Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add nimadorostkar/Claude-Skills-collection --skill security-reviewgit clone --depth 1 https://github.com/nimadorostkar/Claude-Skills-collectionWrote 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/nimadorostkar/claude-skills-collection/security-review)<a href="https://agentmods.dev/skills/nimadorostkar/claude-skills-collection/security-review"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/security-review/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/nimadorostkar/claude-skills-collection/security-review"><img src="https://agentmods.dev/badge/skills/nimadorostkar/claude-skills-collection/security-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 77 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00040 | $0.01181 |
| Opus 5 | $0.00020 | $0.00590 |
| Sonnet 5 | $0.00008 | $0.00236 |
| Haiku 4.5 | $0.00004 | $0.00118 |
Grade A, and why
security-review scanned grade A with 1 finding 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 9d 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 -H "Authorization: Bearer <any valid token>" https://api.example.com/invoices/1 How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Review
Purpose
Find the vulnerabilities in a codebase or a change, with enough specificity that each finding can be fixed and verified. A security review that produces a list of theoretical concerns is not a security review.
When to Use
- Reviewing a pull request that touches authentication, authorization, or user input.
- Auditing a service before it becomes internet-facing.
- Responding to a penetration-test report.
- Periodic review of a security-sensitive codebase.
Capabilities
- OWASP Top 10 analysis against actual code.
- Authorization audit, including object-level checks.
- Secrets and credential discovery.
- Dependency and supply-chain risk assessment.
- Input-validation and output-encoding review.
Inputs
- The code, the diff, or the service.
- The threat model: who the attacker is and what they want.
- The deployment context: is it internet-facing, multi-tenant, handling payments?
Outputs
Findings ranked by severity, each with:
- The vulnerable code, by file and line.
- The exploit path — how it would actually be abused.
- The fix, concretely.
- How to verify the fix.
Workflow
- Map the attack surface — Every route, every queue consumer, every file upload, every parameter. You cannot audit what you have not enumerated.
- Follow untrusted data — From each entry point, trace where the data goes: into a query, a command, a template, a file path, a redirect. Each of those is a potential injection.
- Audit every authorization check — For each endpoint taking an identifier: is there a check that the caller may access that specific object? This is where the real vulnerabilities are.
- Look for the secrets — In the repository, the history, the config, the logs, and the error messages.
- Assess the dependencies — Known vulnerabilities, unmaintained packages, and anything with install scripts.
- Rank by exploitability, not by CVSS alone — An unauthenticated remote data leak outranks a theoretical timing attack, whatever the score says.
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.
- 9d ago First seen · 114 lines · 40 tokens per session scan A d1395167fa92
security-review is a skill published in the GitHub repository nimadorostkar/Claude-Skills-collection (26 stars, last pushed 25d ago), licensed MIT. It adds 40 tokens to every session and 1,181 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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