The AI security platform built for agents, not just prompts.
Test, map, and prove the security posture of LLM apps and autonomous agent workflows.
Agent Security Scanning
Run 100+ agentic security probes against any LLM endpoint. Detect prompt injection, tool misuse, and data leakage — each probe targets a real-world failure mode.
- Prompt injection detection across system prompts and tool inputs
- Tool misuse chains that cross intended capability boundaries
- Data leakage through side channels and memory reads
- Regression reruns that test only previously failed probes
POST /v1/scans | async worker queueAdversarial Simulator
Compose tool-call sequences and see exactly where your policy enforcement breaks. The risk graph scores each transition for escalation potential before an attacker finds it.
- Models tool-to-tool transition risk (e.g. browser.fetch to filesystem.write)
- Scores chains by overall risk: low > medium > high > critical
- Attack path visualization with remediation hints per edge
- Pre-built scenario presets: data exfiltration, privilege escalation, prompt injection
ToolRiskGraph engine | cross-tool transition scoringCompliance Mapping
Every finding automatically maps to SOC 2, HIPAA, ISO 27001, and more. Export evidence packages that tie probe results directly to control requirements.
- Auto-map findings to multiple frameworks simultaneously
- Framework-specific evidence packages for audits
- Track remediation status per control requirement
- Historical compliance posture trends over time
ComplianceMapper engine | multi-framework supportProvider Differential Testing
Run identical probe sets across LLM providers and see which models resist which attacks. Make informed decisions about model selection based on security posture, not just benchmarks.
- Side-by-side comparison of provider security postures
- Identify model-specific vulnerabilities across providers
- Track provider security regressions over time
- Export comparison reports for procurement decisions
ProviderDiffTesting | cross-provider probe normalization | report exportGuardrail Enforcement Testing
Before deploying guardrails into production, test them against actual attack patterns. Orithos validates that your policy enforcement boundaries block the right sequences and allow legitimate traffic.
- Test guardrail rules against real attack patterns
- Identify enforcement gaps before they're exploited
- Validate policy updates with regression probe runs
- Integration with existing policy-as-code workflows
Guardrail policy engine | rule evaluation | regression testingRemediation Reruns
When a probe finds a vulnerability, fix it and rerun only the failed probes - not the entire suite. Regression testing for your AI security posture, without the wait.
- Rerun only failed probes from previous scans
- Track remediation status per finding
- Audit trail of before/after states for compliance
- Integrates into CI/CD for automated security gates
Scoped rerun engine | audit event logging | CI/CD integrationReady to probe your AI attack surface?
Join the waitlist for early access and guided onboarding.