AI Risk Management
AI Risk Management for the Agent Era
See every AI agent, govern its access, and stop machine insider risk at runtime.
See every AI agent, govern its access, and stop machine insider risk at runtime.
AI agents are a new class of risk.They hold credentials, move data at machine speed, and act without human approval; but most enterprise risk management programs were never designed to govern these non-human actors.
Effective AI agent risk management requires runtime truth: a real, evidence-based view of what every agent actually did, not what its configuration said it could do. Obsidian connects directly to AI platforms to inventory every agent, score its risk, and govern its access.
You cannot manage risk on agents you cannot see. Obsidian connects directly to AI platforms to surface every agent in a single, unified view — including who built it, what it can access, what it has done, and the tools and MCP servers it calls. Inventory is the foundation of AI risk management.
Most agents inherit far more access than they need. Obsidian scores risk for each agent based on its actual privileges, connections, and runtime behavior; surfacing toxic combinations, orphaned agents, and maker-mode escalation paths that legacy IAM tools cannot see.
Enforce policy with runtime guardrails that block privilege escalation, token abuse, and action chaining before damage is done; so every agent action safe, secured, and approved.
AI risk management is the practice of identifying, assessing, and controlling the security, privacy, and operational risks that AI systems introduce to an organization. For autonomous AI agents specifically, that means inventorying every agent, scoring its access and behavior, and governing what it can do across the platforms it touches.
AI agents move data at machine speed; up to 16× more than human users — and are typically granted 10× more access than their workflows actually need. If compromised or misused, an agent can exfiltrate sensitive data or chain actions across connected systems in seconds.
No. Traditional SaaS integrations usually have narrow, well-defined scopes. AI agents are different: they chain tasks across multiple apps, inherit broad OAuth privileges, and act on behalf of users without human approval. That autonomy makes them far more dangerous if left unchecked. The longer you wait, the faster the risks multiply.
SaaS applications are deeply interconnected, and AI agents amplify this by chaining actions across multiple platforms with little oversight. If one agent is compromised, attackers can pivot into other SaaS systems like Salesforce, Google Workspace, Slack, or Azure in minutes. AI agents expand the attack surface, creating an entirely new class of SaaS supply chain security risks—where exposure in one application can rapidly cascade across the enterprise.
SaaS-to-SaaS connectors pass data based on predefined rules. AI agents go further: they make decisions, execute actions across multiple apps, and often request excessive OAuth scopes. Their autonomy gives them far greater reach, making them a powerful accelerant for SaaS supply chain risks if abused.
Very quickly. Thousands of agents can appear in a matter of days. Some are auto-provisioned in seconds. Most launch without IT or security oversight. Left unchecked, these “shadow agents” spread silently, multiplying SaaS connections before anyone knows they exist. Obsidian provides visibility and control directly inside SaaS before that happens.
No. Legacy tools were designed for human-driven SaaS activity, not AI agents. They can’t see agent actions, connect them to OAuth privileges, or enforce least privilege in real time. Agents operate faster, with broader access, and create new supply chain risks that legacy tools can’t detect.
Obsidian connects directly to AI platforms to inventory every agent, score its access and behavior, and surface privilege escalation paths and toxic combinations. Security teams get one control plane across Microsoft Copilot, Salesforce Agentforce, Google Vertex, Bedrock, and other major platforms — without connectors or new agents to deploy. Runtime guardrails extend that visibility into deterministic enforcement.
No. Obsidian protects autonomous workflows directly inside SaaS. Guardrails run in real time, so teams can continue working and innovating safely.
