CCS Review Process

SkillDev tools

Use when explaining or planning around ACM CCS peer review, the two-cycle HotCRP workflow, decision categories including minor revision, the rebuttal window, the adversarial reviewer pool, ethics and disclosure scrutiny, meta-review dynamics, and ACM proceedings outcomes.

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 Review Process 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-review-process/SKILL.md and read by ahel’s review.

Use this to reason about review-stage strategy. Reopen the current CFP, the cycle's HotCRP site, the reviewer guidelines if posted, and the ethics policy before making process claims.

Process model

  • CCS runs two review cycles per year on HotCRP, each with abstract registration, full-paper submission, review, a rebuttal window, and notification.
  • Reviewers assess threat-model soundness, novelty, technical correctness, evidence quality, ethics and responsible disclosure, and significance to the security community.
  • Decisions are not binary: CCS 2026 used accept, minor revision (authors revise for the same cycle under a shepherd or check), and reject. A first-cycle reject cannot return that year.
  • An ethics or disclosure concern can sink an otherwise strong paper; the ethics reviewer's view carries weight independent of technical scores.
  • Accepted papers publish in the ACM Digital Library proceedings, so camera-ready and metadata compliance matter as much as the initial decision.

Who reviews here

  • The pool is adversarial by training: expect at least one reviewer to attack your threat model, look for the assumption that makes the attack easy, and probe whether the defense was tested against an adaptive attacker.
  • CCS is broad, so a paper may draw reviewers from an adjacent sub-area; the threat model and intro must orient a web-security reviewer to a crypto result and vice versa.
  • Borderline papers usually fall on one of three edges: an attacker assumption too strong to be interesting, a defense never adapted against, or an ethics gap left unaddressed.

Scoring leverage table

Review dimensionWhat raises itWhat sinks it
Threat modelA tight, realistic adversary stated up frontCapabilities that quietly grow to make the attack work
NoveltyAn attack class or guarantee the literature lackedAn increment over a cited paper with no new idea
EvidenceEnd-to-end demonstration against a real targetLab-only results against a strawman
EthicsDisclosure done, harm minimized, reasoned in the paperReal-world harm with no disclosure or IRB reasoning

Stage-by-stage realism

  • Initial reviews: triage by what the meta-reviewer will weigh — threat model and evidence — not by reviewer tone.
  • Rebuttal: the window is short and structured; one crisp answer to the decision-critical objection beats an exhaustive point-by-point.
  • Decision: the meta-review synthesizes; one unresolved threat-model or ethics objection outweighs several resolved clarity complaints.
  • Minor revision: treat it as conditional acceptance with a checklist, not a debate; do exactly what the shepherd asks within the cycle's timeline.

Output format

[Current stage] submitted / reviews / rebuttal / decision / revision / camera-ready
[Decision actors] <reviewers / ethics reviewer / meta-reviewer / chairs>
[Likely leverage] <threat model / novelty / evidence / ethics>
[Forbidden moves] <identity leak / new unsupported results / ignoring the shepherd>
[Next response move] <one action>

Signals

GitHub stars
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Last commit
Aug 2026
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skill
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ccs-review-process
Source
github.com/brycewang-stanford/awesome-journal-skills