testing-prompt-injection-in-rag-pipelines SKILL.md skillA

testing-prompt-injection-in-rag-pipelines from adriannoes/awesome-agentic-ai is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add adriannoes/awesome-agentic-ai/testing-prompt-injection-in-rag-pipelines@v1.0

Pins v1.0 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
adriannoes/awesome-agentic-ai
Path
cursor-claude-codex/skills/anthropic-cybersecurity-skills/skills/testing-prompt-injection-in-rag-pipelines/SKILL.md
Versions recorded
1
Latest version
v1.0, committed Jun 25, 2026
Size
12,678 bytes
Repository stars
69
License
MIT

Probe RAG applications for prompt injection via poisoned retrieved context and embedding manipulation.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# Testing Prompt Injection in RAG Pipelines

> **Authorized-use-only notice:** This skill describes offensive testing techniques against Retrieval-Augmented Generation (RAG) systems. Run these probes only against applications you own or have explicit written authorization to test. Adversarial inputs that exfiltrate documents or hijack a model can cause real harm to production systems and downstream users. Always test in a non-production environment first and follow your engagement rules of engagement (RoE).

## Overview

Retrieval-Augmented Generation (RAG) pipelines combine a large language model (LLM) with a retrieval layer (a vector store such as FAISS, Chroma, Pinecone, Milvus, or pgvector) so the model can answer questions over private documents. The retrieval layer is an *injection surface*: any text that the retriever returns is concatenated into the model's context window and is treated by the model as authoritative. An attacker who can influence the document corpus (a poisoned PDF, a malicious wiki edit, a planted support ticket, a crafted email) can plant instructions that the model will follow when that chunk is retrieved. This is **indirect prompt injection** delivered
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add adriannoes/awesome-agentic-ai/testing-prompt-injection-in-rag-pipelines@sha256:ab5d167bbb09c182

The line at the top of this page pins the label v1.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_d22bjmeg4gtwtudv.svg)](https://markdownregistry.com/a/art_d22bjmeg4gtwtudv)

2 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on Jun 25, 2026.

versioncommittedcommitsizeaudit
v1.0 latest2026-06-25 f69bd81 12,678 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (12678 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

adriannoes/awesome-agentic-ai · 69 stars · license MIT · pushed 2026-10-10 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_d22bjmeg4gtwtudv
GET https://markdownregistry.com/api/v1/resolve?ref=adriannoes/awesome-agentic-ai/testing-prompt-injection-in-rag-pipelines
GET https://markdownregistry.com/api/v1/blob/ab5d167bbb09c1827c5ef011ce0d78f199f4c166b95796d24b6adb8782248f7b

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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