goal_passthrough

The unattacked direct-prompt baseline optimizer for superred.

GoalPassthroughOptimizer performs no attack. On each run it injects the adversarial Goal.description verbatim, exactly once, into the first user-facing controllable, then ends the run. It is the zero-attack reference point in an attacker sweep: it answers "what does the target do when simply asked the harmful question, with no jailbreak?"

Behaviour

Event Response
RunStartEvent acknowledge; arm the single injection for this run
first ControllablePreCallEvent (non-system_prompt) ControllableInjection(value=goal.description)
subsequent ControllablePreCallEvent ControllableNoInjection (single-turn)
ControllablePostCallEvent ControllableNoInjection (never edits responses)
RunEndEvent RunEndResponse(done=True) (one attempt per task)

The system_prompt controllable is always declined, so a benchmark Task that pre-sets the system prompt via configure_target keeps it intact. The baseline only fills the user-message channel.

Properties

  • No LLM use. It never calls the LLMClient, so it spends none of the per-task budget and is invariant to the attacker-model dimension.
  • Scope-robust. It locks onto the first non-system_prompt controllable it sees, so it works against any chatbot-style target regardless of how the user-message controllable is named.
  • Zero config. Constructs with no arguments, like every superred optimizer.

Install

pip install -e optimizers/goal_passthrough

from goal_passthrough_optimizer import GoalPassthroughOptimizer

Credits / upstream

This module is original work of the superred project, released under the MIT License (see LICENSE). It contains no third-party code, no bundled datasets, and does not reimplement or port any external paper method. Its only dependency is the superred framework itself.

Project links

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Credits

Author: Simon Sure

GitHub Statistics

Data verified by PyPI on Jul 22, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

MIT
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Requires

Python <3.14, >=3.11

Provides Extra

test

Tags

ai-safety baseline llm optimizer red-teaming security superred

Classifiers

Report project as malware

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