SOAR Playbooks: What They Actually Automate and How to Build Them Effectively

Playbooks in SOAR: How Action Scenarios Truly Reduce Incident Response Time

Some of the challenges faced by SOC teams stem from a lack of repeatability. An analyst may spend several minutes checking the same things for every similar alert—logs, IP reputation, user activity, related incidents. Not because they don’t know the procedure, but because that procedure isn’t embedded in the tool.

Action scenarios in SecureVisio (playbooks) are designed to solve this problem. But to use them effectively, it’s important to understand what they consist of and where the nuances lie.

What an Playbook Is and What It Actually Automates

A playbook is a structured response plan—a set of steps, plans, and actions that the system executes for an incident or vulnerability. It is configured in the Desktop application under Response Plan → Playbook.

The key decision when building a scenario is: what should be executed automatically, and what should pause and wait for an operator. This can be configured at three levels—entire scenario, specific response plan, and individual step. This granularity matters.
A scenario that automates too much without oversight can be risky. A scenario that constantly pauses for approval loses its value.

Backtracking – The Most Underrated Feature

The Log Search action allows you to query logs or events within a defined time range as part of a scenario. The query syntax is similar to SQL.

The Condition field is a code block executed before the action—if the condition is not met, the action will not run. This is important: it allows you to tie backtracking searches to the incident context, for example, running only when ctx.DstUser is not empty.

Time range selection can be configured in multiple ways: day of the event, week before, month before, from today, incident duration, or custom. For most scenarios, “day of the event” or “incident duration” is sufficient. Timeout and maximum number of records are configurable—by default, 10 minutes and 1000 records.

The Answers section defines logical branches—what the system should do with the results. You can define numeric thresholds (e.g., “if more than 0 records found”) and route the scenario accordingly. The Process further if unmatched answers option ensures that lack of a match does not block the entire process—the scenario continues.

A well-configured backtracking search can answer in seconds what would normally take an analyst several minutes: Has this user logged into other machines before? Has this IP address appeared in logs in the past week?

Internal Knowledge Base — Context the System Already Knows

The knowledge base stores artifacts collected during incident handling: IP addresses, file hashes, malicious domains. It can also act as a baseline repository—for example, a list of expected system processes on a given host.

Scenarios include actions for querying this database (e.g., “Search Destination IP”, “Search source file hash”, “Analyze public DstIP collected from host”). This means the scenario can automatically check whether a given artifact has been seen before—and make decisions based on that.

The database is periodically updated by a ScriptWorker script. This is important for those planning integrations with their own threat intelligence—data must be regularly updated for searches to remain meaningful.

Reference Lists — Dynamic Whitelist and Blacklist in Action

Reference lists are collections of values (e.g., IP addresses) that scenarios can read from and write to. A typical use case: a scenario detects a suspicious IP address and automatically adds it to a blocked list, which is then used by a security rule.

Conversely, a reference list of trusted IPs (whitelist) can cause a scenario to skip certain assets without triggering remediation actions. The logic is simple, but the impact is significant: fewer false positives and less manual work for known exceptions.

AutoTriage — When a Scenario Replaces the First Layer of Analysis

AutoTriage is an example of a fully automated scenario—designed so that an analyst does not need to engage at the triage stage at all.

The scenario starts by checking whether related incidents for the same user (ctx.User) or IP address (ctx.IP) occurred on the same day with the same rule. If yes—it merges them into one. If not—it proceeds.

What happens next is a parallel series of automated analyses:

• assessment of potential business impact,
• network traffic anomaly analysis,
• comparison of user activity against baseline behavior,
• mapping to the MITRE ATT&CK framework,
• log and event search,
• integration with Threat Intelligence,
• analysis of infected files,
• verification against the knowledge base (e.g., processes on the host),
• analysis of the user account (ctx.User) and destination account.

This is not just a list of features—it is a complete triage procedure executed without human involvement. The analyst steps in only when expert judgment is required—not to click through routine checks.

What This Means in Practice

Action scenarios are effective only when thoughtfully designed. The platform itself doesn’t automate anything—it automates what has been defined within it.

It’s best to start with small scenarios containing a few backtracking searches and simple Answers logic. Gradually add integrations with the knowledge base and reference lists. AutoTriage is the end goal—but it requires a mature environment: well-tuned baseline rules, a populated knowledge base, and up-to-date threat intelligence sources.

A well-built playbook is repeatable, auditable, and independent of which analyst is on shift. That is its real value.