deepsec

A runbook for running DeepSec against a Vercel project checkout. DeepSec is a security scanner that examines application source code and produces findings.

In plain words
What is it for?
Use it to initialize DeepSec, provide project context, run an initial scan, and create a readable security findings report.
Why use it?
It defines a bounded first-pass workflow, explains where scan state belongs, and sets rules for credentials, setup files, and generated reports.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/vercel-labs/dev3000/deepsec
Any agent
npx skills add vercel-labs/dev3000 --skill deepsec
Clone the repo
git clone --depth 1 https://github.com/vercel-labs/dev3000

Made for: Claude Code, Codex.

Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 912 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00041 $0.00912
Opus 5 $0.00020 $0.00456
Sonnet 5 $0.00008 $0.00182
Haiku 4.5 $0.00004 $0.00091

Measured 2d ago against content hash d09b74a1ca27, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, 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 2d 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.

.agents/skills/deepsec/SKILL.md · 58 lines

How it starts

The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DeepSec Dev3000 Runbook

Use this skill to turn the manual DeepSec workflow into a repeatable dev3000 run against the current Vercel project checkout.

Operating Policy

  • Work from the real project checkout at /workspace/repo.
  • Do not write AI credentials into .deepsec/.env.local or any tracked file. The dev3000 runtime passes AI Gateway credentials through the process environment.
  • Default dev3000 runs are a bounded first pass. Do not run an unbounded process or revalidate command unless the user explicitly asks for a full DeepSec scan in run-specific instructions.
  • Keep generated scan state in the locations DeepSec already gitignores. Commit only the durable setup/context files and human-readable findings report.
  • Treat DeepSec as a coding agent with shell access. Do not run it on untrusted source inputs.

Default Flow

  1. Inspect the project shape:
    • Read README.md if present.
    • Read AGENTS.md or CLAUDE.md if present.
    • Skim representative files for auth, middleware, request handlers, data access, billing, webhooks, and security-sensitive boundaries.
  2. Initialize DeepSec if needed:
    • If .deepsec/ is absent, run npx --yes deepsec@latest init.
    • If .deepsec/ already exists, do not force overwrite it.
  3. Install DeepSec workspace dependencies:
    • Run corepack pnpm install from .deepsec/.
    • Ensure the Claude Agent SDK native binary that DeepSec actually uses is available. Do not run a Claude Code postinstall; DeepSec uses @anthropic-ai/claude-agent-sdk.
    • If corepack pnpm is unavailable, run pnpm install only after confirming pnpm exists.
  4. Fill the generated project context:
    • Read .deepsec/node_modules/deepsec/SKILL.md.
    • Read .deepsec/data/<id>/SETUP.md.
    • Replace .deepsec/data/<id>/INFO.md with concise project-specific context.
    • Keep INFO.md to roughly 50-100 lines.
    • Use 3-5 examples per section. Name local primitives such as auth helpers, middleware, database clients, webhook handlers, and privileged APIs.
    • Do not include line numbers, generic CWE lists, or broad framework summaries.
  5. Run the scan:
    • Run corepack pnpm deepsec scan from .deepsec/.
  6. Run bounded AI processing:
    • Default command: corepack pnpm deepsec process --limit 25 --concurrency 2 --batch-size 3.
    • If the candidate set is below the limit, state that all discovered candidates were processed.
    • If the user explicitly requested a full run, use the requested limit/concurrency or omit --limit.
    • If the process command fails, stop and report the failure. Do not generate a manual fallback report from regex candidates.
  7. Generate the findings report:
    • Run corepack pnpm deepsec export --format md-dir --out ./findings.
    • If there are no findings, create .deepsec/findings/README.md summarizing that this bounded pass found no findings and include the exact commands that were run.
  8. Summarize the run:
    • Include commands run, project id, limit/concurrency, and whether the report contains findings.
    • Do not include a "Next Steps - Full Scan" section by default.
    • Only include a follow-up scan section if DeepSec reports unprocessed candidates or the user explicitly asked about deeper coverage. Label it "Optional Deeper Follow-Up" and explain exactly how it differs from the completed run.

Read the full file on GitHub · 58 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. 2d ago First seen · 58 lines · 41 tokens per session scan A d09b74a1ca27

Subscribe to this mod's changes

deepsec is a skill published in the GitHub repository vercel-labs/dev3000 (1,573 stars, last pushed 6d ago), licensed MIT. It adds 41 tokens to every session and 912 once invoked, about $0.0002 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.

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