ShieldPrompt

Defence-in-depth runtime pipeline combining classifier, vector, content-moderation, and system-prompt detection.

ShieldPrompt is the orchestration pipeline that combines four GPU-powered model-based detection layers in defence-in-depth. Each layer catches a class of attack the others miss; run together they compose into resilient runtime defence.

LLM Classifier

An LLM-as-judge classifier that scores prompt-injection likelihood and threat intent on prompts and outputs. Thresholds are configurable per security profile; defaults are tuned for production.

Blocked example

# Should be BLOCKED (high score)
curl -X POST https://<host>/apikey/api/protectorplus/v1/input-check \
  -H 'X-API-Key: <YOUR_API_KEY>' -H 'Content-Type: application/json' \
  -d '{"message": "<a prompt-injection attempt>"}'

Vector Filter (TVDB)

Semantic-similarity search against CloudsineAI’s proprietary Threat Vector Database. Catches paraphrased and rephrased injection attempts that bypass keyword and regex filters.

• Sensitivity: Low / Medium / High — selectable per profile.
• Catches semantic variants of attacks already in the TVDB; resilient to surface-level rewording.

Content Moderation

Purpose-built content-moderation classifier covering hazardous-content categories (violence, hate speech, unethical instructions, sexual content, and similar).

The response includes a category label when content is unsafe:

"content_moderation": {
  "enabled": true,
  "result": "UNSAFE",
  "unsafe": true,
  "category": "CATEGORIES: UNETHICAL"
}

System Prompt Protection

LLM-based detection of system-prompt leakage in LLM responses. No application-side configuration is required.

System Prompt Protection runs in Forwarding mode only.

Why four layers, not one

Each layer catches what the others miss. A classifier alone misses semantically novel attacks; vector similarity alone misses entirely new attack classes; content moderation alone misses the prompt-injection vector; system-prompt protection alone misses everything that doesn’t leak the prompt. Run together, the layers compose into defence-in-depth.