1stProtect.ai vs Dorothy: 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. Dorothy 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:
Okta security teams with detection gaps in their SIEM or XDR will find Dorothy's value in its free, attack-path testing that mirrors actual threat behavior instead of generic scanning. The MITRE ATT&CK mapping ensures your detection rules are validated against tactics adversaries actually use, not checkbox compliance. Skip Dorothy if you need continuous monitoring or remediation automation; it's a point-in-time validation tool, not a runtime detection layer.
Data verified Jun 2026
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1stProtect.ai
Runtime enforcement platform with 22 modules on one SIGMA engine, offline-capable.
Dorothy
Dorothy is a tool to test monitoring and detection capabilities for Okta environments, with modules mapped to MITRE ATT&CK® tactics.
Side-by-Side Comparison
Feature
1stProtect.ai
Dorothy
Pricing Model
Commercial
Free
Category
Detection Engineering
Detection Engineering
Verified Vendor
Open Source
GitHub Stars
191
Last Commit
Sep 2025
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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