LightState Registry / Portable Agent Skill (SKILL.md)s / Security & Infra / skill-prompt-injection-defense
⚡ Pulse Score 93/100
LLM Indirect Prompt Injection & Untrusted Data Fencing Skill
Defend autonomous agents against indirect prompt injection in emails, web pages, and MCP tool outputs using XML data fencing, privilege separation, and hum
⚡ 1-Click Agent & Developer Install
Zero Auth · Ready for Grok Bot, Claude Code & Cursornpx lightstate install skill-prompt-injection-defense
Copy-Paste System Prompt / Routine Blueprint:
Load the LLM Indirect Prompt Injection & Untrusted Data Fencing Skill (skill-prompt-injection-defense) playbook. First inspect our current configuration and codebase for Prompt Security, Untrusted Data Fencing, Tool Governance, Agent Safety. Then propose a concrete, step-by-step implementation plan following the skill-prompt-injection-defense guardrails, run the non-destructive verification commands (npx lightstate inspect inbox-injection-guard), and summarize any findings, risks, or required environment variables before making production changes.
📘 Complete SKILL.md Playbook Specification
--- name: prompt-injection-defense description: Defend autonomous agents against indirect prompt injection in emails, web pages, and MCP tool outputs using XML data fencing, privilege separation, and human approval gates. Use when working with Prompt Security, Untrusted Data Fencing, Tool Governance, Agent Safety. triggers: - prompt injection defense - prompt security - untrusted data fencing --- # LLM Indirect Prompt Injection & Untrusted Data Fencing Skill ## 1. When to Use This Skill Load `skill-prompt-injection-defense` whenever an engineering or operations task involves **Prompt Security, Untrusted Data Fencing, Tool Governance, Agent Safety**. Specifically: - Defend autonomous agents against indirect prompt injection in emails, web pages, and MCP tool outputs using XML data fencing, privilege separation, and human approval gates. - Designing, reviewing, or debugging production configurations without guesswork or deprecated flags. - Running deterministic pre-flight and post-execution verification checks before reporting completion. ## 2. Prerequisites & Required Environment - **Target Stack:** Prompt Security, Untrusted Data Fencing, Tool Governance, Agent Safety - **Permissions:** Read-only inspection by default; ask for explicit confirmation before executing destructive mutations or production deployments. - **Reference Repository:** `https://simonwillison.net/tags/prompt-injection/` ## 3. Step-by-Step Execution Playbook 1. **Context & Configuration Discovery:** Inspect existing project manifests (`package.json`, `wrangler.jsonc`, schema files, or environment declarations) before proposing changes. Never overwrite existing bindings or credentials blindly. 2. **Deterministic Implementation:** Apply the canonical patterns for **Prompt Security**: - Enforce strict schema/type validation at every external boundary. - Include explicit error handling, structured logging, and idempotency keys on all mutating calls. - Keep secrets in environment variables or secret stores—never hardcode tokens in source files. 3. **Verification & Regression Gate:** Run the verification commands below and inspect both exit codes and output payloads before marking the task complete. ## 4. Reference Commands & CLI Workflow ```bash npx lightstate inspect inbox-injection-guard ``` ## 5. Edge Cases & Anti-Hallucination Guardrails - **Zero Unverified Claims:** Never claim a deployment, migration, or API call succeeded without inspecting the command output or HTTP status code. - **Rollback Readiness:** Always record the previous state or migration version so changes can be reverted cleanly if downstream health checks fail.
Synthesized Engineering Blueprint & Setup Guide
### Overview & Capability Scope
**LLM Indirect Prompt Injection & Untrusted Data Fencing Skill** (`skill-prompt-injection-defense`) is a verified, portable `SKILL.md` playbook curated with **@simonw** for Grok Bot (`x.ai/bot/`), Claude Code (`~/.claude/skills/`), and Cursor (`.cursor/skills/`).
Defend autonomous agents against indirect prompt injection in emails, web pages, and MCP tool outputs using XML data fencing, privilege separation, and human approval gates.
### Required Stack & Tooling
- **Primary Stack:** Prompt Security, Untrusted Data Fencing, Tool Governance, Agent Safety
- **Category:** `security-ops`
- **Source & Reference:** [https://simonwillison.net/tags/prompt-injection/](https://simonwillison.net/tags/prompt-injection/)
### Quickstart Installation
Install this `SKILL.md` playbook directly into your agent workspace:
```bash
npx lightstate install skill-prompt-injection-defense
```
Or copy the complete `SKILL.md` specification below into `.cursor/skills/skill-prompt-injection-defense/SKILL.md` or `~/.claude/skills/skill-prompt-injection-defense/SKILL.md`.
### Verification Commands
```bash
npx lightstate inspect inbox-injection-guard
```
Tags: #prompt-security#untrusted-data-fencing#tool-governance#agent-safety#skill-md#security-ops
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