attack-vector-generation

$npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/attack-vector-generation

Generates executable attack vectors for specified threat surfaces

  • Solves the problem of identifying actionable attack paths for red teams
  • Relies on threat-surface-mapping and subagent-spawning execution model
  • Analyzes surface, artifact, and prior findings to prioritize novel vectors
  • Returns prioritized vectors with severity, outcomes, and follow-up triggers
SKILL.md
.github/skills/attack-vector-generationView on GitHub ↗
---
name: attack-vector-generation
description: Generate specific attack strategies for a given threat surface, producing concrete probes that can be executed.
execution: subagent
prompt: ./prompt.md
input: surface (string), artifact (string), prior_findings (string)
used-by: [red-teaming]
---

# Attack Vector Generation

Generates concrete, executable attack vectors targeting a specific threat surface.

## Execution

Subagent — spawned via subagent-spawning/spawn-agent.

## Why Subagent

Vector generation requires creative adversarial thinking without defensive contamination. Each surface needs fresh attack ideation.

## Input

- **surface**: The specific threat surface to target (from threat-surface-mapping)
- **artifact**: The artifact being attacked
- **prior_findings**: Results from previous probes (to avoid repetition)

## Output

- **vectors**: List of specific attack vectors with description, expected outcome, and severity estimate
- **priority_order**: Recommended execution order (highest-impact first)
- **follow_up_triggers**: Conditions that should trigger deeper investigation
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