
  traceable-scan:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Deploy to staging
        run: docker-compose up -d

      - name: Run Traceable AST
        uses: Traceableai/ast-action@main
        with:
          scan_name: 'CI Security Scan'
          traffic_env: ${{ secrets.TRACEABLE_TRAFFIC_ENV }}
          token: ${{ secrets.TRACEABLE_TOKEN }}

SIEM and Alerting Integration

Traceable integrates with SIEMs through webhook-based alert forwarding configured in the Traceable platform UI. Supported SIEM integrations include Splunk, Datadog, and Sumo Logic. Alert rules and severity thresholds are managed from the Traceable dashboard.

OpenTelemetry Integration

If you already use OpenTelemetry, Traceable can consume your existing traces:

# Traceable uses its own platform agent for trace collection
# Deploy via Helm: helm install traceable-agent traceable/traceable-agent
# The agent runs as a DaemonSet or sidecar proxy
# See: https://docs.traceable.ai/docs/k8s

When to Use Traceable AI

Ideal for organizations that:

• Run microservices architectures with service-to-service API communication
• Already use or plan to use distributed tracing (OpenTelemetry, Jaeger)
• Need to track sensitive data flows for compliance
• Want API security that understands internal APIs, not just external endpoints
• Build GenAI applications with LLM API calls
• Require deep forensic investigation capabilities for security incidents

Consider alternatives if:

• Your architecture is monolithic with few internal APIs
• You need a simple, lightweight API gateway security solution
• Budget constraints favor open-source alternatives
• You prefer detection-only without runtime protection needs

Traceable AI brings the observability mindset to API security.

By building on distributed tracing foundations, it provides visibility into API behavior that network-perimeter tools cannot match, making it particularly valuable for organizations with complex, distributed architectures.

Frequently Asked Questions