What is ct-security-review?

A security-focused code review method for finding exploitable vulnerabilities, such as injection, cross-site scripting, and authentication or authorization flaws.

Use it to audit a specified file, code change, or codebase and report only vulnerabilities with strong evidence, including their severity.

It traces attacker-controlled data through the code and checks the surrounding protections, reducing false alarms from pattern-only reviews.

ct-security-review — Skill for Claude Code by canonical

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 canonical/charm-tech --skill ct-security-review

Clone the repo

git clone --depth 1 https://github.com/canonical/charm-tech

Made for: Claude Code.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/canonical/charm-tech/ct-security-review.svg)](https://agentmods.dev/skills/canonical/charm-tech/ct-security-review)

Your own site

<a href="https://agentmods.dev/skills/canonical/charm-tech/ct-security-review"><img src="https://agentmods.dev/badge/skills/canonical/charm-tech/ct-security-review.svg" alt="Measured on agentmods" height="20"></a>

Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,857 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 2 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 98% copy Near-identical to another mod 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.

Model	Per session	Once invoked
Fable 5.1	$0.00062	$0.02857
Opus 5	$0.00031	$0.01429
Sonnet 5	$0.00012	$0.00571
Haiku 4.5	$0.00006	$0.00286

Measured 7d ago against content hash d6197891a5c9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

ct-security-review scanned grade A with 2 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.

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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

response = requests.get(f"{settings.SEER_AUTOFIX_URL}{path}")

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

child_process.exec(user) # Node.js

Origin

This is a copy

98% identical to security-review — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/engineering/ct-security-review/SKILL.md · 315 lines

How it starts

The opening of the file, as written. The whole thing — 315 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Security Review Skill

Identify exploitable security vulnerabilities in code. Report only HIGH CONFIDENCE findings—clear vulnerable patterns with attacker-controlled input.

Scope: Research vs. Reporting

CRITICAL DISTINCTION:

Report on: Only the specific file, diff, or code provided by the user
Research: The ENTIRE codebase to build confidence before reporting

Before flagging any issue, you MUST research the codebase to understand:

Where does this input actually come from? (Trace data flow)
Is there validation/sanitization elsewhere?
How is this configured? (Check settings, config files, middleware)
What framework protections exist?

Do NOT report issues based solely on pattern matching. Investigate first, then report only what you're confident is exploitable.

Confidence Levels

Level	Criteria	Action
HIGH	Vulnerable pattern + attacker-controlled input confirmed	Report with severity
MEDIUM	Vulnerable pattern, input source unclear	Note as "Needs verification"
LOW	Theoretical, best practice, defense-in-depth	Do not report

Do Not Flag

General Rules

Test files (unless explicitly reviewing test security)
Dead code, commented code, documentation strings
Patterns using constants or server-controlled configuration
Code paths that require prior authentication to reach (note the auth requirement instead)

Server-Controlled Values (NOT Attacker-Controlled)

These are configured by operators, not controlled by attackers:

Source	Example	Why It's Safe
Django settings	`settings.API_URL`, `settings.ALLOWED_HOSTS`	Set via config/env at deployment
Environment variables	`os.environ.get('DATABASE_URL')`	Deployment configuration
Config files	`config.yaml`, `app.config['KEY']`	Server-side files
Framework constants	`django.conf.settings.*`	Not user-modifiable
Hardcoded values	`BASE_URL = "https://api.internal"`	Compile-time constants

Read the full file on GitHub · 315 lines

Files

What ships with it

21 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.

7d ago First seen · 315 lines · 62 tokens per session scan A d6197891a5c9

Subscribe to this mod's changes

ct-security-review is a skill published in the GitHub repository canonical/charm-tech (2 stars, last pushed 22d ago), licensed Apache-2.0. It adds 62 tokens to every session and 2,857 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). It is 98% identical to security-review, differing in 8 lines, and is treated as a copy.

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ct-security-review