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security-review

security-review is a skill for Claude Code from Srajangpt1/ai-security-crew. It costs 143 tokens per session (1,198 once invoked), scanned A, original, MIT.

A security assessment performed before coding a new feature. It identifies the technologies involved, rates the likely risk, and lists security requirements to consider during implementation.

In plain words
What is it for?
Use it before developing a feature to understand its attack surface, choose appropriate safeguards, and plan security checks for the relevant language, framework, database, and infrastructure.
Why use it?
Security decisions made early are easier to apply than fixes discovered after a feature is built. The review highlights concerns such as authentication, personal data, file uploads, and external integrations.

Skill for Claude Code

Written for Claude Code: $ARGUMENTS substitution.

Part of the mcp-security-review plugin — 3 skills, 3 commands, 1 MCP server shipped together

not rated 68repo 4mo ago A scan 143 tokens original MIT

Good fit Use it before developing a feature to understand its attack surface, choose appropriate safeguards, and plan security checks for the relevant language, framework, database, and infrastructure.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/srajangpt1/ai-security-crew/security-review
View source ↗ Srajangpt1/ai-security-crew
Install

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.

Any agent
npx skills add Srajangpt1/ai-security-crew --skill security-review
Clone the repo
git clone --depth 1 https://github.com/Srajangpt1/ai-security-crew

Made for: Claude Code.

Or install mcp-security-review, the plugin that ships this one along with the rest of its 3 skills, 3 commands, 1 MCP server.

Wrote 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.

agentmods badge for security-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/srajangpt1/ai-security-crew/security-review/github.svg)](https://agentmods.dev/skills/srajangpt1/ai-security-crew/security-review)
Your own site
<a href="https://agentmods.dev/skills/srajangpt1/ai-security-crew/security-review"><img src="https://agentmods.dev/badge/skills/srajangpt1/ai-security-crew/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.

agentmods 80×15 button for security-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/srajangpt1/ai-security-crew/security-review"><img src="https://agentmods.dev/badge/skills/srajangpt1/ai-security-crew/security-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 143 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,198 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00143 $0.01198
Opus 5 $0.00072 $0.00599
Sonnet 5 $0.00029 $0.00240
Haiku 4.5 $0.00014 $0.00120

Measured 12d ago against content hash 7bc8ba24afdd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

security-review scanned grade A with 0 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 12d 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/security-review/SKILL.md · 118 lines

How it starts

The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Perform a pre-coding security review for the following task:

$ARGUMENTS

What to do

Analyze the task description above and produce a structured security assessment. If no task description was provided in the arguments, ask the user to describe what they are building and optionally their tech stack before proceeding.

Step 1 — Identify Technologies

Detect technologies from the description:

  • Languages: Python, JavaScript, TypeScript, Java, Go, Ruby, PHP, Rust, C#
  • Frameworks: Django, FastAPI, Flask, Express, Next.js, Spring, Rails, Laravel
  • Databases: PostgreSQL, MySQL, MongoDB, Redis, SQLite, DynamoDB
  • Auth: JWT, OAuth2, SAML, session-based, API keys
  • Infrastructure: AWS, GCP, Azure, Docker, Kubernetes
  • Other: GraphQL, REST API, gRPC, WebSockets, message queues

Step 2 — Assess Risk Level

Critical — payments/financial transactions, healthcare/PHI, authentication system, cryptographic key management, admin functionality, multi-tenant data isolation

High — PII collection/storage, file uploads, external API integrations, session management, password handling, OAuth flows, database schema changes

Medium — user-generated content, search functionality, data exports, email/notification systems, third-party SDKs, internal APIs

Low — static content, read-only public data, internal tooling with no sensitive data

Step 3 — Identify Security Categories

Select all applicable:

  • authentication — login, registration, password reset, MFA
  • authorization — access control, roles, permissions, IDOR
  • data_validation — input validation, sanitization, output encoding
  • cryptography — encryption, hashing, key management, TLS
  • api_security — endpoints, rate limiting, CORS, versioning
  • web_security — XSS, CSRF, clickjacking, CSP
  • database — SQL injection, ORM, connection security
  • secrets_management — credentials, env vars, vaults
  • error_handling — information disclosure, stack traces
  • logging — audit trails, sensitive data in logs
  • cloud_security — IAM, S3 permissions, VPC, security groups
  • supply_chain_security — dependencies, lockfiles

Read the full file on GitHub · 118 lines

Changes

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.

  1. 12d ago First seen · 118 lines · 143 tokens per session scan A 7bc8ba24afdd

Subscribe to this mod's changes

security-review is a skill published in the GitHub repository Srajangpt1/ai-security-crew (68 stars, last pushed 4mo ago), licensed MIT. It adds 143 tokens to every session and 1,198 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Security
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