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.
git clone --depth 1 https://github.com/AdobeDocs/ff-services-docsWrote 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.
[](https://agentmods.dev/rules/adobedocs/ff-services-docs/security-lang-python)<a href="https://agentmods.dev/rules/adobedocs/ff-services-docs/security-lang-python"><img src="https://agentmods.dev/badge/rules/adobedocs/ff-services-docs/security-lang-python/github.svg" alt="Measured on agentmods" height="20"></a>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.
<a href="https://agentmods.dev/rules/adobedocs/ff-services-docs/security-lang-python"><img src="https://agentmods.dev/badge/rules/adobedocs/ff-services-docs/security-lang-python.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00000 | $0.01098 |
| Opus 5.5 | $0.00000 | $0.00439 |
| Sonnet 5.5 | $0.00000 | $0.00220 |
| Haiku 4.5 | $0.00000 | $0.00110 |
Grade A, and why
security-lang-python 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 1mo 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.
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.
How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
These rules apply to all Python code in the repository and aim to prevent common security risks through disciplined handling of input validation, output encoding, safe execution, secure configuration, and dependency hygiene.
All violations must include a clear explanation of which rule was triggered and why, to help developers understand and fix the issue effectively.
If code is in violation:
- Add a comment explaining why.
- Reference the rule number.
- Suggest a compliant alternative.
- Do not generate code that violates these rules unless explicitly marked with
# security-reviewed.
1. Validate All External Input
- Rule: All external input must be validated before being used in logic, database queries, file access, subprocess calls, or rendering.
- External input includes request data, CLI arguments, environment variables, file contents, deserialized payloads, and message queue data.
- Validation must use explicit type conversion, Pydantic models, regex allowlists, enums, or strict schema validation.
- Invalid input must be rejected — do not silently correct it.
2. Do Not Use User Input Directly in File Paths
-
Rule: User-controlled input must not directly determine file paths.
-
If input influences file access:
- Use
pathlib - Resolve against a fixed base directory
- Prevent directory traversal (
..) - Use allowlists where possible
- Use
-
Never concatenate raw input into file paths.
3. Use Parameterized Database Queries
- Rule: Never construct SQL queries using string concatenation.
- Always use parameterized queries provided by the database driver.
- ORM usage must not interpolate user input directly into raw SQL.
4. Avoid eval, exec, and compile on Dynamic Input
- Rule: Do not use
eval(),exec(), orcompile()on any user-controllable input. - No exceptions unless marked
# security-reviewed.
5. Use Constant-Time Comparison for Secrets
- Rule: Use
hmac.compare_digest()for comparing secrets such as tokens, passwords, or signatures. - Never use
==for secret comparison.
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.
- 1mo ago First seen · 144 lines · 1,098 tokens per session scan A ed404b0b4c21
security-lang-python is a cursor rule published in the GitHub repository AdobeDocs/ff-services-docs (4 stars, last pushed 3mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,098 tokens. 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.
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