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What each service does in an alert-triage workflow
“Deep-sea” is not a documented Google SecOps product or feature name. The documented workflow involves Google Security Operations (Google SecOps), Vertex AI, and, for certain ingestion tasks, Cloud Run functions. Chronicle still appears in some documentation paths and API names.
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These components have different roles. Vertex AI integration lets a playbook use generative prompts and return results to workflow logic. TIN is a separate, built-in investigation agent for eligible alerts. Cloud Run functions can run example scripts to ingest selected feeds, but Google documents a checkpointing limitation that can cause incomplete ingestion in stateless environments.
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|---|---|---|---|
| Vertex AI integration | Custom AI steps in playbooks | Run prompts and support contextual entity summaries, EML analysis, and JSON transformations. | Requires service-account and IAM setup plus API root, project, model, and location configuration. It is not the same feature as TIN. |
| Triage and Investigation Agent (TIN) | Built-in alert investigation | Return a true- or false-positive verdict with a supporting summary; use documented tools such as SecOps searches, GTI enrichment, command-line explanations, and process-tree reconstruction. | Runs on data ingested through Google SecOps SIEM, not alerts arriving through a Google SecOps SOAR connector. Tenant eligibility and permissions must be checked. |
| Cloud Run functions | Selected feed-ingestion tasks | Run example scripts for ingesting threat-intelligence indicators from sources such as STIX/TAXII and MISP. | Not described as the triage engine. The example scripts lack checkpointing and may omit logs in a stateless environment. |
Decide which AI path fits the alert
Use TIN for supported investigations
TIN is the direct option when an alert is eligible for its built-in investigation. Google describes it as determining whether an alert is a true or false positive and summarizing its reasoning. The documented investigation tools include dynamic searches in SecOps, GTI enrichment, command-line explanation, and process-tree reconstruction. Treat the verdict and summary as evidence for a decision, not as proof that an alert is harmless.
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The TIN guide describes an average investigation time of 60 seconds and a maximum of 20 minutes. Those are Google’s operational figures, not an independently audited performance guarantee or a latency SLA. Confirm that the tenant and alert pathway are supported before designing around the agent.
Use Vertex AI integration for custom playbook logic
Choose the Vertex AI integration when the workflow needs a custom prompt or AI output that a playbook can use in its own branches. The documented capabilities include contextual entity summaries, EML analysis, and JSON transformations. A playbook can combine those results with deterministic steps, such as routing a case for escalation or additional review.
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Google strongly recommends using generally available (GA) models in production. Preview models may be unstable, change incompatibly, or have limited support. The integration also requires service-account and IAM configuration. Its configurable parameters include the API root, project, model, and location; validate the values and access in the target environment rather than assuming a particular model or region is available.
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Build a triage flow analysts can control
1. Put urgent alerts in an actionable queue
Start with assigned cases and the broader case queue. Google’s response guidance recommends filtering for Critical and High priority alerts and checking that alerting is enabled for the relevant detections. Make ownership and priority visible before adding AI; an investigation result is less useful if no person or response path is accountable for it.
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- FAST & CONVENIENT LOGIN: Plug in your Security Key NFC via USB-A and tap it, or tap it against your phone (NFC) to authenticate. No batteries, no internet connection, and no extra fees required.
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2. Enrich the alert with relevant context
Review the involved assets, identities, and related entities, including their risk context. Google SecOps investigation features describe event enrichment and contextual information for related entities. Use related searches and available indicator enrichment to give the analyst evidence beyond the alert’s initial summary.
3. Separate evidence gathering from consequential action
Let AI summarize evidence or propose a routing path, then use explicit playbook conditions to distinguish escalation from further review. Keep deterministic checks around high-impact actions. Google documents manual approval steps for sensitive operations such as host isolation, file detonation, and IP blocking. Require analyst confirmation when a mistaken action could disrupt a user or system.
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4. Preserve a reviewable decision trail
Keep the alert, supporting evidence, AI output, branch conditions, and any human approval associated with the case according to the organization’s audit and retention requirements. The documented material does not establish a universal logging configuration or retention period, so verify those controls in the tenant and playbook design. Do not treat a model-generated explanation alone as a complete audit record.
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Plan for capacity without combining unlike quotas
Google documents two different throughput descriptions for different contexts. Agentic Automation in playbooks is limited to up to five automatic investigations per hour, subject to Gemini resource availability and Vertex AI capacity. Google’s broader response guide describes TIN as typically handling around ten investigations per hour per tenant, including manual and automatic triggers as examples. These figures are not interchangeable or a universal promise; confirm current tenant eligibility, quota, and capacity before relying on a throughput target.
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Google’s response guide also says AI-powered triage can condense 15–20 minutes of manual work into a shorter timeframe. This is a Google product-documentation claim, not an independent benchmark. Test the workflow against the organization’s own alert mix and review requirements before using it to set staffing or response-time expectations.
Use Cloud Run cautiously for ingestion
Cloud Run functions belong upstream of triage when used to ingest selected threat-intelligence feeds. Google warns that its example scripts lack checkpoint functionality and may not send all logs when run in a stateless environment such as Cloud Run functions. Missing records can undermine subsequent searches and investigations, so verify feed completeness and ingestion health rather than assuming a successful function run means every event arrived.
Google recommends Chronicle API for ingestion instead of the deprecated Ingestion API. The documentation states that the Ingestion API is scheduled for discontinuation on July 20, 2027. If an existing workflow uses that API, plan a migration and validate the replacement path before the scheduled date.
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Quick Recap
Check eligibility, privacy, and compliance before enabling automation
- Confirm that the tenant, alert source, permissions, and required service configuration support the chosen route. TIN’s documented support is specific; it does not cover alerts from a Google SecOps SOAR connector.
- For Vertex AI integration, verify service-account permissions and the configured API root, project, model, and location. Use GA models for production workflows in line with Google’s recommendation.
- Confirm data-handling and compliance requirements before sending security content to an AI workflow. Google states that TIN is not FedRAMP or CMEK compliant.
- Keep human approval for actions whose false-positive cost is high, and establish a way to inspect the evidence behind an AI-assisted decision.
- Validate tenant-specific quotas and current feature availability; do not infer a fixed rate or entitlement from general documentation.
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