1stProtect.ai vs EQL Analytics Library: Side-by-Side Comparison (2026)
Features, pricing, ratings, and pros & cons — compared head-to-head.
1stProtect.ai is a commercial detection engineering tool by 1stProtect.ai. EQL Analytics Library is a free detection engineering tool. Compare features, ratings, integrations, and community reviews side by side to find the best detection engineering fit for your security stack.
CST VerdictBased on our analysis of core features, integrations, here is our conclusion:
Threat hunters and detection engineers at Elastic Stack shops should use EQL Analytics Library because it maps 168 community-maintained detection rules directly to MITRE ATT&CK behaviors without the licensing friction of closed vendor rule sets. The rules are free, version-controlled on GitHub, and immediately deployable in your existing Elastic cluster. Skip this if your team lacks EQL fluency or runs a detection program centered on proprietary SIEMs; these rules won't port cleanly outside the Elastic ecosystem.
Data verified Jun 2026
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1stProtect.ai
Runtime enforcement platform with 22 modules on one SIGMA engine, offline-capable.
EQL Analytics Library
A library of event-based analytics written in EQL to detect adversary behaviors identified in MITRE ATT&CK, providing detection rules for the Elastic Stack.
Side-by-Side Comparison
Feature
1stProtect.ai
EQL Analytics Library
Pricing Model
Commercial
Free
Category
Detection Engineering
Detection Engineering
Verified Vendor
Open Source
GitHub Stars
168
Last Commit
Jan 2021
Company Information
Company
1stProtect.ai
Headquarters
Founded, Size & Funding
Use Cases & Capabilities
Runtime Security
Sigma
Ransomware Prevention
Data Exfiltration
Process Injection
Syscalls
Kubernetes Security
Active Directory
MCP Security
USB Security
MITRE Attack
Detection Rules
NIST CSF 2.0 Coverage
NIST CSF 2.0 Mapping
Access NIST CSF 2.0 data from thousands of security products via MCP to assess your stack coverage.
Access via MCPCore Features
- Single user-space SIGMA engine replacing multiple legacy security engines (EPP, EDR, DLP, IAM, ITDR, SASE)
- 22 protection modules covering credential theft, ransomware, data exfiltration, process injection, browser attacks, and agent self-defense
- Offline-first policy enforcement with local policy engine cached in kernel memory — no cloud dependency required
- Sub-0.04ms threat enforcement latency with less than 1% CPU overhead, no kernel modules
- On-host MCP server for AI-based forensic investigation without cloud round-trip
- Immutable forensic snapshots captured at syscall level with JSON-structured telemetry
- Kubernetes DaemonSet deployment with no sidecars and no kernel module compilation
- Audit Mode for policy baselining before switching to active enforcement
- No features listed
Integrations
Splunk
Datadog
Elastic
Sumo Logic
Okta
Azure AD
Ping
JumpCloud
AWS
GCP
No integrations listed
Community
Community Votes
0
0
Bookmarks
User Reviews
No reviews yet
No reviews yet
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