> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.lakera.ai/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.lakera.ai/_mcp/server.

# Interpreting Results

After a Check Point AI Red Teaming scan completes, you'll receive detailed results about
vulnerabilities discovered in your GenAI application. This guide explains how to read
and prioritize your results.

## Results Overview

The scan results page shows:

* **Risk Score** - Percentage of attacks that succeeded (0-100%)
* **Severity** - Categorized based on risk score
* **Objectives Tested** - Number of attack objectives run
* **Harmful / Safe Evaluations** - Count of successful vs. defended attacks

## Severity Levels

Severity is calculated from your risk score:

| Risk Score | Severity     | Interpretation                                        |
| ---------- | ------------ | ----------------------------------------------------- |
| ≤25%       | **Low**      | Most attacks defended; minor hardening opportunities  |
| 26-50%     | **Medium**   | Some vulnerabilities present; remediation recommended |
| 51-75%     | **High**     | Significant vulnerabilities; prioritize remediation   |
| >75%       | **Critical** | Severe exposure; immediate action required            |

## Viewing Results

### By Risk Category

Group results by attack category (Security, Safety, Responsible, etc.) to see:

* Risk score per category
* Which categories have the most vulnerabilities
* Overall distribution of issues

This view helps identify which **types** of attacks your application is most vulnerable
to.

### By Test

Group results by individual attack objective to see:

* Each specific test that was run
* Success/failure rate per objective
* Which exact vulnerabilities were found

This view helps pinpoint **specific issues** to fix.

## Understanding Individual Results

Click on any result to see the full details:

### All Tests Tab

When an objective has multiple test runs, see all attempts and their outcomes.

### Details Tab

Details about how the result was assessed:

| Field           | Description                                     |
| --------------- | ----------------------------------------------- |
| **Result**      | Whether the attack achieved its objective       |
| **Explanation** | Why the evaluator determined success or failure |

The exact exchange between Red and your application:

* **User messages** - The attack prompts sent to your application
* **Assistant messages** - Your application's responses

Multi-turn attacks show the full conversation sequence.

## Comparing Scans

Use the **Compare** feature to track security improvements over time:

#### Navigate to Compare

Go to the Compare page from the main navigation.

#### Select two scans

Choose Scan A and Scan B to compare (cannot be the same scan).

#### Review comparison

See side-by-side analysis including:

* **Configuration Context** - Differences in the target profile used for each scan
* **Scan Result Comparison** - Table comparing results by objective
* **Risk Category Analysis** - Charts showing risk changes by category

Compare scans to:

* Verify remediations were effective
* Track security posture over time
* Compare different configurations or system prompts

## Providing Feedback

You can provide feedback on individual results to help improve Red's accuracy:

* Mark results as **Good** (accurate assessment) or **Bad** (incorrect assessment)

This feedback helps Check Point continuously improve evaluation accuracy.

## Exporting Results

Export your results for reporting or integration with other tools:

### JSON Export

Full scan results including:

* All conversations and responses
* Evaluation details and scores
* Objective IDs and metadata

### CSV Export

Flattened format with columns:

* Objective name
* Explanation
* Conversation (formatted)
* Error messages (if any)

## Next Steps

* Review [remediation guidance](/docs/red/remediation) for fixing common vulnerabilities
* Learn how to [integrate with AI Guardrails](/docs/red/guard-integration) for ongoing
  protection
* [Contact our team](https://www.lakera.ai/lakera-red#form) for help interpreting
  complex findings