audit-setup

A command that creates a security audit log: a lasting record of important actions in an application.

In plain words
What is it for?
Use it to initialize audit logging, produce time-based reports, configure suspicious-activity alerts, and create compliance checklists for GDPR, SOC 2, or HIPAA.
Why use it?
It helps teams trace activity, investigate suspicious behavior, and prepare evidence for security and privacy reviews.

Command

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 commands/alphaaiservice/cortex/audit-setup
Clone the repo
git clone --depth 1 https://github.com/alphaaiservice/cortex
Per session 40 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 7,079 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 $0.00040 $0.07079
Opus 5 $0.00020 $0.03540
Sonnet 5 $0.00008 $0.01416
Haiku 4.5 $0.00004 $0.00708

Measured yesterday against content hash 11473a6bc710, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

audit-setup 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 yesterday.

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.

commands/audit-setup.md · 837 lines

How it starts

The opening of the file, as written. The whole thing — 837 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Security Audit Logging System

Action: $ARGUMENTS (default: init)

Parse $ARGUMENTS:

  • init — Generate the complete audit logging system (schema, middleware, service, dashboard)
  • report — Generate an audit report for a specified time period
  • alerts — Configure alerting rules for suspicious activity patterns
  • compliance — Generate compliance checklist and evidence for GDPR/SOC 2/HIPAA
  • No argument = init

Step 0: Detect Project Context

echo "=== Project Type ==="
ls package.json pyproject.toml build.gradle.kts pom.xml 2>/dev/null

echo "=== Backend Language ==="
if [ -f "pyproject.toml" ] || [ -f "requirements.txt" ]; then
  echo "Python/FastAPI detected"
elif [ -f "package.json" ] && grep -q "nestjs" package.json 2>/dev/null; then
  echo "NestJS detected"
elif [ -f "build.gradle.kts" ] || [ -f "pom.xml" ]; then
  echo "Spring Boot detected"
fi

echo "=== Existing Audit/Logging ==="
grep -rn "audit\|AuditLog\|audit_log" --include="*.py" --include="*.ts" --include="*.java" . 2>/dev/null | grep -v node_modules | head -20

echo "=== Auth System ==="
find . -maxdepth 5 -path "*/auth*" -name "*.py" -o -path "*/auth*" -name "*.ts" -o -path "*/auth*" -name "*.java" 2>/dev/null | grep -v node_modules | head -10

echo "=== Database ==="
grep -rn "mysql\|mongodb\|DATABASE_URL\|MONGO" .env* 2>/dev/null | head -5

Determine:

  • Backend language (Python/NestJS/Spring Boot)
  • Which database to use for audit logs (MySQL for structured, MongoDB for high-volume)
  • Whether auth system exists (to instrument login/logout events)

Step 1: Audit Event Categories

Define the complete list of auditable events:

Authentication Events (MUST audit)

Event Severity Data Captured
auth.login.success INFO user_id, IP, user_agent, method (password/oauth)
auth.login.failure WARNING email_attempted, IP, user_agent, failure_reason
auth.logout INFO user_id, IP
auth.token.refresh INFO user_id, IP
auth.password.change WARNING user_id, IP
auth.password.reset.request WARNING email, IP
auth.password.reset.complete WARNING user_id, IP
auth.2fa.enable WARNING user_id, IP
auth.2fa.disable CRITICAL user_id, IP
auth.account.lockout CRITICAL user_id, IP, failed_attempts

Read the full file on GitHub · 837 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. yesterday First seen · 837 lines · 40 tokens per session scan A 11473a6bc710

Subscribe to this mod's changes

audit-setup is a command published in the GitHub repository alphaaiservice/cortex (1 stars, last pushed 26d ago), licensed MIT. It adds 40 tokens to every session and 7,079 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 2026-08-31.