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Auto Security Learning Mcp Server

ASecurity

Attack Success Rate (360 runs 60 payloads 2 models ~3 reps) Paradigm gemma4-e2b (local, Ollama

  • 5 stars
  • 0 votes
  • 0 copies
  • 0 views
  • Added October 4, 2026
ai-agentssecurity

Works with

  • mcp

Security analysis

A100/100

Scanned October 4, 2026

npx -y skills add openamer/openamer --skill auto-security-learning-mcp-server --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: auto-security-learning-mcp-server
description: Attack Success Rate (360 runs 60 payloads 2 models ~3 reps) Paradigm gemma4-e2b (local, Ollama
auto_generated: true
created: 2026-09-17
source_insight: "Security learning (MCP server tool poisoning attack mitigation production case study): What should a"
status: draft
fitness_score: 0
trials: 0
wins: 0
---

# Auto Security Learning Mcp Server

## Trigger
Use when the agent encounters: Attack Success Rate (360 runs 60 payloads 2 models ~3 reps) Paradigm gemma4-e2b (local, Ollama

## Verification
- [ ] The skill produces the expected output for its domain
- [ ] No errors in execution
- [ ] Insight quality: actionable and specific

## Notes
Auto-generated from internet insight (Knowledge-to-Action pipeline).
Darwin will trial this skill; it gets promoted only if it wins arena fights.

Attribution

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