deepsec

deepsec is a skill for Claude Code, Codex from Kevin-Liu-01/Agent-Machines. It costs 132 tokens per session (2,865 once invoked), scanned A, original, MIT.

A security scanner that uses coding agents to inspect a local codebase for vulnerabilities, meaning weaknesses attackers could exploit.

In plain words
What is it for?
Use it for vulnerability scans, security reviews, checks after a new CVE, and audits of customer, partner, or internal codebases.
Why use it?
It helps identify security problems before software is shipped or while reviewing an unfamiliar repository.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions CLAUDE.md; mentions subagents; mentions AGENTS.md.

Good fit Use it for vulnerability scans, security reviews, checks after a new CVE, and audits of customer, partner, or internal codebases.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kevin-liu-01/agent-machines/deepsec
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 Kevin-Liu-01/Agent-Machines --skill deepsec
Clone the repo
git clone --depth 1 https://github.com/Kevin-Liu-01/Agent-Machines

Made for: Claude Code, Codex.

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 deepsec

README.md
[![agentmods](https://agentmods.dev/badge/skills/kevin-liu-01/agent-machines/deepsec/github.svg)](https://agentmods.dev/skills/kevin-liu-01/agent-machines/deepsec)
Your own site
<a href="https://agentmods.dev/skills/kevin-liu-01/agent-machines/deepsec"><img src="https://agentmods.dev/badge/skills/kevin-liu-01/agent-machines/deepsec/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 deepsec

Your own site · 80×15
<a href="https://agentmods.dev/skills/kevin-liu-01/agent-machines/deepsec"><img src="https://agentmods.dev/badge/skills/kevin-liu-01/agent-machines/deepsec.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 132 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,865 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 3 findings, up to high

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 →

  • high Privilege Escalation · line 61
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Excessive Agency · line 157
    Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.
    Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
  • medium MCP Rug Pull · line 80
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
How audits are shown
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 $0.00132 $0.02865
Opus 5 $0.00066 $0.01432
Sonnet 5 $0.00026 $0.00573
Haiku 4.5 $0.00013 $0.00286

Measured 10d ago against content hash 8ac3bc772c73, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

deepsec 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 10d 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.

knowledge/skills/deepsec/SKILL.md · 296 lines

How it starts

The opening of the file, as written. The whole thing — 296 lines — stays where its author put it; the contents beside it link to each section on GitHub.

deepsec — Agent-Powered Vulnerability Scanner

Run vercel-labs/deepsec — Vercel's open-source security harness — against any local codebase Kevin asks to audit. deepsec installs into a .deepsec/ directory inside the target repo (checked into the same git repo so config and matchers travel with the code) and uses coding agents to investigate security-sensitive files at maximum thinking.

When this fires

  • Kevin says "deepsec", "security scan ", "scan for vulns", "find security bugs in ", "audit X for vulnerabilities", or "run a security review on "
  • Before shipping a new service or backend to production
  • After a CVE drops in a peer/customer codebase
  • Customer / open-source repo due diligence (Kevin reviewing partner repos the way Vercel did with dub.co and Unkey)
  • Periodic deep audit on Sigil UI, Dedalus monorepo, or any repo Kevin owns

Cost discipline (read this before running anything)

deepsec uses Opus 4.7 / GPT 5.5 at max reasoning. Full scans cost real money:

Files Approx cost Approx wall time
100 $25–60 5–15 min
500 $130–300 25–60 min
2,000 $500–1,200 1.5–4 hr

Iron rule: never run a full process without explicit confirmation from Kevin of the expected dollar amount. Always start with --limit 50 to calibrate. For repos > 1,000 files, propose Vercel Sandbox fanout or Codex/GPT 5.5 as a cheaper backend before suggesting a default Opus run.

Prerequisites

  • Node.js 22+ (node -v)
  • pnpm available (deepsec scaffold uses pnpm; npm/yarn work but pnpm is the documented path)
  • One of:
    • Logged-in claude CLI subscription (default — non-sandbox runs reuse it)
    • Logged-in codex CLI subscription
    • AI_GATEWAY_API_KEY=vck_... (Vercel AI Gateway — covers both Claude and Codex with one token)
    • Or explicit ANTHROPIC_AUTH_TOKEN / OPENAI_API_KEY

If sandbox fanout is needed: a Vercel account with OIDC tokens or access tokens.

Read the full file on GitHub · 296 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. 10d ago First seen · 296 lines · 132 tokens per session scan A 8ac3bc772c73

Subscribe to this mod's changes

deepsec is a skill published in the GitHub repository Kevin-Liu-01/Agent-Machines (26 stars, last pushed 9d ago), licensed MIT. It adds 132 tokens to every session and 2,865 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.

Related

Other skills, from other repositories

agent-reach

An internet-search and platform-access router for finding information across websites and services such as Reddit, X, GitHub, YouTube, and job sites.

Panniantong/Agent-Reach · 349 tokens

xiaohongshu-search-full

Search Xiaohongshu (XHS / RedNote) notes by keyword with full field extraction including body text, topics/tags, image list URLs, video stream URL, publish timestamp, and all engagement stats (likes, collects, comments, shares). Supports all page filter options: sort order (general, latest, most liked, most commented…

browser-act/skills · 254 tokens

using-ao

Catalog of the AO (Agent Orchestrator) ao CLI: spawning workers, managing sessions and projects, sending messages, controlling the shared browser, previewing pages, and daemon control. Use when using the ao CLI, spawning workers, or managing AO sessions in an AO workspace.

Untrivial-ai/agent-orchestrator · 62 tokens

1688-product-detail

Extracts comprehensive wholesale product data from 1688.com product detail pages: title, tiered pricing, SKU variants with dimensions/weight, product images, seller info, shop scores, buyer protection, cross-border flags, product attributes, coupon/promotion data, and review stats. Use when user mentions 1688…

browser-act/skills · 212 tokens

youtube-channel-business-email

YouTube channel business email and contact extractor: accepts a channel id (UCxxx), handle (@name), or URL; navigates the channel About view; extracts the business email from the description text plus full channel metadata (name, id, country, subscriber count, view count, video count, joined date, external links…

browser-act/skills · 324 tokens

google-maps-contact-extract

Extracts business contact details from Google Maps search results and place detail pages, then visits each business website to collect emails, phone numbers, and social media profiles (Facebook, Instagram, Twitter/X, LinkedIn, YouTube, TikTok, Pinterest, Discord). Use when user mentions Google Maps contact extraction…

browser-act/skills · 152 tokens