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Adversarial Testing and Policy Refinement

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: Building Adversarial Deepfake Detection

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Linked challenge
Building Adversarial Deepfake Detection

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Original prompt text with formatting preserved for inspection.

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Conduct iterative testing using a diverse dataset of real images, generated deepfakes, and carefully crafted adversarial prompts. Use the 'Red Team Agent' to systematically attempt to bypass your moderation system. Based on the 'Moderation Agent's' failure cases, refine your agent's prompts, update moderation policies (via RAG), and enhance the multimodal analysis logic. Document the evolution of your system's robustness.

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Preserve the rubric, target behavior, and pass-fail criteria as the baseline for evaluation.

Tune next

Adjust fixtures, mocks, and thresholds to the system under test instead of weakening the assertions.

Verify after

Make sure the prompt catches regressions instead of just mirroring the happy-path examples.