Agentic AI Security Guide / Monitoring & Incident Response

Monitoring & Incident Response

Visibility is essential for detecting attacks and responding to incidents. Implement comprehensive telemetry and AI-specific incident response procedures.

11.1 Structured Telemetry and Immutable Audit

For each agentic task, log at least:

Identity

  • User ID (or pseudonymous ID), role
  • Tenant/organization
  • Agent ID and version

Request

  • Timestamp, environment, region
  • User prompt (sanitized: PII/secrets redacted)
  • High-level context (e.g., retrieved doc IDs, not full content)

Actions

  • Tools called, parameters (sanitized)
  • Data domains touched (e.g., which tables/collections/indices)
  • Guardrails triggered and decisions taken

Outcome

  • Final agent output (sanitized)
  • Status (success, blocked, error)
  • Any policy violations or escalations

Store logs in append-only or tamper-evident storage (WORM, hash-chaining, or signed logs) with retention aligned to regulatory needs.

11.2 Behavioral Monitoring and AI-Specific Detection

Establish baselines per agent:

  • Normal tool usage frequency and mix
  • Typical data volumes and classifications accessed
  • Usual response lengths, latency, and patterns

Monitor for Anomalies

  • Sudden spikes in:
    • High-risk tool calls
    • Bulk exports
    • Guardrail violations
  • Unusual times or geographies for activity
  • Sudden shifts in agent behavior (e.g., tone, recommendations, systematic policy deviations)

Detect AI-Specific Threats

  • Repeated prompt injection/jailbreak attempts
  • Cross-tenant access attempts
  • Data exfiltration patterns (e.g., large responses, repeated "list all" requests)
  • Abuse of code-exec or generic HTTP tools

11.3 Automated Safeguards

Implement automatic controls such as:

Circuit Breakers for Agents

If error or violation rate crosses thresholds:

  • Disable the agent or switch to a degraded mode (read-only, no tools).

Adaptive Security Posture

In high threat levels:

  • Disable risky tools
  • Tighten rate limits
  • Force human approval for actions that are normally automated

Quarantine Modes

For suspicious users or tenants, move them to stricter policies and manual review.

11.4 AI-Specific Incident Response

Treat AI incidents as first-class incidents, integrated with security operations.

Common Incident Classes

  • Data leakage (PII/secrets/confidential data)
  • Tool misuse or unauthorized changes (e.g., records deleted, config modified)
  • RAG/memory poisoning
  • Unsafe or harmful outputs in production
  • Provider compromise or misconfiguration

For Each Class, Define:

1. Detection

Which alerts or metrics indicate the problem?

2. Containment

  • Disable affected agents/tools.
  • Revoke or rotate credentials.
  • Apply network lockdown if needed.

3. Triage & Analysis

  • Scope: which tenants/users/data, how long, via which flows.
  • Root cause: injection, misconfig, code bug, infra compromise.

4. Remediation

  • Fix code/policies or patch components.
  • Clean or roll back poisoned memory/RAG indices.
  • Restore systems under stricter observation.

5. Communication

  • Notify internal stakeholders.
  • For regulated or contractual obligations, notify customers/regulators as required.

6. Learning & Improvement

  • Update threat models, test suites, guardrails, and runbooks.