Detect Identity Threats in Real-Time
Behavioral analytics purpose-built for non-human identities. Detect compromised service accounts, anomalous AI agents, and credential abuse before damage is done.
Traditional Security Tools Miss NHI Attacks
Security tools built for human behavior can't detect machine identity anomalies. Non-human identities generate different patterns that legacy SIEM systems miss entirely.
Human-Focused Tools
Traditional security tools are designed for human behavior patterns, missing NHI anomalies.
Different Patterns
Machine identities and AI agents generate patterns that legacy SIEM systems can't interpret.
Delayed Detection
By the time anomalies are noticed through manual review, attackers have already moved laterally.
Alert Fatigue
Generic alerts without NHI context lead to false positives and burned-out security teams.
Behavioral Analytics for Machine Identities
Astellent uses ML specifically designed for NHI patterns. We learn what normal looks like and instantly flag deviations—whether it's a compromised service account or a rogue AI agent.
Behavioral Baselines
Astellent learns what normal looks like for each identity—access patterns, timing, volume, and destinations.
Real-Time Alerts
Instant notifications when behavior deviates from baseline. No waiting for batch processing or log aggregation.
Identity Context
Every alert includes the full identity context—who owns it, what it accesses, why it exists, and its risk profile.
Auto-Quarantine
Automatically suspend suspicious identities while investigation continues. Stop breaches before they spread.
SIEM Integration
Feed enriched alerts into Splunk, Elastic, Sentinel, or any SIEM. Works with your existing security stack.
Threats We Detect
Purpose-built detection models for the threats that matter most.
Credential Compromise
CriticalService account accessed from unusual location or at unusual time
Privilege Escalation
HighIdentity requesting access beyond normal scope
Data Exfiltration
CriticalUnusual volume of data access or download patterns
Lateral Movement
HighIdentity accessing resources outside normal workflow
AI Agent Deviation
MediumAgent behavior differs from declared intent
Orphan Activity
HighDormant identity suddenly becoming active
How Detection Works
Continuous learning and real-time response.
Learn
ML models learn normal behavior patterns for each identity over time.
Monitor
Every action is compared against the behavioral baseline in real-time.
Detect
Anomalies trigger alerts with full context and recommended actions.
Respond
Auto-quarantine suspicious identities and feed alerts to your SIEM.
Related Capabilities
Detection is more powerful with these complementary capabilities.
Stop threats before they spread
See how Astellent can bring real-time threat detection to your NHI environment. Catch compromised identities before attackers can move laterally.