Adversary Emulation Library is a free threat simulation tool. Dorothy is a free threat simulation tool. Compare features, ratings, integrations, and community reviews side by side to find the best threat simulation fit for your security stack.
Based on our analysis of available product data, here is our conclusion:
Security teams building a testing program from scratch should start with Adversary Emulation Library because it's free, well-maintained, and maps directly to real adversary TTPs instead of generic control checklists. The library has 2,076 GitHub stars and covers MITRE ATT&CK techniques across multiple threat groups, giving you actual playbooks to run rather than vague scenarios. Skip this if your team lacks the time or expertise to operationalize emulation plans internally; you'll need engineers who can translate documentation into executable tests, not a turnkey platform that runs attacks for you.
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.
A library of adversary emulation plans to evaluate defensive capabilities against real-world threats.
Dorothy is a tool to test monitoring and detection capabilities for Okta environments, with modules mapped to MITRE ATT&CK® tactics.
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Common questions about comparing Adversary Emulation Library vs Dorothy for your threat simulation needs.
Adversary Emulation Library: A library of adversary emulation plans to evaluate defensive capabilities against real-world threats..
Dorothy: Dorothy is a tool to test monitoring and detection capabilities for Okta environments, with modules mapped to MITRE ATT&CK® tactics..
Both serve the Threat Simulation market but differ in approach, feature depth, and target audience.
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