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About
Use cases: security
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/triage
What's inside
- Skill name
triage- Description
- Adversarial validation of vulnerability findings. Use when triaging security findings, validating vulnerabilities, or prioritizing remediation.
- License
- Apache-2.0
- Instructions
- 177 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Triage — Adversarial Vulnerability Validation
## Iron Law
A vulnerability finding is not confirmed until an adversary would agree it's exploitable. Unvalidated findings are noise.
## Process
### Step 0: Load Inputs
Required inputs (in order of preference):
1. `VULN-FINDINGS.json` from `/vuln-scan`
2. Raw findings from `/audit --security`
3. User-provided finding list
Optional:
- `THREAT_MODEL.md` for threat scenario context
- `.harness/engagement.md` for scope constraints
If no findings input exists, suggest:
**"Run `/vuln-scan` first to generate findings to triage."**
### Step 1: Adversarial Review
For each finding, challenge it from an attacker's perspective:
#### Exploitability Check
1. **Can input reach the vulnerable code?** Trace the data flow from entry point to vulnerability.
2. **Can the attacker control the input?** Distinguish between user-controlled vs. system-generated data.
3. **Is there a path to impact?** Connecting the vulnerability to a security consequence (data leak, code exec, DoS).
4. **Are there bypasses for existing mitigations?** WAF, input validation, CSP — all have bypass techniques.
#### Severity Validation
| Criteria | Adjust |
|----------|--------|
| Requires authentication | Lower by 1 level |
| Requires specific permissions | Lower by 1 level |
| Chained with another finding | Raise by 1 level |
| Affects all users | Raise by 1 level |
| No mitigation in place | Raise by 1 level |
| Defense-in-depth exists | Lower by 1 level |
#### Classification
| Class | Meaning |
|-------|---------|
| `CONFIRMED` | Exploitable with demonstrated path |
| `LIKELY` | Exploitable with high confidence, minor gaps in proof |
| `POSSIBLE` | Theoretical, needs more investigation |
| `FALSE_POSITIVE` | Not exploitable with justification |
| `ACCEPTED_RISK` | Known, documented, accepted by team |
### Step 2: Dependency Analysis
Check if findings chain together:
1. **Find pairs** where finding A enables finding B (e.g., IDOR → data exposure)
2. **Mark chains** — chained findings are more severe than individual findings
3. **Identify root causes** — multiple findings from the same root cause should be grouped
### Step 3: Produce Output
Write `TRIAGE.json`:
```json
{
"triage_date": "ISO-8601",
"source": "VULN-FINDINGS.json | audit | manual",
"findings": [
{
"id": "V1",
"classification": "CONFIRMED | LIKELY | POSSIBLE | FALSE_POSITIVE | ACCEPTED_RISK",
"original_severity": "CRITICAL",
"adjusted_severity": "HIGH",
"severity_adjustments": ["requires auth (-1)", "no mitigation (+1)"],
"exploit_path": ["entry point → vulnerable function → impact"],
"chains_with": ["V3"],
"root_cause_group": "RC1",
"remediation": "specific fix instruction",
"effort": "low | medium | high",
"validation_notes": "why this classification was chosen"
}
],
"root_cause_groups": [
{
"id": "RC1",
"description": "shared root cause",
"findings": ["V1", "V2"],
"fix_once": "single fix that resolves all findings in group"
}
],
"chains": [
{
"findings": ["V1", "V3"],
"combined_severity": "CRITICAL",
"description": "V1 enables V3, creating..."
}
],
"summary": {
"total_input": 10,
"confirmed": 3,
"likely": 2,
"possible": 1,
"false_positive": 2,
"accepted_risk": 2,
"root_cause_groups": 3,
"chains": 1
},
"action_items": [
{
"priority": 1,
"severity": "CRITICAL",
"finding_ids": ["V1"],
"action": "specific remediation step",
"effort": "low"
}
]
}
```From epicsagas/epic-harness, Apache-2.0.
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Signals
- Stars
- 19
- Forks
- 5
- Open issues
- 3
- Last commit (this folder)
- Jun 25, 2026 (4 months ago)
- Last release
- Oct 23, 2026 (7 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Repository
- github.com/epicsagas/epic-harness
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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triage skill. Agent Mart. https://agentmart.dev/skills/epicsagas-triage (last updated 2026-10-24)