Every tool call is a new entry point
Agents chain tools, call APIs, and take autonomous actions across systems. Each new connection needs to be discovered, scored, and governed-not assumed safe.
By business need
Turn agent risk into a number you can act on.
Every new agent and every new tool connection expands your attack surface. Risk management means scoring that surface, detecting deviation the moment it happens, and containing it before it becomes an incident report.
Why it matters
Agents multiply your attack surface faster than reviews can keep up
Goal hijacking and memory poisoning are new threat classes
Agents ingest untrusted context from documents, tools, and the open web. Attackers exploit that ingestion path in ways traditional security tooling was never built to catch.
Compliance pressure is only increasing
The EU AI Act, NIST AI RMF, and ISO 42001 require documented controls and audit trails tied to every agent action, not a policy statement.
What Lineation does
Risk management as a runtime capability, not a quarterly review
Risk scoring calibrated to baseline
Every agent is scored against its own normal behavior, so anomalies stand out instead of drowning in noise.
Real-time threat detection
Prompt injection, exfiltration attempts, and tool misuse are flagged as they happen, not discovered in a post-mortem.
Policy enforcement with default-deny
High-risk actions require an explicit allow. Anything outside defined policy is denied and logged.
Compliance-ready audit trail
Every score, detection, and decision is captured for export to auditors, regulators, and your own security team.
How it works
From baseline to contained, in real time
Baseline normal behavior
Each agent's typical calls, data access, and volume become its own reference point.
Detect deviation
Injection attempts, unusual tool calls, and data access outside the baseline are flagged immediately.
Contain automatically
Policy determines whether the action is blocked, sanitized, or routed for approval.
Escalate to case management
Flagged events open a case with full context-no manual log correlation required.
Export evidence
Cases and decisions export to your SIEM/SOAR and to compliance-ready reports.
FAQ
Common questions
What is agentic AI risk management?
Identifying, scoring, and controlling risks created by autonomous AI agents across their lifecycle-discovery, scoring, detection, enforcement, and compliance evidence.
What's the difference between agentic and generative AI risk?
Generative AI produces content in response to a prompt. Agentic AI takes autonomous actions and chains decisions, so risk compounds with every additional tool call.
What frameworks does this map to?
NIST AI RMF, the EU AI Act, ISO 42001, and SOC 2, with exportable evidence for internal and external review.
How does risk scoring avoid high false positives?
Scoring is calibrated against each agent's own baseline rather than one global threshold, so normal high-volume behavior isn't flagged as risk.
Can this integrate with our existing SIEM?
Yes-detections and case records export to the SIEM and SOAR tooling you already run.
What happens when a risk threshold is crossed?
The action is blocked, sanitized, or routed to an approval gate per policy, and a case opens automatically with full context.
Related use cases
Keep exploring
See your riskiest agent before it becomes an incident.
Baseline, score, and contain agent risk in real time-not in next quarter's review.