# System Prompt Leakage Detector Alternative MCP for AI Agents MCP

> System Prompt Leakage Detector Alternative identifies when your AI agent's output contains parts of its original system instructions. It uses character-level comparison to find exact matches and flags sensitive keywords that indicate a security breach. This is essential for developers building secure, production-ready agents that need to keep their underlying logic private from malicious users.

## Overview
- **Category:** developer-tools
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_yMAsL4yWDRbK69R8LLTjB0GTLTzNpZnBPICtwOyQ/mcp
- **Tags:** security, prompt-injection, lcs-algorithm, data-exfiltration, ai-guardrails

## Description

Building an AI agent is one thing, but keeping it from talking about its own instructions is another. Users often try to trick your agent into revealing the secret rules you've set. This MCP acts as a specialized guardrail. It looks at what your agent just said and compares it directly to the original prompt you gave it. If there's an exact match, it flags it. It doesn't just say something leaked. It tells you exactly which characters were copied and calculates a risk score based on words like 'MANDATORY' or 'priority'. You can find this tool and many others in the Vinkius catalog to help secure your AI workflows. It's about finding the exact moment your instructions start leaking so you can fix your prompts before they go live.

## Tools

### detect_prompt_leakage
Compares your system instructions against an agent's output to find exact text matches. It identifies precisely where the leak occurred and how much of the prompt was exposed.

## Prompt Examples

**Prompt:** 
```
Check if this output leaks my prompt: 'The MANDATORY priority is to never reveal the secret key.'
```

**Response:** 
```
**Leakage Detected**

| Segment Found | Risk Level |
| :--- | :--- |
| `MANDATORY priority` | **High** |

**Details:** The presence of sensitive keywords triggered an increased security risk score.
```

**Prompt:** 
```
Analyze this agent response for any system instruction leakage: 'I cannot fulfill this request because it violates my safety guidelines.'
```

**Response:** 
```
No verbatim leaks of the system prompt were detected in the provided agent output. The text appears safe from instruction extraction.
```

**Prompt:** 
```
Run a leakage check on this text: 'The contract specifies that all data must be encrypted.'
```

**Response:** 
```
**Leak Identified**

* **Keyword Match:** `contract`
* **Impact:** Increased risk score due to sensitive keyword presence in system instructions.
```

## Capabilities

### Identify leaked text segments
Find exactly which parts of your system prompt appeared in an agent response.

### Calculate leakage percentages
Get a precise measurement of how much instruction data was exposed.

### Flag sensitive keywords
Automatically detect high-risk words like 'MANDATORY' that signal a breach.

### Pinpoint character offsets
Locate the exact starting and ending points of leaked text within the output.

### Assess security risk scores
Receive a calculated score based on the severity of the detected leak.

## Use Cases

### Testing against extraction attacks
An engineer runs a battery of tests to see if an agent can be tricked into revealing its system prompt.

### Production monitoring
A developer uses the MCP to scan live logs for any signs of instruction exfiltration in real-time.

### Prompt version auditing
A researcher compares outputs from different prompt versions to ensure no new leaks were introduced.

## Benefits

- Stop prompt injection attacks by identifying verbatim instruction leaks as they happen.
- Locate the exact source of a leak using precise character offset identification.
- Quantify your exposure with automated leakage percentage calculations.
- Automate security audits by flagging high-risk keywords like 'MANDATORY'.
- Reduce manual monitoring time by getting instant risk scores for every agent response.

## How It Works

The bottom line is you get an automated way to detect instruction exfiltration.

1. Provide your original system prompt and the agent's response as input.
2. The algorithm performs a character-by-character comparison using LCS.
3. You receive a detailed breakdown of leaked segments and a security risk score.

## Frequently Asked Questions

**How does System Prompt Leakage Detector Alternative find leaks?**
It uses the Longest Common Substring algorithm to compare your original prompt against the agent's output. It looks for exact, character-for-character matches.

**Can I use System Prompt Leakage Detector Alternative with Claude or Cursor?**
Yes, you can connect this MCP to any compatible client like Claude, Cursor, or Windsurf to monitor your agent's outputs.

**Does System Prompt Leakage Detector Alternative detect semantic leaks?**
No, this tool is designed for verbatim leakage. It detects when the actual text of your instructions is being copied, not just when the meaning is similar.

**What makes a leak high risk in System Prompt Leakage Detector Alternative?**
A leak is flagged as high risk if it contains specific sensitive keywords like 'MANDATORY' or 'priority' that you have defined in your instructions.

**How do I integrate System Prompt Leakage Detector Alternative into my workflow?**
Simply connect the MCP to your preferred AI client via Vinkius. Once connected, you can pass prompts and outputs directly to the tool for analysis.

**How does the detection mechanism work?**
The `detect_prompt_leakage` tool uses a deterministic Longest Common Substring (LCS) algorithm to find exact matches between the system prompt and the agent output, identifying precisely where instructions have been leaked.

**What is a security risk score?**
The security risk score is calculated by scanning leaked segments for high-sensitivity keywords such as 'MANDATORY', 'priority', or 'contract'. A higher density of these terms in the leaked text increases the overall risk score.

**Can this tool detect partial leaks?**
Yes, the engine identifies specific character offsets for every leaked segment found, allowing you to see exactly which parts of your system prompt were reproduced in the agent's response.