CCS Reproducibility

SkillDatabases & data

Use when strengthening ACM CCS reproducibility evidence, including the artifact-availability posture, threat-model-to-evidence mapping, attack reproduction steps, defense overhead measurement, measurement-dataset provenance, environment and version pinning, and honest justification when artifacts cannot be shared.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the CCS Reproducibility skill

What this skill tells your AI

The instructions your AI receives, as published by brycewang-stanford/awesome-journal-skills in ACM-CCS-Skills/skills/ccs-reproducibility/SKILL.md and read by ahel’s review.

Use this before submission and again before the artifact-evaluation deadline. Reopen the current CFP and call for artifacts to confirm what availability statement and packaging CCS expects this cycle.

Evidence map

  • Map each security claim — every attack, defense guarantee, and measurement result — to a verifiable location: a script, a config, a dataset, a proof, or a logged run.
  • For attacks, record the target's exact version and configuration, the attacker's resource budget, and the sequence of steps that reproduce the exploit.
  • For defenses, record the workload, the overhead-measurement method, the hardware, and the adaptive attacker used, so the cost-versus-security tradeoff can be rechecked.
  • For measurements, document the vantage point, the collection window, the sampling frame, known blind spots, and the ground-truth validation.
  • When artifacts cannot be shared — licensing, responsible disclosure, subject safety, or premature-release risk — say so explicitly and offer partial, synthetic, or redacted artifacts that still let a reader assess the methodology.

Availability-posture table

Claim typeWhat full sharing looks likeHonest fallback when sharing is blocked
Exploit against deployed softwareRunnable PoC plus target buildRedacted PoC, disclosed-and-patched note, synthetic target
Defense with overhead numbersInstrumented build and benchmark scriptsBinaries plus measurement scripts if source is proprietary
Internet-scale measurementDataset plus collection toolingAggregated data with subject-privacy justification for the rest
Cryptographic protocolReference implementation and test vectorsSpec plus test vectors if the implementation is embargoed

Claiming an artifact is unavailable without a reason CCS accepts (a license, a disclosure embargo, subject safety) reads as evasion; state the specific reason and offer the closest shareable substitute.

Vignette: a measurement paper on vulnerable hosts

Consider a study scanning the Internet for a misconfiguration. Its reproducibility spine: the scan methodology and rate-limiting, the classification rule for "vulnerable," the ground-truth sample validated by hand, the ethics of scanning and notification, and an aggregated dataset that preserves the finding without exposing individual vulnerable hosts to opportunistic attackers.

Degrees of reproducibility

  • Turnkey: one command reproduces the attack or the overhead measurement from pinned configs.
  • Scripted: scripts exist but need documented manual steps or gated data access.
  • Descriptive: prose detailed enough that a competent security researcher could rebuild it.

For CCS, aim turnkey for anything you submit to artifact evaluation, and state the achieved level honestly rather than overpromising a one-command reproduction that fails on a clean host.

Output format

[Claim inventory] <claim -> evidence location>
[Availability posture] full / partial / justified-withheld
[Reproducibility gaps] <versions / configs / budgets / provenance / ethics>
[Paper fixes] <must appear in main PDF or appendix>
[Artifact fixes] <packaging additions before the AE deadline>

Signals

GitHub stars
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Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
ccs-reproducibility
Source
github.com/brycewang-stanford/awesome-journal-skills