L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Développement · SKILL.md

security-contest

security-contest

Explain Nesa Hack EE contest rules, token-mapping submission format, scoring, and baseline attack ideas safely.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: security-contest description: "Explain Nesa Hack EE contest rules, token-mapping submission format, scoring, and baseline attack ideas safely." metadata: disco-role: operating disable-model-invocation: true license: NO_LICENSE

Hack EE Security Contest

Use this sub-skill when the user asks about the Nesa Hack EE contest, encrypted token ID mappings, submission JSON, scoring, daily/grand-prize rules, or the baseline attacks described in the public attack paper.

Typical triggers:

  • "format my Hack EE submission"
  • "what does {"tokens": ...} need to look like?"
  • "how is the contest scored?"
  • "summarize baseline attacks against EE"
  • "plan a safe token-mapping analysis"

Ground rules

  • The public contest objective is to map encrypted/private token IDs back to original text tokens.
  • This skill can explain rules and safe local analysis; it does not provide a guaranteed decryption method.
  • Do not submit to the live contest portal or tweet on the user's behalf.
  • Do not claim success without a user-provided gold/evaluation signal.

Submission format

Contest mappings are JSON objects shaped like:

{"tokens":{"12":"an","345":"swer","678":" he"}}

Use scripts/validate_submission.py to check local JSON shape and optionally score against a user-provided gold fixture.

Attack-baseline workflow

  1. Read references/contest-format.md for rules, scoring, and submission caveats.
  2. Read references/attack-baselines.md for the optimization framing and baseline heuristic families.
  3. If the user provides encrypted prompt/response pairs, keep the analysis local and record assumptions about vocabulary, hints, frequency counts, and model family.
  4. If the user provides a gold mapping for a toy case, validate or score local guesses with the bundled script.
  5. Be explicit about uncertainty and contest timing rules.

References and scripts

Boundaries

  • For local encrypted model demos, route to encrypted-distilbert.
  • For backend tokenization/request flow, route to backend-protocol.
  • For web UI runtime, route to web-ui-runtime.
  • Do not automate credentialed submissions, leaderboard scraping, or social media bonus actions without an explicit user request and safe boundaries.
Skills enregistrées