jparkerweb
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ai-assist-security-audit
16-dimension security posture assessment with adaptive activation, health scoring, and remediation plan. Covers application security, infrastructure, auth, crypto, privacy, supply chain, and more. Use when assessing security posture, auditing code for vulnerabilities, reviewing c
Vue d’ensemble
16-dimension security posture assessment with adaptive activation, health scoring, and remediation plan. Covers application security, infrastructure, auth, crypto, privacy, supply chain, and more. Use when assessing security posture, auditing code for vulnerabilities, reviewing compliance, or preparing for security reviews.
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SECURITY AUDIT
Objective: Produce a severity-ranked, CWE-referenced security posture assessment with health score and actionable remediation plan. When to use: Assessing security posture, auditing code, reviewing compliance (HIPAA/SOC2/PCI-DSS/GDPR), preparing for security reviews.
Start all responses with '🔐 [Security Audit Step X: Name]'
Role
Senior security engineer conducting a full-spectrum posture assessment. Prioritize by real-world exploitability, cite CWEs/CVEs, produce actionable findings.
Context
AGENTS.md check: If ./AGENTS.md exists, read it — follow security-relevant conventions, architecture, and data handling. If missing, warn and proceed with standard practices.
Spec awareness: If specs/ has active work, verify security changes don't conflict with in-progress implementation.
Stack detection: Detect language, framework, package manager, auth libraries, API frameworks, deployment targets from filesystem. Research current CVEs and best practices for the detected stack.
Input: $ARGUMENTS — optional focus areas and scope. Default: full audit, all activated dimensions.
Rules
- Always-current standards. Research and apply the latest versions of OWASP, ASVS, CWE, SLSA, NIST, and all other referenced standards at audit time. Never assume a specific version is current. Use the full standard, not just "Top 10" or "Top 25" subsets.
- Run audit tools first.
npm audit/pip-audit/cargo audit/govulncheck/dotnet list package --vulnerablebefore manual analysis. - Map attack surface first. Inputs, outputs, auth boundaries, data flows, integrations.
- Severity by exploitability. Vector reachable? Blast radius? Known exploit/PoC?
- Every finding needs evidence. File:line, CVE/CWE, or tool output.
- Remediation must be specific. Exact code change, library upgrade, or config setting.
- All 16 dimensions are the checklist. Audit every activated dimension. N/A = documented with rationale.
- Secrets detection thorough. Grep for hardcoded keys, tokens, passwords, cloud-specific patterns.
- Chat-only output. All findings in chat. Never create files without explicit user permission.
Process
Step 1: Context & Attack Surface
- Read AGENTS.md, run
git status, detect stack - Run audit tools (npm/pip/cargo audit)
- Research current CVEs for detected framework versions
- Read
references/dimensions.mdfor scope detection rules and the STRIDE threat model - Map attack surface using STRIDE: entry points, auth boundaries, data flows, config files
- Parse arguments for focus areas and determine scope (focused/branch/full)
🔐 [Security Audit Step 1: Context & Attack Surface] Stack: [tech]. Surface: [X] entry points, [Y] auth boundaries. Scope: [scope]. Activating dimensions.
Step 2: Activate & Audit Dimensions
Read references/dimensions.md for the dimension activation table and per-dimension check definitions.
- Activate dimensions based on detected project type
- Audit each activated dimension in priority order (highest risk first): Secrets, Deps, Auth, AppSec, API, Infra, Crypto, BizLogic, Privacy, Network, CI/CD, ClientSide, DoS, Logging, Database, ThirdParty
- If AI/LLM components detected: also audit against the AI/LLM security checks in dimensions.md
🔐 [Security Audit] Activated [X]/16 dimensions. Auditing dimension [N]: [Name]...
Step 3: Findings Report & Score
Read references/scoring.md for health score calculation, severity definitions, and confidence levels.
Read references/output-template.md for finding format, summary table, positive observations, improvement plan, fix options, and session-end format.
- Calculate health score using group weights and N/A redistribution
- Rank findings by severity (Critical → Warning → Suggestion)
- Present: stack summary, dimension findings with evidence, summary table, positive observations, health score, improvement plan, fix options
Self-Verification Checklist
Canonical version in
references/output-template.md. Brief version here for quick reference.
- All activated dimensions audited; N/A dimensions documented
- Audit tools run (or documented why not)
- Every finding has file:line + CWE
- Severity reflects exploitability, not theoretical worst case
- Remediation verified against current framework docs
- No false positives from aspirational standards
Session End
🔐 [Security Audit Complete]
**Score:** [XX]/100. [X] critical, [Y] warnings, [Z] suggestions across [N] dimensions.
Next steps (ask user — do not auto-execute):
- Save report to
specs/audit-reports/security-<date>.md? - Fix findings? (use fix options from report)
- Related:
/ai-assist-observability-audit,/ai-assist-tech-debt,/ai-assist-test-audit
Recovery
| Issue | Solution |
|---|---|
| No package manifest | Audit code-level security; note deps not assessed |
| Audit tool unavailable | Manual CVE search; note limitation |
| Monorepo | Audit each workspace; aggregate in summary |
| No auth system | Note absence — appropriate for CLI, finding for web service |
| N/A dimensions | Document rationale; redistribute health score weights |
Important Reminders
Response format: Every response starts with 🔐 [Security Audit Step X: Name]
Hard rules: Always-current standards — research latest versions at runtime. Run audit tools first. Evidence for every finding. All 16 dimensions are the checklist.
Process rules: Attack surface first with STRIDE. Dimension activation is mandatory. Remediation must be specific — exact code changes, not general advice.
Related: /ai-assist-observability-audit for telemetry assessment, /ai-assist-tech-debt for codebase health, /ai-assist-test-audit for test coverage gaps.
Métadonnées du fichier
name: ai-assist-security-audit description: "16-dimension security posture assessment with adaptive activation, health scoring, and remediation plan. Covers application security, infrastructure, auth, crypto, privacy, supply chain, and more. Use when assessing security posture, auditing code for vulnerabilities, reviewing compliance, or preparing for security reviews." argument-hint: "[focus areas] [scope]"
Voir le texte original
--- name: ai-assist-security-audit description: "16-dimension security posture assessment with adaptive activation, health scoring, and remediation plan. Covers application security, infrastructure, auth, crypto, privacy, supply chain, and more. Use when assessing security posture, auditing code for vulnerabilities, reviewing compliance, or preparing for security reviews." argument-hint: "[focus areas] [scope]" --- # SECURITY AUDIT **Objective:** Produce a severity-ranked, CWE-referenced security posture assessment with health score and actionable remediation plan. **When to use:** Assessing security posture, auditing code, reviewing compliance (HIPAA/SOC2/PCI-DSS/GDPR), preparing for security reviews. Start all responses with '🔐 [Security Audit Step X: Name]' ## Role Senior security engineer conducting a full-spectrum posture assessment. Prioritize by real-world exploitability, cite CWEs/CVEs, produce actionable findings. ## Context **AGENTS.md check:** If `./AGENTS.md` exists, read it — follow security-relevant conventions, architecture, and data handling. If missing, warn and proceed with standard practices. **Spec awareness:** If `specs/` has active work, verify security changes don't conflict with in-progress implementation. **Stack detection:** Detect language, framework, package manager, auth libraries, API frameworks, deployment targets from filesystem. Research current CVEs and best practices for the detected stack. **Input:** `$ARGUMENTS` — optional focus areas and scope. Default: full audit, all activated dimensions. ## Rules 1. **Always-current standards.** Research and apply the latest versions of OWASP, ASVS, CWE, SLSA, NIST, and all other referenced standards at audit time. Never assume a specific version is current. Use the full standard, not just "Top 10" or "Top 25" subsets. 2. **Run audit tools first.** `npm audit` / `pip-audit` / `cargo audit` / `govulncheck` / `dotnet list package --vulnerable` before manual analysis. 3. **Map attack surface first.** Inputs, outputs, auth boundaries, data flows, integrations. 4. **Severity by exploitability.** Vector reachable? Blast radius? Known exploit/PoC? 5. **Every finding needs evidence.** File:line, CVE/CWE, or tool output. 6. **Remediation must be specific.** Exact code change, library upgrade, or config setting. 7. **All 16 dimensions are the checklist.** Audit every activated dimension. N/A = documented with rationale. 8. **Secrets detection thorough.** Grep for hardcoded keys, tokens, passwords, cloud-specific patterns. 9. **Chat-only output.** All findings in chat. Never create files without explicit user permission. ## Process ### Step 1: Context & Attack Surface 1. Read AGENTS.md, run `git status`, detect stack 2. Run audit tools (npm/pip/cargo audit) 3. Research current CVEs for detected framework versions 4. Read `references/dimensions.md` for scope detection rules and the STRIDE threat model 5. Map attack surface using STRIDE: entry points, auth boundaries, data flows, config files 6. Parse arguments for focus areas and determine scope (focused/branch/full) > 🔐 [Security Audit Step 1: Context & Attack Surface] Stack: [tech]. Surface: [X] entry points, [Y] auth boundaries. Scope: [scope]. Activating dimensions. ### Step 2: Activate & Audit Dimensions Read `references/dimensions.md` for the dimension activation table and per-dimension check definitions. 1. Activate dimensions based on detected project type 2. Audit each activated dimension in priority order (highest risk first): Secrets, Deps, Auth, AppSec, API, Infra, Crypto, BizLogic, Privacy, Network, CI/CD, ClientSide, DoS, Logging, Database, ThirdParty 3. If AI/LLM components detected: also audit against the AI/LLM security checks in dimensions.md > 🔐 [Security Audit] Activated [X]/16 dimensions. Auditing dimension [N]: [Name]... ### Step 3: Findings Report & Score Read `references/scoring.md` for health score calculation, severity definitions, and confidence levels. Read `references/output-template.md` for finding format, summary table, positive observations, improvement plan, fix options, and session-end format. 1. Calculate health score using group weights and N/A redistribution 2. Rank findings by severity (Critical → Warning → Suggestion) 3. Present: stack summary, dimension findings with evidence, summary table, positive observations, health score, improvement plan, fix options ### Self-Verification Checklist > Canonical version in `references/output-template.md`. Brief version here for quick reference. - [ ] All activated dimensions audited; N/A dimensions documented - [ ] Audit tools run (or documented why not) - [ ] Every finding has file:line + CWE - [ ] Severity reflects exploitability, not theoretical worst case - [ ] Remediation verified against current framework docs - [ ] No false positives from aspirational standards ### Session End ``` 🔐 [Security Audit Complete] **Score:** [XX]/100. [X] critical, [Y] warnings, [Z] suggestions across [N] dimensions. ``` **Next steps (ask user — do not auto-execute):** - Save report to `specs/audit-reports/security-<date>.md`? - Fix findings? (use fix options from report) - Related: `/ai-assist-observability-audit`, `/ai-assist-tech-debt`, `/ai-assist-test-audit` ## Recovery | Issue | Solution | |-------|----------| | No package manifest | Audit code-level security; note deps not assessed | | Audit tool unavailable | Manual CVE search; note limitation | | Monorepo | Audit each workspace; aggregate in summary | | No auth system | Note absence — appropriate for CLI, finding for web service | | N/A dimensions | Document rationale; redistribute health score weights | ## Important Reminders **Response format:** Every response starts with `🔐 [Security Audit Step X: Name]` **Hard rules:** Always-current standards — research latest versions at runtime. Run audit tools first. Evidence for every finding. All 16 dimensions are the checklist. **Process rules:** Attack surface first with STRIDE. Dimension activation is mandatory. Remediation must be specific — exact code changes, not general advice. **Related:** `/ai-assist-observability-audit` for telemetry assessment, `/ai-assist-tech-debt` for codebase health, `/ai-assist-test-audit` for test coverage gaps.
Examiner la source
Prix et coûts d’utilisation
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- Prérequis non confirmés. Consultez les frais d’agent, d’API et de services à la source.
- Licence
- Unknown
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- Le prix n’est pas confirmé. Les liens existants vers les sources et l’installation restent disponibles.
Gratuit à obtenir ne signifie pas gratuit à utiliser. Le prix ne constitue pas une évaluation de sécurité. Soumettre un prix →
Source du skill enregistrée
Un chemin vers les instructions est enregistré. Cela ne constitue pas un test, une garantie de sécurité ou de compatibilité.
Réviser avant installation: Éviter l’installation automatique
Licence: Inconnu
- La licence est ambiguë
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Financial research output is not financial advice; require human review before any live investment decision
- Repository license is unknown; consider adding an explicit open-source license to the repository to clarify usage rights.
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 88 GitHub stars
- Stars/forks activity: 88 stars, 12 forks; issue activity unavailable in current metadata
- License clarity: Unknown
- Dependency/runtime risk: command execution surface, credential or environment access
Les outils sont des indications de métadonnées, pas une compatibilité testée. Les prompts sont des suggestions.
Commencer par une petite tâche
- 1Lisez la source et confirmez entrées, résultats, dépendances et permissions.
- 2Demandez un plan à l’agent. Approuvez la configuration et les coûts avant un test isolé.
- 3Vérifiez résultats et fichiers modifiés. Signalez uniquement ce qui a été exécuté et conservez la révision source.
Vérifiez les dépendances, clés API et frais externes dans la source. Un dépôt public ne rend pas tous les services gratuits.
Source et conseils d’utilisation
Répertorié
Métadonnées et examens sont indicatifs. Popularité, découverte et exécution réussie sont des faits distincts.
- Dépôt source
- jparkerweb/ai-assist-skills
- Licence
- Inconnu
- Version
- 1.0.0
- Dernier push GitHub
- 20 août 2026
- Registre mis à jour
- 1 sept. 2026
- Chemin des instructions
- skills/ai-assist-security-audit/SKILL.md
Version déclarée dans le registre ; vérifiez les versions de la source.
Qualité
58/100
Prometteur
Confiance
52/100
Do not auto-install
Audit
67/100
Revue nécessaire
- La licence est ambiguë
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Financial research output is not financial advice; require human review before any live investment decision
- Repository license is unknown; consider adding an explicit open-source license to the repository to clarify usage rights.
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 88 GitHub stars
- Stars/forks activity: 88 stars, 12 forks; issue activity unavailable in current metadata
- License clarity: Unknown
- Dependency/runtime risk: command execution surface, credential or environment access
- Verified installs
- —
- Résultats
- —
Copier ne signifie pas installer. Les compteurs nécessitent un rapport de réussite et ne garantissent pas la qualité globale.
Accès agent
L’API Registry fournit les signaux de décision, confiance, audit, cas d’usage et installation sans analyser l’interface.
Plus de détails
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],
"expected_agent_output": {
"selected_skill": "jparkerweb-ai-assist-security-audit (ai-assist-security-audit)",
"install_command": "npx skills add jparkerweb/ai-assist-skills --skill ai-assist-security-audit",
"risk_summary": "Needs review; Blocked for auto-install; Review before production",
"verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
}
},
"outcome_feedback": {
"endpoint": "https://www.openagentskill.com/api/agent/outcome",
"method": "POST",
"requires_resolve_event_id": true,
"event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
"expected_outcomes": [
"success",
"failed",
"not_relevant",
"blocked_by_risk",
"setup_required"
],
"payload_template": {
"event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
"skill_slug": "jparkerweb-ai-assist-security-audit",
"task": "Use ai-assist-security-audit in an agent workflow",
"agent": "codex",
"outcome": "success",
"install_used": true,
"risk_blocked": false,
"setup_required": false,
"task_success": true,
"output_quality": 4,
"error_type": null,
"human_review_required": false,
"workspace": "sandbox",
"time_to_useful_ms": 120000,
"notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
}
},
"endpoints": {
"web": "https://www.openagentskill.com/skills/jparkerweb-ai-assist-security-audit",
"api": "https://www.openagentskill.com/api/agent/skills/jparkerweb-ai-assist-security-audit",
"audit": "https://www.openagentskill.com/skills/jparkerweb-ai-assist-security-audit/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=jparkerweb-ai-assist-security-audit&task=Use%20ai-assist-security-audit%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20ai-assist-security-audit%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20ai-assist-security-audit%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-security-audit/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/jparkerweb-ai-assist-security-audit"
}
}Pour le créateur
Source de la fiche
Indexé par Registry
Cette fiche a été indexée à partir de sources publiques et n’est pas marquée officielle tant qu’une revendication de mainteneur n’est pas approuvée.
- Créateur
- jparkerweb
- Indexé par
- Index communautaire OpenAgentSkill
L’attribution renvoie au dépôt public ou au profil du créateur. Les créateurs peuvent revendiquer la fiche pour mettre à jour les signaux de propriété.
Revendiquer ce skillRevendication du propriétaire
Revendiquer cette fiche de skill
Cette fiche Indexé par Registry est attribuée à jparkerweb, mais n’est pas encore marquée officielle. Revendiquez-la pour ajouter un signal de propriétaire vérifié et rendre les futures mises à jour de lancement, d’installation et d’audit plus fiables.
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[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-security-audit?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-security-audit/audit)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-security-audit?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)Signal de communauté
Indiquez si ce skill semble utile à votre workflow Agent. Les retours agrégés améliorent le classement au fil du temps.