Description

A focused course, tailored for you

Product Security Engineer Static-Analysis Triage Playbook

Name: Product Security Engineer Static-Analysis Triage Playbook
Price: 199 USD
Availability: InStock

Run a credible product-security static-analysis programme end to end, from rule authoring to triage SLAs to engineer hand-off.

Your queue of unreviewed taint findings is the work. The rules that produce them are half-scoped. The engineers downstream of you will accept or mute based on how the hand-off reads, not the severity field. This is the playbook for running the programme so finding rate, triage time, and fix rate all track.

$199 one-time

Tailored to your situation. Access within 24 hours. 30-day money-back.

Includes a hand-built implementation playbook delivered alongside course access, generated for your specific situation.

Why this course

Product security engineers at platform companies inherit a static-analysis estate that someone else built and stopped tuning. CodeQL queries, Pysa models, Semgrep rules, secret scanners, SCA, sometimes all five running on overlapping scopes. Each tool has its own queue. The model owners have moved on or scope-creeped into another team. The triage backlog grows faster than you can clear it, and the engineers downstream learn that muting a finding has no consequence because nobody is tracking mute rates per rule. Meanwhile a real injection slips through because it was the 312th finding that quarter and the reviewer was working through volume, not signal. The fix is not another tool. It is a programme: rule ownership, scope discipline, triage SLAs tied to severity, false-positive budgets per rule, hand-off templates that engineers actually action, and an evidence trail an internal auditor or a customer security questionnaire can read in fifteen minutes. The course teaches you to run that programme.

What you walk away with

Author scoped source-to-sink rules in your tool of choice that produce a defensible signal-to-noise ratio on first run.
Operate a triage queue with severity-tied SLAs, per-rule false-positive budgets, and mute-rate alerting that survives an incident week.
Hand off findings to product engineers in a form they fix rather than mute, with templates the engineering org has already pre-agreed.
Stand up an evidence trail that answers customer security questionnaires and internal audit requests without a manual scramble.
Run the quarterly programme review with the data that shows where rules need retirement, retuning, or new authorship.

The 12 modules

Module 1. Programme shape: what a credible product-security static-analysis programme actually looks like

What separates a tool deployment from a programme. Rule ownership, scope discipline, queue management, hand-off, and evidence as five named responsibilities with named owners. The org-chart shapes that work and the ones that quietly collapse to one overworked engineer. How to write the one-page programme charter that gets your leadership to fund the work rather than asking why the queue is so long.

Module 2. Authoring scoped source-to-sink rules across CodeQL, Pysa, and Semgrep

The discipline of starting from a concrete vulnerability class and ending with a rule that produces a defensible signal-to-noise ratio. Worked examples in three query languages covering SQL injection, SSRF, deserialization, and authorization bypass. How to bound a source set so the rule does not light up every parameter in the monorepo, and how to bound a sink set so it catches the real call sites without catching every logger that happens to take a string.

Module 3. Rule scoping and false-positive budgeting per rule

Why every rule needs a published false-positive budget and a retirement criterion before it ships. The budget table that maps rule severity to acceptable noise. How to instrument findings so you know per-rule FP rate at the end of each quarter without manual sampling. The conversation with a rule author when their rule is over budget and the playbook for retirement, retuning, or scope reduction.

Module 4. Queue triage SLAs tied to severity and exploitability

The SLA matrix that maps finding severity and exploitability to triage time, fix time, and escalation. Why CVSS alone is not enough and what fields the triage engineer needs to see in the finding card. How to instrument the queue so you can answer the question how long did the longest critical sit, broken by week, without opening the queue. The runbook for an incident week when the queue depth doubles.

Module 5. Hand-off templates engineers will action

The finding card that gets fixed and the one that gets muted. The repro instructions, the suggested fix, the example diff, and the pre-agreed expectations with the engineering org about what a hand-off looks like. The mute reason taxonomy and the audit pattern that flags suspicious mute clusters. Why the hand-off template is the single highest-leverage artefact in the programme and how to negotiate the cross-team agreement that ratifies it.

Module 6. Secret scanning, SCA, and IaC integration without queue collapse

When to merge secret scanning, software composition analysis, and infrastructure-as-code findings into the same queue and when to keep them separate. The per-tool triage path, the dedup strategy, and the cross-tool prioritisation that prevents one noisy SCA scanner from drowning out a real product-security finding. The reporting cuts that show your leadership where the actual risk is sitting across all five tool families.

Module 7. Mute-rate analytics and rule-quality dashboards

The dashboard your weekly programme review actually runs from. Mute rate per rule, time-to-triage by severity, fix rate per repo, false-positive rate per rule, and queue depth trend. How to instrument these without a six-month data engineering project, and the SQL or dashboard tool queries that produce them from your existing finding store. The early-warning signals that tell you a rule is decaying before the queue notices.

Module 8. Working with engineering: pre-agreement, escalation, and the cross-team contract

The agreement you negotiate with engineering leadership before you ever ship a rule. What gets fixed, what gets muted, what gets escalated, and who carries the pager when a critical finding is open past SLA. The escalation ladder, the monthly review with engineering, and the joint metrics that align security and engineering on the same finding rather than fighting over it. Sample contracts and a worked walk-through of the first conversation.

Module 9. Evidence trail for security questionnaires and internal audit

What an enterprise customer questionnaire asks about product security testing, what an internal audit asks, and what the SOC 2 CC7 or ISO 27001 A.8.28 auditor expects. The evidence pack you produce once and reuse for every questionnaire, the queries that generate it from your finding store, and the response language that does not over-promise. How to handle the question what is your false-positive rate without panic.

Module 10. Pull-request blocking, advisory mode, and engineer-experience tradeoffs

When a finding should block the merge, when it should warn, and when it should sit in a queue. The user-research method for setting this tier per rule rather than per tool. The escape hatch design that prevents engineers from going around the system. Concrete patterns from organisations that successfully shifted left and the ones that broke build velocity and had to roll back.

Module 11. Programme review and the quarterly retirement conversation

The quarterly programme review that decides which rules ship, which retire, which retune, and which new ones get authored. The prep pack, the meeting structure, and the decision log. How to have the conversation that retires a popular rule because its FP rate exceeded budget for two quarters running. The artefact you leave behind that lets next quarter's review start from the previous decisions rather than rebuild them.

Module 12. Career capital and the public artefacts product-security engineers ship

The work that compounds beyond the queue. Conference talks, open-source rule contributions, blog posts on findings the public should learn from, and the internal write-ups that get cited by other teams. What gets published, what stays internal, and how to negotiate disclosure with leadership. The reading list and the network. How to use the programme you just built as the basis for the next role, the next conference talk, or the next external rule contribution.

How this addresses your situation

Specific modules that map to what you said you are dealing with.

Inherited a CodeQL or Pysa estate with no rule owners and a queue you cannot clear: modules 1, 3, 7, 11.

Shipping a new rule and worried about flooding the queue: modules 2, 3, 5, 10.

Engineering leadership pushing back on mute rates and pull-request blocks: modules 5, 8, 10.

Customer questionnaire or SOC 2 audit landing in the next quarter: modules 7, 9.

What you get with this course

Twelve written modules in the Art of Service learning environment, each with worked examples in CodeQL, Pysa, and Semgrep query syntax.
Downloadable templates: programme charter, rule scoping worksheet, false-positive budget table, SLA matrix, hand-off card template, mute-reason taxonomy, evidence pack outline, quarterly review prep pack.
A hand-built implementation playbook scoped to your current static-analysis estate, delivered alongside course access.
Sample dashboard queries for the metrics in module 7.
Thirty-day satisfaction guarantee.

What you will have in hand by Day 1, Week 1, Month 1

Within 24 hours: account in the Art of Service learning environment is provisioned and the tailored implementation playbook is delivered alongside it.

Week one: complete modules 1 to 4, write the programme charter, draft the scoping worksheet for one rule.

Weeks two and three: complete modules 5 to 8, negotiate the cross-team hand-off agreement, instrument the queue dashboard.

Week four onward: complete modules 9 to 12, run the first quarterly programme review using the prep pack.

Before and after

Before

Your queue is the inbox you do not want to open on Monday. You triage by volume rather than signal, you defend the programme to leadership with anecdote rather than data, and the engineering org has learned that muting a finding has no consequence. The next customer questionnaire will require a week of manual evidence gathering.

After

Your queue has severity-tied SLAs and a measured backlog. Every rule has an owner, a scope, and a published false-positive budget. The engineering org actions hand-offs because the template is pre-agreed. The customer questionnaire is answered from a pack you generated in an afternoon, and the quarterly programme review surfaces the rules that need attention before the queue notices.

What happens if you do not address this

The real injection slips through because it was finding number 312 in a queue with no triage discipline. The audit lands and the evidence pack is a scramble. The engineering org decides product security is overhead because the hand-offs read as obstruction rather than help. Leadership funds the next tool instead of the programme discipline that would have made the existing tools work.

Who it is for

A mid-to-senior product security engineer or application security lead at a platform company, hyperscaler, fintech, or large SaaS. You own static analysis or share ownership with a partner team. You have at least one of CodeQL, Pysa, Semgrep, or a homegrown equivalent in production. You read code in two or more languages. You report queue and fix-rate numbers up the chain at least monthly. You are the person engineers ping when a finding fires on their pull request.

Who this is NOT for. This is not for security generalists who have never authored a static-analysis rule. It is not for compliance specialists who want a SOC 2 walkthrough. It is not for engineering managers looking for a hiring rubric. It assumes you can read query syntax, you understand taint propagation at a working level, and you have shipped at least one production change to a rule or model.

How it arrives

Text-based course in the Art of Service learning environment, plus downloadable templates and worked examples for every module, plus the hand-built implementation playbook delivered alongside course access.

Time investment. Roughly four to six hours per module, eight to twelve weeks at a comfortable pace, faster if you front-load on a quiet sprint.

Why $199 is the right number

Vendor training from your static-analysis tool covers the tool. This covers the programme around the tool. Conference talks cover one war story. This covers the operating model you reuse every quarter. An internal write-up from a previous owner covers what they did. This covers what you do next.

FAQ

Is this specific to CodeQL?

No. Worked examples cover CodeQL, Pysa, and Semgrep because those are the three most common stacks. The programme discipline applies regardless of which tool authored the finding.

Will this teach me to author CodeQL queries from scratch?

Module 2 teaches authoring scoped rules with worked examples. It assumes you can read query syntax. If you are new to query authoring, the module is the right ramp; if you have never seen taint analysis at all, start with the tool vendor's introductory material first.

How is this different from a SOC 2 controls course?

A SOC 2 course teaches you to map controls to evidence. This teaches you to run the underlying programme so the evidence is real. Module 9 covers the evidence trail an auditor or a customer questionnaire actually reads.

What does the implementation playbook contain?

It is scoped to the static-analysis estate you describe in the onboarding form. Typical contents: a programme charter draft, an SLA matrix populated to your finding volume, a hand-off template adapted to your engineering org's review tooling, and a quarterly review prep pack with the first quarter's rule retirement candidates flagged.

30-day money-back guarantee. If after a week of working through the materials this is not what you needed, reply to the receipt email and a full refund is processed. No questions, no forms.

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.