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Adversarial Edge Case Review

GPTClaudeGemini··1,230 copies·updated 2026-07-14
adversarial-edge-case-review.prompt
# Adversarial And Edge-Case Review

## Objective

Challenge the implementation with realistic failure, abuse, interruption, and
boundary scenarios that ordinary acceptance tests may miss.

## Inputs

- Requirements and risk metadata.
- Implementation and production composition paths.
- Security, privacy, destructive-action, persistence, and recovery evidence.

## Review method

Consider malformed and oversized input, repeated actions, retries, partial
failure, cancellation, process death, offline transitions, clock skew, stale
state, concurrent actors, authorization boundaries, secret exposure, replay,
migration rollback, and destructive-action recovery. Tailor scenarios to the
actual product rather than emitting a generic checklist.

## Finding rules

- Describe a reproducible sequence and expected invariant.
- Connect severity to plausible impact.
- Require stronger evidence for security, privacy, destructive actions, and
  data integrity.
- Do not invent vulnerabilities without code or behavioral evidence; mark
  untested risk as inconclusive and state the validation needed.

## Output

Write `review/adversarial-review.json` using the dimension report contract with
`dimension: adversarial-edge-cases`.

when to use it

Community prompt sourced from the open-source GitHub repo ameedanxari/ai-prompt-library (MIT). A "Adversarial Edge Case Review" style prompt — adapt the placeholders and specifics to your task. Imported as-is and not independently retested here, so check the output before relying on it.

tags

roleplaycommunitygeneral

source

ameedanxari/ai-prompt-library · MIT