Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/matteocervelli/llmsnpx agentmods add skills/matteocervelli/llms/vulnerability-assessorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/matteocervelli/llms/vulnerability-assessor)<a href="https://agentmods.dev/skills/matteocervelli/llms/vulnerability-assessor"><img src="https://agentmods.dev/badge/skills/matteocervelli/llms/vulnerability-assessor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/matteocervelli/llms/vulnerability-assessor"><img src="https://agentmods.dev/badge/skills/matteocervelli/llms/vulnerability-assessor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00031 | $0.03537 |
| Opus 5 | $0.00015 | $0.01768 |
| Sonnet 5 | $0.00006 | $0.00707 |
| Haiku 4.5 | $0.00003 | $0.00354 |
Grade A, and why
vulnerability-assessor scanned grade A with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl https://nvd.nist.gov/rest/json/cves/2.0?cveId=CVE-2024-XXXXX Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
os.system(f"ping {user_input}") How it starts
The opening of the file, as written. The whole thing — 622 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vulnerability Assessor Skill
Purpose
This skill provides deep analysis of security vulnerabilities, evaluating exploitability, assessing business impact, calculating risk scores, and providing detailed remediation strategies.
When to Use
- After security scanning identifies vulnerabilities
- Need to prioritize security findings
- Assessing exploitability of vulnerabilities
- Calculating CVSS scores
- Creating remediation roadmaps
- Risk assessment for security issues
Assessment Workflow
1. Vulnerability Classification
Categorize by Type:
Injection Vulnerabilities:
- SQL Injection (SQLi)
- Command Injection
- Code Injection
- LDAP Injection
- XPath Injection
- NoSQL Injection
- OS Command Injection
Broken Authentication:
- Weak password policies
- Session fixation
- Credential stuffing vulnerabilities
- Insecure authentication tokens
- Missing MFA
Sensitive Data Exposure:
- Unencrypted data in transit
- Unencrypted data at rest
- Exposed credentials
- PII leakage
- API keys in code
XML External Entities (XXE):
- XML parsing vulnerabilities
- External entity injection
- DTD injection
Broken Access Control:
- Insecure direct object references (IDOR)
- Missing authorization checks
- Privilege escalation
- CORS misconfiguration
Security Misconfiguration:
- Default credentials
- Unnecessary features enabled
- Error messages leaking information
- Missing security headers
Cross-Site Scripting (XSS):
- Reflected XSS
- Stored XSS
- DOM-based XSS
Insecure Deserialization:
- Pickle in Python
- Unsafe YAML loading
- JSON deserialization issues
Using Components with Known Vulnerabilities:
- Outdated dependencies
- Unpatched libraries
- Known CVEs
Insufficient Logging & Monitoring:
- Missing security event logging
- No alerting on suspicious activity
- Inadequate audit trails
Deliverable: Categorized vulnerability list
2. Exploitability Assessment
Evaluate Ease of Exploitation:
Easy (High Exploitability):
- Publicly available exploits
- No authentication required
- Automated tools can exploit
- Simple proof of concept
- Wide attack surface
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 622 lines · 31 tokens per session scan A 7b3a79edd80a
vulnerability-assessor is a skill published in the GitHub repository matteocervelli/llms (25 stars, last pushed 3mo ago), licensed MIT. It adds 31 tokens to every session and 3,537 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…