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TELEMETRY MESH · SIGNAL INGESTION · MULTI-SOURCE NORMALIZATION · ATTACK CONTEXT

Your tools already havethe signals. Spaktoconnects them into context.

Spakto's Telemetry Mesh ingests and normalizes signals from EDR, SIEM, IAM, cloud, DevOps, and network tools — transforming siloed data into a unified, correlated security context that feeds the live attack graph.

Telemetry Mesh · Signal Ingestion Active

Security teams don't lack data.
They lack connection.

Each security tool sees a fragment of the attacker's story. EDR sees the endpoint. IAM sees the identity. Cloud logs see the API call. None of them see the full attack chain. The Telemetry Mesh stitches every signal into unified context — automatically, in real time.

Native connectors to 50+ security tools — no custom engineering required
Real-time normalization into a unified security event schema
Cross-source correlation linking events across identity, endpoint, cloud, and network
Automatic enrichment with threat intelligence and asset criticality
Zero alert duplication — correlated attack chains, not alert storms
Feeds directly into the live Spakto attack graph in real time
TM · MESH TOPOLOGY · LIVE
4,247 events/s
EDREDRCrowdStrike·S1IAMIAMOkta·AzureADCLOUDCLOUDAWS·Azure·GCPNETWORKNETWORKPaloAlto·ZscalerSIEMSIEMSplunk·ElasticDEVSECDEVSECGitHub·GitLabTITIMITRE·RecFutureVULNVULNTenable·Rapid7TELEMETRYMESHATTACK GRAPHLive · Unified · Context
50+
Sources
<40ms
Latency
50+
Native Integrations
Real-time
Signal Normalization
Zero
Custom ETL Required
Unified
Attack Context Layer
Integration Registry · 50+ Sources

Every tool in your stack.
Natively connected.

Spakto natively integrates with 50+ security tools across endpoint, identity, cloud, network, and DevOps platforms — transforming siloed alerts into unified, correlated security intelligence.

50+
native integrations
across 6 categories
EDR & Endpoint
10integrations
18ms
avg latency
Throughput92%
CrowdStrike FalconSentinelOneMicrosoft DefenderCarbon BlackCortex XDR+5 more
·Process execution trees
·Lateral movement signals
·Host-based IOCs
·EDR prevention events
·Memory injection alerts
Identity & IAM
8integrations
24ms
avg latency
Throughput67%
OktaAzure AD / Entra IDCyberArk PAMPing IdentityAWS IAM+3 more
·Authentication events
·Privilege changes
·Role assignments
·MFA bypass attempts
·Service account activity
Cloud Platforms
9integrations
32ms
avg latency
Throughput78%
AWS CloudTrailAzure MonitorGCP Cloud LoggingSecurity HubDefender for Cloud+4 more
·API call records
·Resource creation/deletion
·IAM role changes
·Storage policy changes
·Network rule modifications
SIEM & Log Management
7integrations
44ms
avg latency
Throughput55%
Splunk SIEMIBM QRadarMicrosoft SentinelGoogle ChronicleElastic SecuritySumo Logic
·Normalized alert feeds
·Raw log correlation
·Detection rule hits
·TI enrichment
·Saved search outputs
DevOps & CI/CD
9integrations
61ms
avg latency
Throughput41%
GitHubGitLabJiraJenkinsServiceNowPagerDuty+3 more
·Pipeline events
·Code changes with CVEs
·Deployment audit logs
·Vulnerability tickets
·Change management records
Network & Perimeter
8integrations
13ms
avg latency
Throughput88%
Palo Alto NetworksFortinet FortiGateCisco FirepowerZscalerCloudflareAkamai+2 more
·Traffic flow records
·Firewall rule hits
·East-west movement
·DNS telemetry
·Proxy access logs
Normalization Pipeline · 4 Stages · Streaming

Raw telemetry to
attack-ready context

Every signal from every tool passes through the same 4-stage normalization pipeline before entering the attack graph. Heterogeneous vendor formats become one universal security event schema — automatically.

TM · NORMALIZATION PIPELINE · STREAMING · 4,247 events/s throughput
INGEST50+ sourcesSTAGE 01PARSESchema mappingSTAGE 02ENRICHTI · Asset · GeoSTAGE 03CORRELATECross-source joinSTAGE 04RAWATTACKGRAPH
01 · INGEST4,247 events/s

Raw Signal Ingestion

  • Native API, syslog, streaming, agent
  • Automatic protocol negotiation
  • Backpressure management
  • End-to-end encryption in transit
02 · PARSE4,244 events/s

Schema Normalization

  • 50+ vendor format parsers
  • Universal field mapping table
  • Timestamp normalization + dedup
  • Type coercion + null inference
03 · ENRICH4,241 events/s

Context Enrichment

  • Asset criticality injection
  • MITRE ATT&CK technique tagging
  • Threat intel IOC matching
  • Geo/IP and user risk scoring
04 · CORRELATE12.3 chains/min

Cross-source Correlation

  • Entity resolution across sources
  • Behavioral session stitching
  • Attack chain assembly
  • Attack graph node/edge creation
Telemetry Mesh vs Custom SIEM Rules

Less engineering.
More attack intelligence.

Custom SIEM rules take months to build, break when vendors update APIs, and produce alert storms with no attacker context. The Telemetry Mesh connects in minutes and outputs ranked attack chains.

Capability
Custom SIEM Rules
Spakto Telemetry Mesh ★
Time to connect
Months (custom engineering)
Minutes (native connectors)
Vendor API changes
Breaks — manual re-engineering
Auto-adapting, zero downtime
Output format
Alert-centric (individual IOCs)
Attack-path-centric (full chains)
Engineering required
Dedicated SIEM engineering team
Zero engineering required
Correlation logic
Static rules, no context
Behavioral, cross-domain
Result quality
Alert storms, high false positives
Ranked attack paths, low noise
Cross-domain visibility
Single-source only
EDR + IAM + Cloud + Network
MITRE ATT&CK coverage
Manual tagging
Automatic technique mapping
30 min
Average time to connect new integration
Zero
Custom ETL pipelines required
97%
Reduction in alert noise vs SIEM alone
Signal Path · How Signals Become Attack Intelligence

How signals become
attack intelligence

Four tools each see one fragment of the same attack. None connect them alone. The Telemetry Mesh joins all four into a complete, correlated attack chain — in under 43 seconds.

TM · SIGNAL PATH · ACTIVE CORRELATION · ATTACK-2024-08474 SOURCES · CORRELATED IN 43s
OktaIAM02:47:01Zsvc-deploy authenticated from new IP 185.220.101.xT1078.003 · Valid Accounts: Local AccountAWSCloudTrail02:47:31ZAssumeRole prod-admin-role — 30s after IAM eventT1078.004 · Valid Accounts: Cloud AccountsCrowdStrikeEDR02:51:44ZProcess injection in svchost.exe on EC2 prod-01T1055 · Process InjectionS3Audit Log02:55:22ZGetObject: 347 files from prd-secrets bucket (8.4 GB)T1530 · Data from Cloud StorageTELEMETRYMESH43s · 4 sourcesATTACK CHAINInitial access → Priv esc → Exec → Exfil
Mesh Conclusion · Attack Chain ATTACK-2024-0847CRITICAL

Connected 4 signals across 4 tools into a complete attack chain showing Initial access → Privilege escalation → Remote code execution → Data exfiltration — none of which were visible to any single tool in isolation. Correlated in 43 seconds.

Use Cases · Who Benefits from Unified Telemetry

Who benefits from
unified telemetry

From SOC analysts drowning in alert noise to security architects mapping tool coverage gaps — unified telemetry transforms every security function.

SOC Teams
97%
alert noise reduction

Eliminate alert fatigue — see correlated attack chains, not individual alerts. Reduce MTTR from days to hours with full attack context at first glance.

Before: 10,000 alerts/day, manual correlation, 48h MTTR
After: 3-5 attack chains/day, full context, <2h MTTR
  • Correlated attack chain view
  • Cross-source context in seconds
  • MITRE ATT&CK pre-mapped
  • AI-suggested response actions
Threat Hunters
1 graph
replaces 50+ tool queries

Query across all sources in one unified graph. Hunt with attacker-centric hypotheses against the full signal corpus — not siloed tool-by-tool searches with no cross-source context.

Before: Query each tool separately, manually join results
After: Single graph query across all 50+ sources
  • Unified signal graph queries
  • Cross-domain pivot hunting
  • MITRE technique filtering
  • Historical attack pattern search
Security Architects
Full
coverage visibility map

Understand which gaps in your tool coverage create blind spots in the attack graph. Make data-driven decisions about tool investments with real coverage heat maps.

Before: Unknown coverage gaps, tool investments based on guesswork
After: Precise coverage map, data-driven tool decisions
  • Attack graph coverage scoring
  • Source gap identification
  • Tool overlap analysis
  • ROI-driven investment guidance
Universal Security Event Schema · Field Mapping

One schema.
Every vendor, unified.

50+ vendors use 50+ different field names, timestamp formats, and data types. The Spakto Universal Schema maps every vendor field to a single canonical structure — enabling cross-source correlation without any manual field mapping.

VENDOR FIELD → UNIVERSAL SCHEMA · FIELD MAPPING
Vendor (Raw)
Universal Field
CrowdStrike: ProcessName
process.name
Okta: actor.displayName
identity.user
AWS: userIdentity.arn
identity.arn
Splunk: src_ip
network.source_ip
SentinelOne: srcProcName
process.name
Azure: callerIpAddress
network.source_ip
Fortinet: srcip
network.source_ip
QRadar: sourceip
network.source_ip
GitHub: actor
identity.user
GCP: protoPayload.authInfo.who
identity.user
Schema Namespaces
process.*18 fields
identity.*14 fields
network.*22 fields
cloud.*16 fields
file.*11 fields
threat.*9 fields
Zero Custom Mapping

All 50+ vendor schemas are pre-mapped to the universal schema. No manual field mapping, no ETL pipelines, no data engineering required.

Temporal Normalization

Timestamps from all sources are normalized to UTC with millisecond precision. Sub-second ordering across tools enables accurate cross-source correlation.

Type Coercion & Inference

IP addresses, hostnames, user identifiers, and domain objects are resolved to canonical types — enabling entity resolution across vendor-specific representations.

Schema Versioning

When vendors update their APIs, Spakto automatically updates the mapping. Your data pipeline never breaks when a vendor releases a new API version.

Deployment Architecture · 3 Models

Deploy anywhere.
Your boundary. Your rules.

The Telemetry Mesh runs within your deployment boundary — no raw security telemetry leaves your environment. Choose the deployment model that fits your data residency and compliance requirements.

Cloud-Hosted SaaSFastest Setup
Setup: < 2 hours

Mesh collector agents deploy in your environment, stream normalized events to Spakto-hosted infrastructure. Setup in under 2 hours.

  • Collector agents on-premises
  • Encrypted event streaming
  • Spakto-managed infrastructure
  • Auto-scaling + HA built in
Customer-Hosted VPCRecommended
Setup: < 8 hours

Full Telemetry Mesh runs inside your cloud VPC. No data leaves your boundary. Spakto manages updates and scaling remotely.

  • Deployed inside your AWS/Azure/GCP VPC
  • Zero data leaves your boundary
  • Remote management by Spakto
  • Configurable retention + residency
On-PremisesAir-Gapped Ready
Setup: 1-3 days

Full Mesh deployment on your own infrastructure. No internet connectivity required. Ideal for government, defense, and regulated environments.

  • Full on-prem deployment
  • Air-gap / offline mode supported
  • FIPS 140-2 compliant cryptography
  • Local key management
Feature
SaaS
VPC
On-Prem
Data leaves environment
Normalized only
Never
Never
Setup time
< 2 hours
< 8 hours
1-3 days
Data residency control
Shared
Full
Full
Air-gap support
No
No
Yes
Auto-scaling
Yes
Yes
Manual
Compliance (FIPS/FedRAMP)
In progress
Yes
Yes

Telemetry Mesh FAQs

Frequently asked
questions.

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