Behavior first
Look beyond a static file label to suspicious execution, scripting, injection, evasion, and fileless patterns.
NGAV / Malware Prevention
Block known and emerging malware
A behavior-first prevention surface for suspicious execution, scripting, injection, evasion, and fileless activity—designed to make a security decision explainable, bounded, and verifiable.
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The capability
Prevent behavior that should not continue
Traditional prevention often starts with a file verdict. Spacetime’s model is broader: observe the execution context, interpret the signal against policy, and keep the response inside a declared boundary.
Policy aware
Bring prevention profiles and declared intent into the decision boundary instead of treating every signal as an isolated alert.
Evidence ready
Keep the signal, decision, action, and verification context available for investigation and review.
What it helps identify
A wider view of suspicious execution
The endpoint can contribute signals across the behaviors that make malware dangerous, while preserving a clear boundary between sensing and consequential action.
Signals
Behavioral context
- Suspicious process and command patterns
- Script and LOLBin activity
- Injection and evasion indicators
- In-memory and fileless execution paths
Outcome
A governed decision
- Policy-defined prevention or observation
- Context for analyst investigation
- Bounded response through authorized effectors
- Evidence tied to the decision path
How it stays governed
Prevention without an unbounded black box
Spacetime keeps prevention inside the same control model as the rest of the platform: policy sets the boundary, the endpoint contributes evidence, and the resulting action remains reviewable.
Boundary · 01
Sense
Collect behavior signals with platform-aware privacy and evidence constraints.
Boundary · 02
Decide
Interpret the signal against prevention policy and declared operating intent.
Boundary · 03
Verify
Confirm the result and preserve the record needed to explain what happened.
Runtime-integrated surface
Feature extraction and CoreML scoring surfaces support behavioral malware prevention in the macOS agent path.
Maturity remains explicit
Model artifacts, observe-only constraints, dispatcher reachability, and installed-agent validation remain part of the production proof process. This page does not claim universal coverage or GA parity.
See the boundary
Discuss prevention in your environment
Review platform coverage, deployment conditions, evidence, and the maturity path with the Spacetime team.
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