Prompt Injection
Instructions cross a trust boundary.
Enterprise AI Security & Assurance
Put autonomous AI into production without losing control.
Orbyntis helps CIOs, CISOs, and technology leaders make agent authority visible, controls testable, and every critical action reviewable.
Authority VisibleControls TestedEvidence Reviewable
SAP SystemsData & Knowledge
Agent
AI Ecosystems
Tools & Actions
AUTONOMOUS AI ASSURANCE
AgentShield
Test agent authority before critical actions reach production.
Explore AgentShieldAUTONOMOUS AI ASSURANCE
Evidence Vault
Keep the evidence behind every reviewable decision.
Explore Evidence VaultAUTONOMOUS AI ASSURANCE
Govern
Turn policies into explicit permissions and operating limits.
Explore GovernAUTONOMOUS AI ASSURANCE
CI Gate
Bring assurance checks into the software delivery workflow.
Explore CI GateAUTONOMOUS AI ASSURANCE
Runtime Guard
Observe agent activity and control runtime risk.
Explore Runtime GuardApproved Technology Partners
MicrosoftAI Cloud Partner
Orbyntis AI Security Lab
See where autonomous authority becomes exposure.
Explore one architecture through 15 private, in-browser questions.Directional, not a certification.
Guided Exposure Check
One workflow.
Five control layers.
Answer from the perspective of the highest-impact agent you operate or plan to deploy.
- 01Context
- 02Authority
- 03Reach
- 04Controls
- 05Evidence
No responses leave this page.
Directional Exposure Index
0/100
Exposure mapped
Calculated only from the 15 answers above. This is not a vulnerability scan, certification, or compliance determination.Threat Exposure Map
Which paths are relevant to your architecture?
Select any combination. The map shows exposure paths to review—it does not claim that a selected platform is vulnerable.
Platforms & Frameworks
Agent Capabilities
Selected ArchitectureChoose your stack aboveSelections stay in this browser.
ORBYNTIS CONTROL VIEWAUTHORITYPOLICYEVIDENCE
Relevant Exposure Paths0
Select a platform or capability to begin.
Indirect Injection
External content influences agent behavior.
Tool Abuse
A valid tool is used outside intended purpose.
Unsafe Execution
Actions change systems without a sufficient gate.
Data Leakage
Sensitive context reaches an unintended destination.
Memory Poisoning
Stored context changes later decisions.
Agent Escalation
Delegated authority exceeds the initiating scope.
Identity Spoofing
Action ownership becomes ambiguous.
Privilege Escalation
Agent rights exceed least privilege.
Model Jailbreak
Policy behavior is intentionally bypassed.
Supply-Chain Risk
External models, tools, or content alter trust.
MCP Risk
Server authorization and tool scope need review.
Tool Poisoning
Tool metadata or behavior becomes hostile.
Evidence Gap
Critical actions cannot be reconstructed.
What Changes Before AI Acts
Make authority visible. Make control provable.
Three questions matter before an autonomous system reaches production.
Know the boundaryWhat may the system access, decide, and change?Map what the system may access, decide, and change.Learn More
Test the pressureWhere can misuse paths bypass the intended control?Exercise misuse paths before they become operational incidents.Learn More
Prove the controlWhat evidence proves the action stayed accountable?Leave reviewable evidence for engineering and governance teams.Learn MoreFive products.
One assurance path.
Start with the risk you need to understand. Expand only when you are ready.
AgentShield
Assess exposure before AI acts.
Map permissions, tools, memory, identity, and action boundaries--then test where control can fail.
Explore AgentShield
Evidence Vault
Keep assurance evidence reviewable.
Organize the evidence created through assessment, validation, and operational review.
Explore Evidence Vault
Govern
Make ownership and approval explicit.
Connect AI actions to clear decision rights, review points, and accountable operating roles.
Explore Govern
CI Gate
Test assurance as systems change.
Bring repeatable control validation into the delivery path before higher-risk changes move forward.
Explore CI Gate
Runtime Guard
Keep authority visible in operation.
Support runtime review and response around sensitive tools, actions, and business workflows.
Explore Runtime Guard
Services
Engineering depth where assurance needs it.
Explore only the service relevant to your immediate risk.
Enterprise AI Consultation & Engineering
Plan and engineer enterprise AI workflows with clear security boundaries, operating controls, and production-readiness criteria.
- A documented target architecture and trust-boundary map
- Prioritized engineering and security requirements
AI Red Teaming
Test AI agents and autonomous workflows for prompt injection, tool misuse, data exposure, control bypass, and unsafe business actions.
- A threat-informed adversarial test plan
- Evidence-backed findings ranked by business impact
Agent Security & Runtime Risk Assessment
Assess AI agent permissions, tools, memory, context, identity, approvals, and runtime controls before business-critical deployment.
- An inventory of agent capabilities and trust boundaries
- A risk-ranked control-gap assessment
Secure Software Development
Engineer security-conscious AI applications, integrations, automation, and remediation for enterprise environments.
- Security requirements translated into working software
- Reviewable integration and control patterns
AI Governance, Observability & Compliance Advisory
Translate enterprise AI risk into accountable governance, operational evidence, monitoring, and compliance-ready review practices.
- Clear ownership and approval responsibilities
- Defined runtime evidence and review requirements
How It Works
A practical path from unclear autonomy to controlled operation.
Orbyntis work starts by making the agent boundary explicit, then turns risk into engineered controls, validation evidence, and operating ownership.
- 01Assess
Map authority
Define the agent, users, identities, data, tools, approvals, and business actions in scope.
OutputWorkflow boundary and authority inventoryExplore this stage - 02Threat Model
Find misuse paths
Connect prompt, context, identity, tool, and approval risks to business impact.
OutputThreat scenarios and control assumptionsExplore this stage - 03Engineer
Build controls
Place deterministic checks around sensitive actions instead of relying only on model behavior.
OutputControl plan and remediation backlogExplore this stage - 04Validate
Prove the change
Exercise realistic failure paths and confirm controls hold under adversarial or degraded conditions.
OutputTest evidence and validation resultsExplore this stage - 05Operate
Review evidence
Keep ownership, logging, containment, and reassessment tied to material workflow changes.
OutputOperating cadence and evidence trailExplore this stage
Learn AI Security
Move from concern to a testable risk boundary.
Use these evergreen guides to understand autonomous AI threats, agent security decisions, enterprise patterns, and common assurance questions.
Agent Foundations
AI Agent Security
A practical hub for authority, tools, identity, context, controls, and runtime evidence.
- Agent identities and permissions
- Tool access and context boundaries
- Runtime controls and reviewable evidence
Threat Research
Autonomous AI Threat Library
Threat families for agentic workflows, mapped to business impact and control questions.
- Prompt injection and poisoned context
- Excessive permissions and unsafe tool use
- Approval bypass and audit gaps
Connected Tools
MCP Security
Server, tool, testing, prompt injection, and data exposure guidance for MCP-connected agents.
- MCP server and tool security
- Prompt injection and data exposure
- Testing connected agent workflows
Retrieval Security
RAG Security
Retrieval testing, prompt injection, and data leakage guidance for enterprise AI systems.
- Retrieval trust boundaries
- Indirect prompt injection
- Data leakage and security testing
Common Questions
AI Security FAQ
Short answers to common questions about agent security, red teaming, approvals, and evidence.
- Agent security and red teaming
- Human approvals and ownership
- Evidence and assurance decisions
Enterprise Patterns
Enterprise Case Studies
Anonymous patterns from AI risk, red teaming, governance, and assurance work.
- Enterprise context and assessment scope
- Control areas and deliverable patterns
- Lessons that generalize without exposing customer details
Bring us the system you need to trust.
Start with a focused briefing. Leave with a clearer assurance path.
Request a Briefing