Rendering Untrusted Content logo

Rendering Untrusted Content

Community
wdm0006
rendering-untrusted-content

Renders stored, authored, or imported content into HTML without shipping XSS — auditing every autoescape bypass (|safe, Markup, innerHTML), sanitizing Markdown output with an allowlist, escaping on both the server and the DOM, and writing sanitization tests that assert on the right copy of the string. Use when adding a Markdown or rich-text filter, rendering user/admin-authored content, reviewing a template that marks HTML trusted, building a client that injects values into innerHTML, or fixing an XSS report.

Overview

Publisherwdm0006
Repositorypython-skills
Skill namerendering-untrusted-content
Stars
111
Forks
17
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by wdm0006 on GitHub. Read the source before you install it.

Installation

Install the Rendering Untrusted Content AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/wdm0006/python-skills/tree/main/skills/common/rendering-untrusted-content
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/wdm0006/python-skills.git /tmp/python-skills
mkdir -p .claude/skills
cp -r /tmp/python-skills/skills/common/rendering-untrusted-content .claude/skills/rendering-untrusted-content
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rendering Untrusted Content in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Rendering Untrusted Content on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Rendering Untrusted Content is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Rendering Untrusted Content

Template engines autoescape by default, so the vulnerable surface is small and enumerable: it is exactly the places where something says this value is already safe HTML. Find those first; everything else is already handled.

Step 1 — Enumerate the trust bypasses

bash
# Server-side (Jinja/Django templates + the Python that feeds them)
grep -rnE '\|\s*safe|Markup\(|autoescape false|mark_safe' templates/ src/

# Client-side
grep -rnE 'innerHTML|outerHTML|insertAdjacentHTML|document\.write' web/ static/

Every hit is a claim that needs justification. A |safe on a value that came from a database column is a claim about everything that has ever been written to that column, including via an import path nobody remembers.

Step 2 — Markdown output is not sanitized HTML

Markdown renderers pass raw HTML through by design — that is a documented feature, not a bug. So a shared template filter shaped like this is an XSS sink:

python
# BAD — the filter marks arbitrary stored markup trusted.
def _markdown(text: str) -> Markup:
    return Markup(markdown.markdown(text, extensions=["extra", "tables"]))

"Only admins author content" is not a boundary. As soon as there is an import path, a seed script, or a second author, the content store is untrusted input.

Render, then sanitize with an allowlist, and only then mark trusted:

python
import markdown, nh3
from markupsafe import Markup

ALLOWED_TAGS = {
    "p", "br", "hr", "em", "strong", "code", "pre", "blockquote",
    "h1", "h2", "h3", "h4", "h5", "h6", "ul", "ol", "li",
    "a", "img", "table", "thead", "tbody", "tr", "th", "td",
}
ALLOWED_ATTRS = {
    "a": {"href", "title", "rel"},
    "img": {"src", "alt", "title"},
    "th": {"style", "align"},
    "td": {"style", "align"},
}

def _markdown(text: str) -> Markup:
    html = markdown.markdown(text, extensions=["extra", "tables"])
    return Markup(nh3.clean(
        html,
        tags=ALLOWED_TAGS,
        attributes=ALLOWED_ATTRS,
        filter_style_properties={"text-align"},   # see below
    ))

Do not hand-roll the allowlist logic. Use a maintained HTML sanitizer (nh3, the Rust/ammonia-backed successor to bleach). Regex-stripping <script> is not sanitization.

The table-alignment trap

Markdown's tables extension encodes column alignment as an inline style — <th style="text-align: left;">. An allowlist that drops style is "secure" and silently removes alignment from every table in the corpus. Allow style on table cells and constrain which properties survive (filter_style_properties).

Then note that the sanitizer normalizes what it keeps: text-align: left; comes back as text-align:left — no space, no trailing semicolon. An exact-output test must expect the normalized form, not the string Markdown emitted, or it fails on a correct fix.

Step 3 — A shared filter has the whole corpus as its blast radius

One filter feeds every post body, every FAQ answer, every description. Changing it re-renders all of them at once, and the failure mode is not a crash — it is content quietly losing a construct.

Render every piece of authored content before and after the change and diff it character by character, then keep that as a regression test:

python
@pytest.mark.parametrize("path", sorted(CONTENT_DIR.glob("*.md")))
def test_authored_content_is_unchanged_by_sanitization(path):
    raw = markdown.markdown(path.read_text(), extensions=EXTENSIONS)
    assert _markdown(path.read_text()) == raw

If no authored file contains raw HTML, that equality holds and any future diff is a genuine regression. If some file does need raw HTML, you have found the one case worth an explicit decision instead of discovering it in production.

Step 4 — Test the copy of the string that actually matters

The same value is often rendered several times on one page: in prose, in <meta> tags, and inside a JSON-LD <script> block. A whole-document assertion therefore reports a vulnerability that isn't one:

python
# BAD — fails even when the prose is correctly sanitized.
assert "<script>alert(1)</script>" not in html

Template tojson filters emit HTML-safe JSON — angle brackets become \u003c / \u003e, so the JSON-LD copy cannot break out of its <script> element and is not a vulnerability. But the payload's text still appears there, so a document-wide assertion goes red while the prose is perfectly sanitized. Scope the assertion to the rendered prose:

python
article = extract_article_html(html)
assert "<script>" not in article
assert "&lt;script&gt;" in article        # proves it was escaped, not dropped

Assert the escaped form is present, not just that the dangerous form is absent — otherwise a filter that silently deletes the whole field passes.

Also scope the audit: a feed or export built from separately-escaped title/description fields that never includes the body is not part of this surface. Don't "fix" it.

Step 5 — Escape at both ends

Server-side escaping does nothing for a client that re-injects the same value through innerHTML. A card grid rendered safely by the server and a detail modal built with a template literal are two independent sinks, and the second one is usually the one that got missed.

js
// Prefer the API that cannot execute markup.
el.textContent = item.description;

// When you must build markup, escape into a local first.
const description = escapeHtml(item.description);
const tags = item.tags.map(escapeHtml).join(", ");
modal.innerHTML = `<p>${description}</p><footer>${tags}</footer>`;

Escaping into a const before the template literal is not just style: wrapping the expression inline pushes the line past the linter's length limit, and reflowing the HTML string to fit introduces leading whitespace that is visible inside white-space: pre-wrap blocks. Escape first, interpolate second.

Step 6 — "No event handlers" is a test that fails on clean code

Asserting that no on* attribute appears in rendered output looks like a strong XSS regression test, and it goes red immediately: application templates legitimately emit handlers (onclick="showDetail(3)"). A test that fails on correct code gets deleted within a week.

Allowlist the handlers your own templates emit and assert on the remainder:

python
handlers = re.findall(r'\son(\w+)="([^"]*)"', card_html)
assert handlers == [("click", "showDetail(3)")]

Pinning the full list (rather than not any(...)) also catches a second, injected handler alongside the legitimate one — presence assertions can't.

Checklist

- [ ] Every |safe / Markup() / mark_safe / innerHTML site enumerated and justified
- [ ] Markdown (and any rich-text) output passes through an allowlist sanitizer
      before being marked trusted — a maintained library, not a regex
- [ ] Allowlist keeps constructs the renderer depends on (table-cell style),
      and tests expect the sanitizer's normalized output
- [ ] Authored content diffed before/after the filter change, pinned by a test
- [ ] Sanitization tests assert on the rendered prose, and assert the escaped
      form is present — not just that the raw payload is absent
- [ ] Client-side injection points escape too (or use textContent)
- [ ] Handler/attribute assertions allowlist what the app's own templates emit

Frequently asked questions

What does the Rendering Untrusted Content AI skill do?

Renders stored, authored, or imported content into HTML without shipping XSS — auditing every autoescape bypass (|safe, Markup, innerHTML), sanitizing Markdown output with an allowlist, escaping on both the server and the DOM, and writing sanitization tests that assert on the right copy of the string. Use when adding a Markdown or rich-text filter, rendering user/admin-authored content, reviewing a template that marks HTML trusted, building a client that injects values into innerHTML, or fixing an XSS report.

Why use Rendering Untrusted Content on TypingMind?

Because you install it once and use it with any model. Rendering Untrusted Content is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Rendering Untrusted Content in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/wdm0006/python-skills/tree/main/skills/common/rendering-untrusted-content. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Rendering Untrusted Content?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Rendering Untrusted Content?

As many as you like. As long as a model supports skills, you can use Rendering Untrusted Content with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Rendering Untrusted Content AI skill free?

Yes. It is published on GitHub by wdm0006 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇