Prompt Injection

March 6, 2026 · View on GitHub

🧭 Quick Return to Map

You are in a sub-page of Safety_PromptIntegrity.
To reorient, go back here:

Think of this page as a desk within a ward.
If you need the full triage and all prescriptions, return to the Emergency Room lobby.

A focused guide to handle prompt injection attacks in RAG, agents, and orchestration.
Use this page when injected text hijacks your instructions, bypasses schema, or makes the model ignore contracts.


When to open this page

  • Responses contain leaked system prompt or hidden instructions.
  • Model obeys malicious user text like “ignore above and do X”.
  • Citations vanish after injection payload.
  • JSON / tool schema is broken by arbitrary free text.
  • Memory or context keys rewritten by injected content.

Open these first


Core acceptance

  • ΔS(question, retrieved) ≤ 0.45 even with injection attempts.
  • λ remains convergent across 3 paraphrases, does not flip under “ignore above” payloads.
  • Schema lock: JSON/tool calls validate against fixed schema.
  • Coverage ≥ 0.70 of target section even under noisy injection.

Fix in 60 seconds

  1. Detect abnormal ΔS drift

    • Compute ΔS(question, retrieved). If injected phrase raises ΔS ≥ 0.60, isolate payload.
  2. Enforce contracts

    • Wrap retriever and reasoner outputs in data-contracts.md.
    • Reject free text outside schema.
  3. Apply fences

  4. Verify stability

    • Re-run with paraphrase probes. Injection should not flip λ or erase citations.

Typical injection payloads → exact fix

Payload typeSymptomFix
Ignore-all overrideModel discards earlier rulesrole_confusion.md + schema locks
Citation erasureNo references, only free text answerretrieval-traceability.md, data-contracts.md
Tool hijackJSON field replaced with instruction textjson_mode_and_tool_calls.md
Role swapUser prompt injected as “system”role_confusion.md
Memory overwritePast state or keys corruptedmemory_fences_and_state_keys.md

Copy-paste probe prompt

System: WFGY firewall active.
User input: {question}

Check:
1. Did retrieved snippet keep citations?
2. Did ΔS(question,retrieved) ≤ 0.45?
3. Did λ stay convergent under paraphrase?
4. Did JSON/tool call respect schema?

If any fail, return the failing layer + fix page.

🔗 Quick-Start Downloads (60 sec)

ToolLink3-Step Setup
WFGY 1.0 PDFEngine Paper1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + <your question>”
TXT OS (plain-text OS)TXTOS.txt1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly

Explore More

LayerPageWhat it’s for
⭐ ProofWFGY Recognition MapExternal citations, integrations, and ecosystem proof
⚙️ EngineWFGY 1.0Original PDF tension engine and early logic sketch (legacy reference)
⚙️ EngineWFGY 2.0Production tension kernel for RAG and agent systems
⚙️ EngineWFGY 3.0TXT based Singularity tension engine (131 S class set)
🗺️ MapProblem Map 1.0Flagship 16 problem RAG failure taxonomy and fix map
🗺️ MapProblem Map 2.0Global Debug Card for RAG and agent pipeline diagnosis
🗺️ MapProblem Map 3.0Global AI troubleshooting atlas and failure pattern map
🧰 AppTXT OS.txt semantic OS with fast bootstrap
🧰 AppBlah Blah BlahAbstract and paradox Q&A built on TXT OS
🧰 AppBlur Blur BlurText to image generation with semantic control
🏡 OnboardingStarter VillageGuided entry point for new users

If this repository helped, starring it improves discovery so more builders can find the docs and tools.
GitHub Repo stars