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Soc Operations

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briiirussell
soc-operations

Build, run, and improve a Security Operations Center — alert prioritization, runbook authoring, escalation criteria, on-call structure, alert tuning workflow, MTTD / MTTR / fidelity KPIs, analyst tiering, and shift handoffs. Use when the user mentions 'SOC,' 'security operations,' 'SOC analyst,' 'alert triage workflow,' 'runbook,' 'escalation,' 'on-call,' 'SOC tiering,' 'tier 1 / tier 2,' 'MTTD,' 'MTTR,' 'alert fatigue,' 'alert tuning,' 'shift handoff,' 'SOAR,' or wants to design or improve a security operations team.

Overview

Publisherbriiirussell
Repositorycybersecurity-skills
Skill namesoc-operations
Stars
429
Forks
60
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by briiirussell on GitHub. Read the source before you install it.

Installation

Install the Soc Operations AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/briiirussell/cybersecurity-skills/tree/main/skills/soc-operations
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/briiirussell/cybersecurity-skills.git /tmp/cybersecurity-skills
mkdir -p .claude/skills
cp -r /tmp/cybersecurity-skills/skills/soc-operations .claude/skills/soc-operations
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Soc Operations in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Soc Operations on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Soc Operations is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

SOC Operations — Building and Running a Security Operations Center

The operations layer above siem-detection (engineering rules) and incident-triage (response). This skill is about the people and process of running 24/7 alert triage — alert prioritization, runbook authoring, escalation, on-call hygiene, MTTD / MTTR, and the slow drift toward alert fatigue that kills SOCs.

Three modes:

  • Build — designing a SOC from scratch (small org standing up its first IR capability, or MSSP onboarding)
  • Run — daily operations for an existing SOC
  • Improve — analyzing an existing SOC's metrics and fixing the broken parts

Cross-references: siem-detection (the rules that feed alerts to the SOC), incident-triage (the playbook for confirmed incidents), threat-hunting (proactive work between alert triage), breach-patterns (what attacks the SOC should be ready for).

Mode 1 — Build a SOC

Decision: in-house, MSSP, or hybrid?

ModelWhen it fitsPitfalls
Fully in-houseMature security org, ≥ 5 dedicated analysts, regulated industryHard to staff 24/7 with under 8 people; on-call burnout
Fully outsourced (MSSP)Smaller orgs, regulated requirements without internal staffingMSSP context drift — they don't know your business; alert tuning slow
Hybrid (MSSP Tier 1, in-house Tier 2+)Most common for growth-stage companiesHandoff complexity, "MSSP filtered it but didn't tell us" gaps

Staffing model

For 24/7 in-house coverage, the math:

  • 24 × 7 = 168 hours per week of coverage needed
  • One analyst at 40 hours/week (= 160 hr/yr × 50 weeks ≈ 8000 hr/yr - PTO - training ≈ 1700 productive hours)
  • Minimum 5 analysts for true 24/7 if no overlap; realistic minimum 6–7 to handle PTO and burnout
  • Below 6 — consider MSSP for off-hours coverage; the burnout cost of "always on" is real

Analyst tiering

Standard tier model (adjust to taste):

  • Tier 1 — Triage: initial alert review. Closes false positives with notes. Escalates real findings to Tier 2. Typically follows runbooks; deviates with documentation.
  • Tier 2 — Investigation: deeper analysis on escalations. Pivots across data sources, correlates events, decides "incident" vs "noise." Authors new runbooks for patterns Tier 1 should handle next time.
  • Tier 3 — Engineering & response: detection engineering (see siem-detection), threat hunting (see threat-hunting), incident response leadership (see incident-triage). Senior, expensive, the ones building the SOC's capability.

For small SOCs (≤ 4 analysts), the tiers collapse — every analyst does T1+T2 work, T3 is part-time or contracted. Don't pretend you have tiers if you don't.

Tools you actually need

  • SIEM for log aggregation and alerting (see siem-detection)
  • Case management — ServiceNow / Jira Security / TheHive / Tines workflow. Tickets, not Slack threads. Slack is for chatter; the audit trail is in the ticket
  • SOAR for playbook automation — Tines, Torq, Cortex XSOAR, Splunk SOAR. Only worth it after you have stable runbooks worth automating
  • EDR / NDR consoles the analyst can pivot into during triage
  • Asset inventory the analyst can look up — Snipe-IT, ServiceNow CMDB, Axonius
  • Documentation — a wiki where runbooks live (Notion / Confluence / GitBook). Not Slack DMs

Mode 2 — Run the SOC

Alert prioritization

When ten alerts land in five minutes, what's the order?

The default ranking (tweak per environment):

  1. Critical — confirmed compromise indicator (known-bad hash, C2 callback, ransomware behavior, data egress to known-bad infrastructure)
  2. High — credential-access patterns (LSASS dump, ticket forging), privileged-account unusual behavior, security-control disablement (EDR removed, audit log stopped)
  3. Medium — persistence indicators (new scheduled task, registry run key), discovery commands by service accounts, MFA failures spike
  4. Low — single-event anomalies, behavioral outliers without context
  5. Informational — context-rich events for correlation later, not actionable alone

Critical and High should never wait. Medium triages within shift (≤ 8 hours). Low and Info batched.

Runbook authoring

Every alert that fires more than 2-3 times needs a runbook. Without one, every analyst re-derives the response and quality varies.

Runbook structure:

markdown
# Runbook: [Alert name]
## Trigger: [exact SIEM rule / detection name]
## Owner: [team / person]
## Last reviewed: [date]

## Quick reference
- **What the alert means in plain English:** [one sentence]
- **Common false positives:** [list, with how to recognize]
- **Common true positives:** [list, with what to look for next]

## Triage steps
1. [Step 1 — specific query / action]
2. [Step 2]
3. [Decision point — true positive / false positive / escalate]

## False positive handling
- [How to close + what to document]
- [Whether to add to suppression list]

## True positive handling
- [Immediate containment if any]
- [Escalation to whom, with what info]
- [Link to incident-triage skill for full IR]

## Common pivots
- [Other data sources to check]
- [Other systems likely affected]

Runbooks live in version control or a versioned wiki — not in Slack DMs, not in individual analyst notes.

Escalation criteria

Escalation rules should be explicit, not "use your judgment." Judgment lives at Tier 3+; lower tiers need rules.

ConditionEscalate toHow quickly
Active data egress observedTier 2 / on-callImmediately
Privileged account behavior anomalyTier 2This shift
Multiple correlated alerts on one hostTier 2This shift
Detection rule firing > 50× / hour with high TP rateTier 3 (engineering)Next business day
Detection rule firing > 50× / hour with 100% FPTier 3 (engineering)Next business day
Anything Tier 1 doesn't know how to handleTier 2After 30 minutes of triage

Shift handoffs

The single most preventable cause of breaches detected days late is "the night shift had something interesting and the morning shift never heard about it."

Handoff checklist (5–10 minutes per shift):

  • Open cases — what's in progress, what's blocked, what's the next step
  • Watch items — anything not yet a case but worth keeping eyes on
  • Active tuning — rules under tuning, FP patterns being investigated
  • Pages received during shift — even if resolved, the next shift should know
  • Anything you decided to ignore — and why — so next shift doesn't quietly disagree without context

Write it down. Slack handoff channel, daily summary doc, ticketing system shift report — any format works as long as it's persistent and searchable.

Mode 3 — Improve the SOC

KPIs that actually matter

MetricDefinitionTarget
MTTDMean Time To Detect — from event to alert firing< 5 min for high-confidence rules; < 1 hr for behavioral
MTTRMean Time To Respond — from alert to triage decisionTier 1: < 15 min for Critical; < 4 hr for Medium
MTTCMean Time To Contain — from confirmed incident to spread halted< 1 hr for confirmed compromise (industry P50 is ~6 days; aspire higher)
TP rate per ruleTrue positives / total alerts> 30% for any rule; tune or kill rules below
Alert volume per analyst per shiftAlerts per Tier 1 analyst per 8-hour shift< 25 — above that, fatigue dominates
Coverage by ATT&CK tacticTactics with at least one detection ruleAim for 100% Initial Access, Execution, Persistence, Defense Evasion, Credential Access
Runbook coverage% of alerts that have runbooks> 80% of alert volume
Time to runbookNew alert-type to runbook delivered< 5 alerts of the new type

Don't measure things you can't act on. "Number of alerts processed" is a vanity metric — it goes up with noisier rules.

The tuning loop

The dominant SOC failure mode is alert fatigue from un-tuned rules. The loop that prevents it:

  1. Weekly: review top-N rules by alert volume
  2. For each high-volume rule: what's the TP rate? If < 30%, the rule is broken — tune or retire
  3. Retire vs tune: if the rule's underlying concept is sound, tune (add filter, increase threshold, add allow-list); if the concept is unsound (anomaly that's normal in your environment), retire
  4. Document every retirement — future engineers will want to know why the rule went away
  5. Track tuning cycles — "rule X tuned 3 times in 6 months" means the rule concept is wrong, not the parameters

See siem-detection's tuning section for the engineering side; this is the operations side.

Alert fatigue diagnostic

Symptoms your SOC is suffering:

  • Tier 1 analysts closing alerts in < 30 seconds (not investigating, just clicking through)
  • Same alert types ignored repeatedly without documented suppression
  • Analyst turnover > 25% / year
  • "We didn't catch X" post-mortems pointing to an alert that fired but wasn't actioned

When you see these: full-stop the new-rule pipeline and spend a cycle on tuning. Adding more rules to an over-firing SOC makes things worse.

Output Format

markdown
# SOC Assessment / Build Plan
## Organization: [name]
## Mode: Build / Run / Improve
## Date: [date]

### Current state (or proposed)
- Coverage hours, staffing model
- Tier structure
- Tools in use
- Alert volume / day
- Key metrics — MTTD, MTTR, TP rate distribution

### Findings (Improve mode) / Gaps (Build mode)
| Category | Issue / Gap | Severity |
|----------|-------------|----------|

### Recommendations
| Priority | Item | Owner | Timeline |
|----------|------|-------|----------|

### KPI dashboard proposal
[What to measure, how to source it, target thresholds]

### Runbook backlog
[Alert types that lack runbooks, ranked by volume]

Boundaries

  • This skill produces operations plans, not exploitation
  • Refuse to design SOC capabilities for unauthorized surveillance of employees or third parties
  • Alert tuning that intentionally hides legitimate security events is a finding, not a deliverable
  • Don't help build "compliance-theater" SOCs — if the org's intent is "check the box without actually detecting," push back
  • Where the assessment surfaces an active incident, hand off to incident-triage — don't continue planning work mid-fire

References

  • NIST SP 800-61 Rev. 3 (Computer Security Incident Handling Guide)
  • "Crafting the InfoSec Playbook" — Bollinger / Enright / Valites
  • "The Practice of Network Security Monitoring" — Richard Bejtlich
  • "Intelligence-Driven Incident Response" — Brown / Roberts
  • SANS SOC Survey (annual)
  • Gartner Magic Quadrant for SIEM (rotating — use the current edition)
  • ATT&CK for SOC analysts — attack.mitre.org/resources/training
  • MITRE D3FEND — defensive countermeasures catalog
  • "SOC Maturity Model" — various — pick one and measure against it

Frequently asked questions

What does the Soc Operations AI skill do?

Build, run, and improve a Security Operations Center — alert prioritization, runbook authoring, escalation criteria, on-call structure, alert tuning workflow, MTTD / MTTR / fidelity KPIs, analyst tiering, and shift handoffs. Use when the user mentions 'SOC,' 'security operations,' 'SOC analyst,' 'alert triage workflow,' 'runbook,' 'escalation,' 'on-call,' 'SOC tiering,' 'tier 1 / tier 2,' 'MTTD,' 'MTTR,' 'alert fatigue,' 'alert tuning,' 'shift handoff,' 'SOAR,' or wants to design or improve a security operations team.

Why use Soc Operations on TypingMind?

Because you install it once and use it with any model. Soc Operations is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Soc Operations in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/briiirussell/cybersecurity-skills/tree/main/skills/soc-operations. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Soc Operations?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Soc Operations?

As many as you like. As long as a model supports skills, you can use Soc Operations with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Soc Operations AI skill free?

Yes. It is published on GitHub by briiirussell under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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