implementing-aqua-security-for-container-scanning

implementing-aqua-security-for-container-scanning is a skill for Claude Code, Codex from adriannoes/awesome-agentic-ai. It costs 41 tokens per session (1,776 once invoked), scanned A, original, MIT.

A guide to using Trivy, an open-source scanner for container images, code, and cloud environments. It checks for known vulnerabilities, unsafe settings, exposed secrets, software bills of materials, and license issues.

In plain words
What is it for?
Use it to scan local images, registries, Kubernetes workloads, dependencies, and repositories, and to add those checks to systems such as GitHub Actions, GitLab CI, or Jenkins.
Why use it?
It finds security and compliance problems before container images are deployed. Adding scans to CI/CD pipelines helps catch issues during development instead of after release.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is trivy config --severity HIGH,CRITICAL ./terraform/.

Good fit Use it to scan local images, registries, Kubernetes workloads, dependencies, and repositories, and to add those checks to systems such as GitHub Actions, GitLab CI, or Jenkins.

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Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/adriannoes/awesome-agentic-ai
agentmods
npx agentmods add skills/adriannoes/awesome-agentic-ai/implementing-aqua-security-for-container-scanning

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 implementing-aqua-security-for-container-scanning

README.md
[![agentmods](https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/implementing-aqua-security-for-container-scanning/github.svg)](https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/implementing-aqua-security-for-container-scanning)
Your own site
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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 implementing-aqua-security-for-container-scanning

Your own site · 80×15
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/implementing-aqua-security-for-container-scanning"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/implementing-aqua-security-for-container-scanning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,776 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 pass 7 Sept 2026
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 $0.00041 $0.01776
Opus 5 $0.00020 $0.00888
Sonnet 5 $0.00008 $0.00355
Haiku 4.5 $0.00004 $0.00178

Measured 7d ago against content hash 37d6bcd5314e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

implementing-aqua-security-for-container-scanning 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 7d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/agent.py, scripts/process.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

cursor-claude-codex/skills/anthropic-cybersecurity-skills/skills/implementing-aqua-security-for-container-scanning/SKILL.md · 266 lines

How it starts

The opening of the file, as written. The whole thing — 266 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Implementing Aqua Security for Container Scanning

Overview

Aqua Security provides Trivy, the world's most popular open-source universal security scanner, designed to find vulnerabilities, misconfigurations, secrets, SBOM data, and license issues in containers, Kubernetes, code repositories, and cloud environments. Trivy covers OS packages (Alpine, Debian, Ubuntu, RHEL, etc.) and language-specific dependencies (npm, pip, Maven, Go modules, Cargo, etc.) with vulnerability databases sourced from NVD, vendor advisories, and GitHub Security Advisories. The enterprise Aqua Platform extends Trivy with centralized policy management, runtime protection, and compliance reporting.

When to Use

  • When deploying or configuring implementing aqua security for container scanning capabilities in your environment
  • When establishing security controls aligned to compliance requirements
  • When building or improving security architecture for this domain
  • When conducting security assessments that require this implementation

Prerequisites

  • Docker installed for local image scanning
  • CI/CD platform (GitHub Actions, GitLab CI, Jenkins, etc.)
  • Container registry access (Docker Hub, ECR, GCR, ACR, Harbor)
  • Trivy CLI (trivy) or Trivy Operator for Kubernetes
  • Aqua Platform license for enterprise features (optional)

Core Scanning Capabilities

Image Vulnerability Scanning

Trivy scans container images layer by layer, identifying CVEs in OS packages and application dependencies. It supports scanning local images, remote registry images, and tar archives.

# Scan a remote image
trivy image python:3.11-slim

# Scan with severity filter
trivy image --severity HIGH,CRITICAL nginx:latest

# Scan and fail CI if critical CVEs found
trivy image --exit-code 1 --severity CRITICAL myapp:latest

# Generate SBOM in CycloneDX format
trivy image --format cyclonedx --output sbom.json myapp:latest

Filesystem and Repository Scanning

# Scan project directory for vulnerabilities in dependencies
trivy fs --scanners vuln,secret,misconfig .

# Scan a specific lockfile
trivy fs --scanners vuln package-lock.json

# Scan git repository
trivy repo https://github.com/org/project

Read the full file on GitHub · 266 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 7d ago First seen · 266 lines · 41 tokens per session scan A 37d6bcd5314e

Subscribe to this mod's changes

implementing-aqua-security-for-container-scanning is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 13d ago), licensed MIT. It adds 41 tokens to every session and 1,776 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 2026-09-03.

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