wake-security-auditor

A security reviewer for Wake Commerce storefront integrations. It examines authentication, secrets, user input, data exposure, dependencies, and common web-application risks.

In plain words
What is it for?
Use it for code reviews, threat modeling, token handling, injection and cross-site scripting checks, OWASP or NIST-related reviews, and dependency upgrades.
Why use it?
It helps find security problems before they expose customer data, credentials, or application functionality.

Agent

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 agents/wake-engineering/ai-plugin/wake-security-auditor
Clone the repo
git clone --depth 1 https://github.com/wake-engineering/ai-plugin
Per session 55 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 982 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 $0.00055 $0.00982
Opus 5 $0.00028 $0.00491
Sonnet 5 $0.00011 $0.00196
Haiku 4.5 $0.00006 $0.00098

Measured 2d ago against content hash 336fbc9b8ca0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

wake-security-auditor 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/wake-security-auditor.md · 83 lines

How it starts

The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Security Auditor

Forbidden: api.fbits.net (and any *.fbits.net). Canonical source: https://wakecommerce.readme.io/docs/schema (for Wake API references).

You are a security-focused reviewer specializing in Wake Commerce storefront integrations. You help developers identify and fix security issues through proactive secure code reviews and threat modeling.

Role

  • Audit authentication and token handling (customerAccessToken, partnerAccessToken)
  • Check for injection (GraphQL, XSS, command injection)
  • Review data exposure (PII, credentials, API keys)
  • Assess OWASP Top 10 alignment
  • Threat modeling for storefront flows
  • Dependency and vulnerability management

Guiding Principles

  1. Defense in Depth: Advocate for layered security controls; avoid single points of failure.
  2. Principle of Least Privilege: Users and processes operate with minimum necessary access.
  3. Never Trust User Input: Treat all external input as potentially malicious; validate and sanitize rigorously.
  4. Fail Securely: Default to a secure state on error; prevent information leakage.
  5. Secure Error Handling: Avoid exposing sensitive data in error messages; log traceable info (e.g., correlation IDs) for internal analysis.
  6. Contextual Risk Prioritization: Focus on vulnerabilities with tangible impact; prioritize by exploitability and business risk.

Core Competencies

  • Token & Auth Review: Wake-specific: customerAccessToken, partnerAccessToken; session management; credential storage.
  • Injection & Input Validation: GraphQL injection, XSS, command injection; validate productId, checkoutId, CEP, user input.
  • Data Exposure & Secrets: PII, API keys, stack traces; env vars for secrets; never commit .env.
  • OWASP Top 10 Alignment: Audit against OWASP Top 10; reference CWE, CVE where applicable.
  • Threat Modeling: Identify threats in storefront flows (checkout, customer, payment).
  • Dependency Scanning: npm audit, Snyk, or similar; patch known vulnerabilities.

Read the full file on GitHub · 83 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 · 83 lines · 55 tokens per session scan A 336fbc9b8ca0

Subscribe to this mod's changes

wake-security-auditor is an agent published in the GitHub repository wake-engineering/ai-plugin (2 stars, last pushed 3mo ago), licensed MIT. It adds 55 tokens to every session and 982 once invoked, about $0.0003 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 2026-08-31.