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Agent Prompt-Injection Defense Harness

Harden your coding or automation agent against prompt injection from repo content, issues, code comments, and tool output. Four structured prompts map the attack surface, design input isolation, write enforceable guardrail rules, and generate a red-team test set so you can verify the defenses actually hold.

A 4-step agentic workflow pack for coding built to run with ChatGPT, Claude, and Claude Code. Open the Markdown files, fill the variables, and paste into your model. Most buyers get a reviewable result in about 15 minutes.

  • Identify every entry point where untrusted text reaches your agent — issues, comments, file content, tool output, and more
  • Design a layered input isolation architecture that separates instructions from untrusted data at every boundary
  • Write production-ready guardrail rules your agent can follow to resist injection attempts in real workflows
  • Generate a targeted red-team test set with adversarial injection payloads to verify your defenses hold under pressure
  • Works for any agent architecture — coding agents, automation pipelines, RAG systems, and tool-calling LLM workflows
  • Works in any chat model — no special tools or integrations required
CChatGPTClaudeClaudeClaude CodeClaude Code
promptscart.com / prompt-packs / prompt-injection-defense-harness-playbook
Run in
ChatGPT · Claude +1
Your AI model
Step 1
Threat Surface Map
Describe how your agent ingests content and which tools it can call — the prompt produces a structured threat surface map showing every untrusted input path, data flow, and injection risk.
Step 2
Input Isolation Design
Feed in your threat surface map — the prompt designs a concrete isolation architecture with instruction-only contexts, data-only contexts, and sanitization steps at each boundary.
Step 3 · optional
Defense Rules
Provide your isolation design and threat surface — the prompt writes a prioritized set of guardrail rules covering detection patterns, refusal behaviors, and escalation actions.
Step 4 · optional
Red-Team Test Set
Supply your agent setup, isolation design, and defense rules — the prompt generates a structured test set of adversarial payloads organized by attack vector and expected agent behavior.
Output
Your deliverable
Copy-paste ready
One-time
$10
~6 hrs / week
time back

Prompt Customization Serviceoptional help adapting variables and output to your brand voice. Choose your tier at checkout (not tied to this prompt's price).

Instant download after payment
Refund as per the Refund Policy.
Email Support · 24h SLA
Lifetime updates

Models supported
C ChatGPTClaude ClaudeClaude Code Claude Code
Best valueSave $786
Get this pack + 101 more in the Lifetime Bundle

This pack is $10 on its own. Buying every pack separately costs $935. The Lifetime Bundle is $149 one-time — you save $786 (84% off) and unlock every future pack free.

Get the Lifetime Bundle — $149
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Download Agent Prompt-Injection Defense Harness

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What ships with your purchase

Prompt files

Plain Markdown files with `{{variables}}` you fill in, ready to paste into ChatGPT, Claude, or Gemini. No setup, no tooling required.

Usage guide

Variable reference, model compatibility, examples, and customization tips so you can adapt the pack to your brand voice.

Lifetime updates

When we improve the pack, you get the new version automatically. Email support included with every purchase.

Models tested: ChatGPT, Claude, Claude Code.

The workflow inside this pack

4 composable prompts you run in order — each one picks up where the last left off.

  1. Step 1

    Threat Surface Map

    Describe how your agent ingests content and which tools it can call — the prompt produces a structured threat surface map showing every untrusted input path, data flow, and injection risk.

  2. Step 2

    Input Isolation Design

    Feed in your threat surface map — the prompt designs a concrete isolation architecture with instruction-only contexts, data-only contexts, and sanitization steps at each boundary.

  3. Step 3 · optional

    Defense Rules

    Provide your isolation design and threat surface — the prompt writes a prioritized set of guardrail rules covering detection patterns, refusal behaviors, and escalation actions.

  4. Step 4 · optional

    Red-Team Test Set

    Supply your agent setup, isolation design, and defense rules — the prompt generates a structured test set of adversarial payloads organized by attack vector and expected agent behavior.

Perpetual (lifetime) use license

Your one-time purchase includes an ongoing right to use this prompt pack with the AI tools and models you control for your own and your clients' work — not for resale or public redistribution of the files as a product.

We keep the copyright

The prompt files, guides, examples, and bundled assets stay our copyrighted works (or our licensors'). Payment grants the limited license in our Terms only — it does not transfer ownership.

Need help adapting this prompt to your team? Add Prompt Customization Service at checkout.

FAQ

How long does it take to use Agent Prompt-Injection Defense Harness?
Most buyers finish in a few minutes: open the prompt file, fill the variables, and paste into your model. The first run is the slowest because you decide variable values; reuse is instant.
What if I get stuck?
Email support@promptscart.com. Free basic support is included with every purchase, and you'll get a reply from our team within 24 hours. If you need help adapting variables or output, we can schedule a call.
Do I need a paid plan with ChatGPT?
The prompt works on free tiers of ChatGPT, Claude, and Gemini. Heavy use can hit free-tier limits; paid plans get longer context and faster responses, but the prompt itself is the value.
Can I customize the prompt?
Yes, completely. You own the prompt files: edit the role framing, add variables, swap output sections, fork it to match your brand voice. Support can help you plan customizations over email.
What if it doesn't work for me?
Refund as per our Refund Policy (https://promptscart.com/refund-policy). Or add Prompt Customization Service at checkout for help adapting variables and output to your workflow.