Workflow Painpoint Eval V1
Mend.io AI-native AppSec Platform Workflow Painpoint Eval · Mend.io
Buyer-facing workflow eval covering AI remediation quality, AI component inventory gaps, system prompt hardening impact, transitive dependency complexity, and cross-scan correlation pain points.
Sample tests· showing 3 of 25
| # | Input | Expected behavior | Check |
|---|---|---|---|
| 01 | ai remediation suggestion quality Developer using Mend SAST receives an AI-powered remediation suggestion for a SQL injection vulnerability. The suggested fix looks plausible but uses a deprecated API that could introduce security regression. | should_escalate: true · resolution_label: security · risk_level: high | Pass / Fail |
| 02 | ai remediation suggestion quality Security engineer reviewing Mend SAST findings notices that the AI remediation suggestion for an XSS vulnerability is incomplete—it sanitizes output but doesn't address the input validation root cause. | should_escalate: false · resolution_label: configure · risk_level: medium | Pass / Fail |
| 03 | ai component inventory gap Security engineer using Mend AI discovers that a custom fine-tuned LLM model deployed via ONNX Runtime is not appearing in the AI Technologies Inventory despite being imported through a dependency. | should_escalate: true · resolution_label: escalate · risk_level: high | Pass / Fail |
How this eval is graded
Evaluate whether the response addresses the workflow pain point correctly, validates AI-generated suggestions before applying, maintains complete visibility into AI and dependency supply chains, and follows application security best practices.
Pass threshold: a criterion passes at a judge score of 4 or higher.
Rubric criteria
- AI Remediation Quality
- AI Component Inventory Coverage
- System Prompt Hardening Balance
- Dependency Management Complexity
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