Security & SIEM Accelerator

Your SIEM Has Rules. Attackers Have Workarounds. Our ML Doesn't.

Threat Correlation Engine uses ML behavior analytics and multi-stage attack correlation to detect threats that rule-based SIEM misses -- across your Elasticsearch SIEM indices. MITRE ATT&CK mapping on every detection. False positives cut 85%.

Schedule 15-Minute Demo Get SIEM Readiness Assessment

verified 85% False Positive Reduction shield 3 APT Campaigns Detected emoji_events Elastic Innovation Award 2023 schedule 24-Hour Response SLA

The Threats Your Rules Can't See

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Attackers Don't Match Signatures

Sophisticated attackers don't trigger rules. They move slow, blend in across dozens of loosely connected events, and only become visible in hindsight. Multi-stage attacks are invisible to rule-based detection because no single event is anomalous.

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85% of Alerts Are False Positives

Your SOC analysts dismiss most alerts as noise. Alert fatigue is real -- analysts deprioritize, skip, and develop blind spots. The one alert they dismiss incorrectly is the breach that costs you.

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Rules Were Written for Yesterday's Attacks

SIEM detection rules require you to know what you're looking for. By the time your team writes a rule for a new technique, the attacker has moved on. Rule maintenance is a treadmill that never catches up.

"Detected 3 APT campaigns missed by signature-based tools. Reduced false positives 85% compared to SIEM-only setup."

CISO, Financial Services Company

From Raw Signals to Ranked Threats in Five Steps

Ingest Security Signals

Threat Correlation Engine connects to your Elasticsearch SIEM indices: firewall logs, endpoint events, authentication logs, network flows, cloud audit trails. No data migration required.

Establish Behavioral Baselines

ML models build per-entity baselines -- what is normal for each user, host, and service. Meaningful baselines form within the first two to four weeks on your data.

Detect and Correlate

Anomaly detection flags behavioral deviations. Multi-stage correlation maps related events across time and systems into attack sequences -- identifying kill chain progression even when individual events appear benign.

Kill chain detection timeline showing individual security events connected by correlation edges revealing a multi-stage attack pattern over 14 days

link Kill chain detected.

Map and Enrich

Every detection tagged to the relevant MITRE ATT&CK tactic and technique. Threat intelligence integration adds known indicator enrichment from STIX/TAXII feeds alongside behavior-based detection.

Deliver Ranked Threats

Priority-scored alert queue delivers ranked threats to your SOC analysts. Highest confidence, highest severity, largest blast radius first. Your team works real incidents, not noise.

Six Capabilities Your SIEM Rules Can't Replicate

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ML Behavior Analytics

Per-entity baselines detect deviations from normal behavior. Catches insider threats and novel attack patterns that signatures miss. No rules to write. No patterns to define.

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Multi-Stage Attack Correlation

Maps attack sequences across time and systems. Identifies kill chain progression by connecting events that appear benign in isolation. This is the capability gap in every rule-based SIEM.

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MITRE ATT&CK Mapping

Every detection tagged to ATT&CK tactic and technique. Lateral Movement. Pass the Hash. Data Exfiltration. Your analysts communicate in one framework. Your compliance reports map to security standards.

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Threat Intelligence Integration

STIX/TAXII feed support enriches behavior-based detections with known threat indicators. Combines signature-based and ML-based approaches. Threat intel is additive, not required -- ML operates independently.

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Auto-Tuning False Positive Reduction

ML models update from analyst feedback. Confirmed threats sharpen future detection. Dismissed alerts are learned and suppressed automatically. False positive rate decreases continuously over time.

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Priority Scoring

Each threat alert scored by confidence, severity, and blast radius. SOC analysts work the highest-priority incidents first. No more guessing which alert matters.

Measured Impact, Not Marketing Claims

85%

False positive reduction compared to SIEM-only setup. Documented across customer deployments.

APT campaigns detected before impact that signature-based tools missed entirely.

Reclaimed

SOC analyst capacity previously consumed by false positive triage, now redirected to real investigations.

Rule-Based SIEM

Detection	Signature matching -- must know the pattern in advance
False Positives	High -- overly sensitive rules generate noise
Multi-Stage	Invisible -- no single event triggers a rule

Threat Correlation Engine

Detection	ML behavior analytics -- detects deviations from normal
False Positives	Reduced 85% -- auto-tuning suppresses learned false positives
Multi-Stage	Correlated -- events mapped into kill chain sequences

Elasticsearch ML jobs are the foundation. Threat Correlation Engine adds multi-stage correlation logic, MITRE ATT&CK mapping, priority scoring, and auto-tuning. We built it because we kept rebuilding it for clients.

schedule 24-Hour Response SLA. Demo scheduled within 72 hours. SIEM assessment requests receive priority response.

The SIEM Accelerator Suite -- Three Accelerators, One Methodology

Threat Correlation Engine is the detection layer in the SquareShift SIEM accelerator suite. Every detection feeds downstream systems. Every alert connects to compliance and remediation.

Compliance Reporter

Every detection generates compliance evidence. Access violations, policy breaches, and security events become audit trail entries. Pass SOC2, PCI-DSS, and HIPAA with detection-linked evidence.

AI Triage Assistant

Confirmed threats routed to AI-powered triage for remediation suggestion. Reduce mean time to respond. Your SOC analysts get recommendations, not just alerts.

Alarm Noise Suppression

Broader SIEM alert volume reduction across the entire alert stream. Works alongside Threat Correlation Engine to reduce noise at every stage of the pipeline.

Three accelerators. One 12-week SIEM implementation methodology. Part of the SIEM Readiness Assessment engagement. No competitor offers this as named IP.

Explore SIEM Accelerator Bundle →

Validated in Production

Financial Services CISO

Deployed Threat Correlation Engine alongside Elasticsearch SIEM. Detected 3 APT campaigns that were invisible to signature-based detection. Reduced false positive rate 85% within first quarter.

3 APT campaigns detected · 85% false positive reduction

Enterprise Validation -- Broadcom

Broadcom security reference validates enterprise-grade security capability for the Threat Correlation Engine. Production deployment at enterprise scale.

Enterprise-scale production deployment

SOC2 Case Study

Payments platform deployed Threat Correlation Engine + Compliance Reporter + AI Triage Assistant. Passed SOC2 audit in 12 weeks. The SIEM accelerator suite delivered audit-readiness on deadline.

SOC2 passed in 12 weeks · Full accelerator suite

Common Questions

Straight answers to the questions security teams ask before scheduling a demo.

How is ML-based threat detection different from rule-based SIEM? expand_more

Rule-based SIEM requires you to know what you're looking for and write a rule for it. ML-based detection establishes what "normal" looks like and flags deviations -- catching attacks that don't match any known signature. Rules work for known patterns. ML works for novel threats.

Does Threat Correlation Engine require threat intelligence feeds to work? expand_more

No. Behavior-based detection operates independently of threat intel feeds. STIX/TAXII integration is additive -- it enriches detections with known indicators but is not required for the ML layer to function.

How long before ML models establish accurate baselines? expand_more

Meaningful baselines typically form within the first two to four weeks on your Elasticsearch data. Detection accuracy improves continuously from there as models learn from analyst feedback on confirmed vs. dismissed detections.

What is the MITRE ATT&CK mapping used for? expand_more

It tags each detection to a specific tactic (e.g., Lateral Movement) and technique (e.g., Pass the Hash). This makes analyst communication consistent across your SOC team and enables compliance reporting that maps directly to security framework requirements.

Is Threat Correlation Engine standalone or part of a SIEM engagement? expand_more

Available both ways. Included in SIEM engagements and the 12-week SIEM implementation methodology. Available standalone with custom implementation. Pricing is custom -- included in SIEM engagements; standalone requires consultation.

See What Your SIEM Is Missing

Schedule a 15-minute demo. See how Threat Correlation Engine detects the threats your rules were never written for. Your SOC will thank you.