Find AI security gaps before attackers do
Help security leaders test agent, workflow, and model risks before production exposure creates business impact.
Why teams need this
AI systems introduce new failure paths across prompts, tools, data access, workflows, and human handoffs that traditional app testing can miss.
What you can do with it
Assess agent behavior; test misuse paths; review tool permissions; prioritize risk remediation; prepare leadership-ready findings.
Capabilities in plain language
A decision-maker summary; implementation detail lives in the linked resources.
AI threat discovery
Find likely agent, workflow, and model abuse paths before real attackers or unsafe users expose them.
Misuse-path testing
Test realistic misuse scenarios in a controlled review process that produces business-readable findings.
Permission review
Review who and what an AI workflow can access so excessive permissions become visible before launch.
Remediation planning
Prioritize fixes, owners, and retest expectations so security findings become governed remediation work.
How it fits with the Apotheon platform
Ares strengthens the Apotheon platform by testing AIOS workflows, Hermes integrations, Thea content flows, and custom GenAI products before they move into wider use.
Proof and trust
Technical deep-dive links
Architecture diagrams, implementation patterns, and deeper security/compliance detail are kept in linked resources so this page stays outcome-first.
- AI-native transformation guide for business-case and operating-model context.
- Governance runtime whitepaper for architecture, controls, and implementation depth.
- AI compliance proof patterns for technical assurance details.
Ready to assess AI security risk?
Talk with Apotheon about fit, risks, proof requirements, and the fastest governed next step.