CCS Reproducibility
SkillDatabases & dataUse 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.
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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 type | What full sharing looks like | Honest fallback when sharing is blocked |
|---|---|---|
| Exploit against deployed software | Runnable PoC plus target build | Redacted PoC, disclosed-and-patched note, synthetic target |
| Defense with overhead numbers | Instrumented build and benchmark scripts | Binaries plus measurement scripts if source is proprietary |
| Internet-scale measurement | Dataset plus collection tooling | Aggregated data with subject-privacy justification for the rest |
| Cryptographic protocol | Reference implementation and test vectors | Spec 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
- 1k
- Forks
- 146
- Last commit
- Aug 2026
Advanced
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ccs-reproducibility- Source
- github.com/brycewang-stanford/awesome-journal-skills