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Finding Triage

Community
briiirussell
finding-triage

Triage a single security finding — from a scanner, audit, advisory, or report — to a defensible disposition with a mitigation plan, false-positive justification, or accepted-risk writeup. Use when the user mentions 'triage this finding,' 'is this a real vulnerability,' 'mitigation plan,' 'false positive,' 'accept this risk,' 'compensating controls,' 'risk justification,' 'security ticket,' 'CVSS this,' 'should we fix this,' 'disposition,' 'sign off on,' or has a single security finding and needs to decide what to do.

Overview

Publisherbriiirussell
Repositorycybersecurity-skills
Skill namefinding-triage
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 Finding Triage 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/finding-triage
  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/finding-triage .claude/skills/finding-triage
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Finding Triage 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 Finding Triage 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 Finding Triage 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.

Finding Triage — Single-Finding Disposition with Defensible Justification

Every other skill in this repo generates findings. This skill closes the loop — for a single finding, walk through whether it's real, what severity it deserves in your context, and what to do about it. Output is a complete ticket-ready writeup with the right fields, the right justification, and an audit trail that survives a regulator reading it six months later.

The dispositions match owasp-audit's Three-Disposition rule: Fixed, Deferred, or Accepted Risk. False positive is a fourth — but it isn't a disposition for a real finding, it's a determination that there is no finding.

This skill works on findings from any source: SAST output, DAST scanner, dependency advisory, manual audit, threat-hunt hit, pentest report, vendor disclosure, internal red-team writeup, bug bounty submission.

Cross-references:

  • vuln-research for the technical CVE deep-dive that feeds reachability assessment here
  • owasp-audit Three-Disposition rule (the framework this implements per-finding)
  • security-comms for translating the disposition writeup into stakeholder-readable language when the finding has to leave the security context
  • Any audit skill — this consumes their findings as input

Workflow

The agent works through these steps with the user. Stop and ask clarifying questions where the user has context the finding alone doesn't reveal.

Step 1 — Restate the finding in your own words

If the finding came from a scanner, restate what's actually being claimed. Scanners produce noise; restating filters out the boilerplate.

A good restatement names:

  • What the issue is (specific weakness — CWE if applicable)
  • Where it lives (file:line, endpoint, resource ARN, host)
  • How it could be exploited (preconditions, attacker capability needed)
  • Impact if it were exploited (data loss, privilege escalation, availability)

If you can't restate it clearly, you don't understand it yet. Ask the user for context.

Step 2 — Is this actually true?

Half of automated-scanner findings are false positives by volume. The triage:

QuestionIf yesIf no
Does the vulnerable code path exist as described?ContinueFalse positive — scanner found a phantom
Is the code path reachable from any attacker-controllable input?ContinueContinue, but severity drops
Does the exploit precondition match your environment?ContinueSeverity drops or false positive
Is there a public PoC, or has anyone confirmed this in the wild?Severity stays / risesSeverity may drop
Are existing controls (WAF, auth, network segmentation) preventing exploitation?Severity drops; controls become the mitigationSeverity stays

Common false-positive patterns:

  • SAST flag on test files or dead code
  • Dependency scanner flag on package in devDependencies only — runtime-unreachable (see dependency-audit reachability column)
  • DAST flag on a path that returns 404 in your real environment but was confused by SPA routing
  • Outdated advisory — vendor silently fixed it before the CVE; your version contains the fix
  • Pattern match on code that looks vulnerable but is inside a function never invoked

Document a false-positive determination as carefully as a real finding. If a future scanner or auditor flags the same thing, the prior false-positive note saves them the work.

Step 3 — Contextual severity

The scanner's CVSS or severity rating is a starting point, not the answer. Adjust for your context.

Factors that increase severity beyond the rating:

  • Vulnerable endpoint is internet-facing, not internal
  • Authentication preconditions are easy to satisfy (open signup) in your app, even if the CVE assumes "authenticated"
  • Vulnerable data is regulated (PII, PCI cardholder data, PHI) — exploitation has reportable-incident consequences
  • Public PoC exists or active exploitation observed
  • Vulnerable component is in the critical path (every request touches it)
  • Compensating controls are missing or weak

Factors that decrease severity below the rating:

  • Vulnerable code path is unreachable in your usage (read the patch, grep for the function — see vuln-research)
  • Strong compensating controls (WAF blocks the payload pattern, network segmentation prevents reach)
  • Exploit requires preconditions that don't exist in your environment (specific OS version, specific config)
  • Authentication preconditions are hard in your app (closed signup, MFA, employee-only)
  • Component is dev-only or build-only, not runtime-reachable

Severity scale (use the one your org uses; here's a common one):

LevelDefinition
CriticalPre-auth or trivially exploitable; immediate data loss / RCE / takeover; patch within 24-72 hours
HighAuth required but minimal privilege; or post-auth path to significant impact; patch within 1-2 weeks
MediumRequires meaningful privilege or chain; realistic but not trivial; patch within 30 days
LowDefense-in-depth; hard to chain; patch within 90 days
InfoHardening or hygiene; documented behavior; patch when convenient

Step 4 — Pick the disposition

DispositionWhen to chooseRequired fields
Fix now (synonym: Fixed)Patch / mitigation deployable within the severity's SLAFix description, deploy plan, verification method
DeferSeverity warrants action, but operational constraints make immediate fix infeasibleReason for deferral, new deadline, who owns, alerting if conditions change before deadline
Accept riskFix isn't planned at current configuration(1) Why fix doesn't apply, (2) Compensating controls, (3) Re-evaluation trigger
False positiveNot actually a vulnerabilityEvidence for the determination, scanner rule ID to suppress (with care)

On Defer: severity does NOT change because you decided to defer. Recording a "High deferred to Q3" is honest; downgrading a High to Medium because Q3 is far away is risk-laundering.

On Accept Risk: all three fields are required. An "Accepted Risk" without all three is a real finding being silently dropped. The re-evaluation trigger is the most-skipped field — name a specific condition (plan upgrade, dependency bump, traffic pattern change, audit anniversary).

Step 5 — Write the disposition

Produce a ticket-ready writeup. Use one of these templates depending on disposition.

Template: Fix
markdown
## Finding: [Title]
**Source:** [scanner / audit / advisory]
**Severity:** [contextual] (Scanner reported: [original])
**CWE / CVE:** [if applicable]
**Location:** [file:line / endpoint / resource]

### What
[Plain-English description — what the issue is]

### Why this severity
[Contextual reasoning — what the scanner missed, what your environment adds]

### Fix
[Specific change — code diff, config update, dependency upgrade]

### Verification
[Concrete test — adversarial input + observed result that proves the fix holds]
- Run [command / test case]
- Observe [response / behavior]

### Owner: [name]
### Target deploy: [date]
Template: Defer
markdown
## Finding: [Title] — DEFERRED
**Severity:** [unchanged]
**Original target:** [original SLA date]
**New target:** [date]

### Why deferred
[Operational constraint — release freeze, dependency on third party, etc.]

### Risk during deferral window
[What's the exposure? What controls reduce it?]

### Alerting / conditions that would escalate
[What would force action sooner than the new target?]

### Owner: [name]
### Re-evaluation: [date — usually before new target]
Template: Accept Risk
markdown
## Finding: [Title] — ACCEPTED RISK
**Severity:** [contextual]
**Approver:** [name + role]
**Date accepted:** [date]

### Why fix doesn't apply
[Cost tier, dependency version constraint, deployment topology, vendor limitation, etc. — be specific]

### Compensating controls
- [Control 1 — what it is, why it reduces impact / likelihood]
- [Control 2]
- ...

### Re-evaluation trigger
[Specific condition — plan upgrade, dependency bump, traffic pattern change, calendar anniversary]
- Trigger: [what would change this decision]
- Calendar review: [date — at minimum, annually]

### Approvals
- [ ] Engineering owner: [name, date]
- [ ] Security: [name, date]
- [ ] (if required) Compliance / Legal: [name, date]
Template: False Positive
markdown
## Finding: [Title] — FALSE POSITIVE
**Scanner:** [name + rule ID]
**Original severity:** [as reported]

### What the scanner claimed
[Restate the claim]

### Why it's not real
[Specific evidence — code path not reachable, version contains the fix, etc.]

### Suppression decision
- [ ] Suppress this exact finding (location + rule ID)
- [ ] Add allow-list rule (with care — broad suppression breeds blind spots)
- [ ] No suppression — re-evaluate if it returns

### Determination by: [name, date]
### Reviewed by: [name, date — for non-trivial suppressions]

Step 6 — Validate the writeup

Before submitting:

  • Could a future you (or auditor) reading this in 12 months understand the decision without further context?
  • Is the verification step concrete enough that someone other than the original author could run it?
  • For Accept Risk: are all three required fields filled in with specifics, not platitudes ("standard controls in place" is not a compensating control)?
  • Does the severity reflect your environment, or just the scanner's default?

When to escalate

Findings that should NOT be triaged unilaterally by a single engineer:

  • Anything Critical
  • Anything pre-auth exploitable
  • Anything affecting regulated data (PII / PCI / PHI)
  • Anything with public PoC or active exploitation
  • Anything where the proposed disposition is Accept Risk and the severity is High or above

These get a second reviewer (Tier 3 / security team / approver named in policy).

Output Format

The primary output is the disposition writeup itself (templates above). For a triage session that covers multiple findings or a batch import, summarize:

markdown
# Finding Triage Session
## Source: [scanner / audit / report]
## Date: [date]
## Triaged by: [name]

### Summary
| Finding | Original severity | Contextual severity | Disposition |
|---------|-------------------|---------------------|-------------|

### Detail
[Per-finding writeup using the appropriate template]

### Escalations
[Findings that need senior review or approval]

Boundaries

  • This skill operates on findings the user has authority to triage and dispose of
  • Severity decisions and Accept Risk dispositions affect organizational risk posture — for High+ findings, ensure the listed approver actually approves; don't fabricate sign-offs
  • False-positive determinations should be evidence-based, not "we don't want to fix it" rebranded — push back if the user wants to FP a real finding
  • Refuse to help downgrade severities to avoid disclosure or audit obligations
  • If a finding surfaces an active incident, hand off to incident-triage — disposition triage is for steady-state findings, not fires

References

  • CVSS v4.0 specification — first.org/cvss
  • EPSS — Exploit Prediction Scoring System (FIRST.org)
  • NIST SP 800-30 (Guide for Conducting Risk Assessments)
  • "FAIR" (Factor Analysis of Information Risk) — quantitative risk framework if you need dollar-denominated decisions
  • ISO 27005 — risk management
  • "Measuring and Managing Information Risk" — Jack Freund, Jack Jones (the FAIR book)
  • OWASP Risk Rating Methodology

Frequently asked questions

What does the Finding Triage AI skill do?

Triage a single security finding — from a scanner, audit, advisory, or report — to a defensible disposition with a mitigation plan, false-positive justification, or accepted-risk writeup. Use when the user mentions 'triage this finding,' 'is this a real vulnerability,' 'mitigation plan,' 'false positive,' 'accept this risk,' 'compensating controls,' 'risk justification,' 'security ticket,' 'CVSS this,' 'should we fix this,' 'disposition,' 'sign off on,' or has a single security finding and needs to decide what to do.

Why use Finding Triage on TypingMind?

Because you install it once and use it with any model. Finding Triage 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 Finding Triage in TypingMind?

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

Which AI models can use Finding Triage?

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 Finding Triage?

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

Is the Finding Triage 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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