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.
npx agentmods add rules/adobe/aem-desktop/security-global-output-encodinggit clone --depth 1 https://github.com/adobe/aem-desktopWhat 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 | $0.00019 | $0.00978 |
| Opus 5 | $0.00010 | $0.00489 |
| Sonnet 5 | $0.00004 | $0.00196 |
| Haiku 4.5 | $0.00002 | $0.00098 |
Grade A, and why
security-global-output-encoding 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.
This is a copy
100% identical to security-global-output-encoding — 0 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.
How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Output Encoding & Escaping
Output encoding and parameterization are critical controls for stopping injection attacks. Use context-specific encoding whenever untrusted data is rendered, and pair it with parameterized interfaces for SQL, shell, or LDAP operations. This requirement is distinct from input validation.
All violations must include a clear explanation of which rule was triggered and why.
Critical: Output Encoding ≠ Input Validation
Input validation alone does NOT prevent injection attacks.
- Input Validation: Ensures data is well-formed before entering system
- Output Encoding: Prevents injection by encoding data for output context
Context-Specific Encoding
Encoding method MUST match output context. Wrong encoding = vulnerability.
1. HTML Context
Inserting into HTML body: Encode & < > " ' /
2. HTML Attribute Context
- Always quote attributes
- Use HTML attribute encoding
- Never use event handlers:
onclick,onerror,onload - Avoid
hrefwithjavascript:URLs
3. JavaScript Context
- Use JSON encoding for data (e.g., JSON.stringify) before inserting untrusted values.
- When embedding JSON in tags, escape < (\u003c) at minimum, and also escape & (\u0026) and the Unicode line/paragraph separators (\u2028, \u2029) to block script-breakout payloads
- Prefer with textContent; parse later instead of concatenating data into executable scripts.
- Avoid inline scripts, event handler attributes, and javascript: URLs for untrusted data.
- Layer with CSP for defense in depth, but never treat it as a substitute for correct encoding.
4. CSS Context
Avoid entirely - extremely dangerous. If unavoidable: Use CSS hex escaping. Prefer allowlist validation for class names.
5. URL Context
- Use URL/percent encoding
- Allowlist protocols:
https:,http:,mailto: - Block:
javascript:,data:,vbscript:
6. SQL Context
PRIMARY defense: Parameterized queries / Prepared statements. Never rely on escaping alone.
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.
- yesterday First seen · 130 lines · 19 tokens per session scan A c8e418e38ebb
security-global-output-encoding is a cursor rule published in the GitHub repository adobe/aem-desktop (2 stars, last pushed 7d ago), licensed Apache-2.0. It adds 19 tokens to every session and 978 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to security-global-output-encoding, differing in 0 lines, and is treated as a copy.
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