Compute held-out benign-versus-adversarial obedience deltas and mechanism checks for safe jailbreak proxies.
Scanned 9/9/2026
Install to Claude Code
npx -y skills add VectorSpaceLab/AREX-Skill --skill jailbreak_proxy_evaluator --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: jailbreak_proxy_evaluator
description: Compute held-out benign-versus-adversarial obedience deltas and mechanism checks for safe jailbreak proxies.
---
# Jailbreak Proxy Evaluator
Use this skill to evaluate whether an optimized visual prompt changes held-out behavior in a safe proxy experiment. It mirrors the paper's comparison between benign image and adversarial image conditions without generating or scoring harmful text.
## Inputs
- `target`: metadata from `module_plan.json.fast_recovery_target`.
- `protocol`: output from the safe corpus protocol skill.
- `benign_scores`: prompt IDs mapped to numeric baseline scores.
- `adversarial_scores`: prompt IDs mapped to numeric optimized-prompt scores.
- Optional optimizer diagnostics such as loss decrease and prompt change.
## Outputs
- `metrics.obedience_delta`: mean adversarial score minus mean benign score.
- `category_metrics`: optional per-category means and deltas.
- `mechanism_checks`: booleans for held-out split validity, prompt change, loss decrease, target match, and threshold success.
## Workflow
1. Confirm the target metric is `obedience_delta` for the proxy recovery.
2. Align score dictionaries by held-out prompt ID.
3. Compute mean benign score, mean adversarial score, and their delta.
4. Aggregate category deltas using protocol categories.
5. Combine score evidence with optimizer diagnostics to decide whether the proxy threshold is met.
## Validation
Run:
```bash
python scripts/proxy_evaluator.py --self-test
```
The tests cover metric calculation, category aggregation, and missing-score rejection.
## Limitations
This evaluator cannot establish real-world jailbreak harm. It validates a mechanism-faithful, harmless proxy under soft-mode constraints.
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