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Crafted at
Skills/Security
telagod avatar

Orchestrating Adversarial Reviews

telagod/code-abyss

When you fan out agents to find security holes or review code at scale, you can't trust a single agent's "all clear" or "fixed it" report. This orchestration pattern runs finder agents in parallel, then puts every finding through a three-way adversarial panel (exploitability, correctness, refutation) that defaults to disbelief and only keeps findings that survive majority vote. For fixes, it gates deployment behind load-bearing proof tests that fail on vulnerable code and pass on patched code, catching agents who falsely claim done. The workflow reference walks through a full security audit with concrete examples of agent lying patterns, exit code traps, and reverse-falsification tests. Overkill for low-stakes work, essential when wrong conclusions have consequences.

GitHub stars
224
last updated
Jun 10, 2026
View on GitHubSave

Install

$ npx -y skills add telagod/code-abyss --skill orchestrating-adversarial-reviews --agent claude-code

Installs into .claude/skills of the current project.

Files

对抗验证编排 · orchestrating-adversarial-reviews

单个 agent 会谎报"已修复 / 全覆盖 / 没问题"。结论的可信度不来自"谁说的",来自"扛过几次推翻"。 本 skill 是编排骨架:fan-out 发现 → 三棱镜对抗验证 → 证明性 guard → 守卫式上线。 信级:运行时行为 / 证明测试 > 多 agent 多数裁决 > 单 agent 自报(永远 [unverified])。

核心信条

  1. 不信单 agent 自报。 finder 会噪音误报,implementer 会谎称"已修复/全覆盖"。每个高价值结论必须被独立 agent 用不同视角尝试推翻。
  2. 可证伪 > 可声称。 修复必须配一个"退回漏洞代码就 FAIL、修好才 PASS"的 load-bearing 证明测试。没有证明测试的"已修复"等于没修。
  3. 失败方向要对。 守卫链里任何一步的退出码都不能被管道遮住;破坏性动作前置可逆检查。

何时使用

场景用理由
授权安全审计 / 加固闭环✅首个范例,见 workflow
大面积代码审查(多维度、需高可信)✅dimensions → find → 对抗验证
研究综合 / 事实核查(结论要扛得住)✅多源 fan-out + 证伪棱镜
大规模迁移 / 重构(site 发现 + 逐项验证)✅pipeline 逐项独立 + 证明测试

何时不使用

  • ❌ 单文件、低风险、机械改动——直接做完跑测试,别套编排(参见 shipping-changes 的"何时不使用")。
  • ❌ 用户没有 opt-in 多-agent 编排 / 没开 ultracode——Workflow 会 fan-out 几十个 agent 烧大量 token,必须显式授权。
  • ❌ 只需要"找什么洞"的知识——那是 securing-systems / analyzing-security,本 skill 不重写知识,只编排。

编排骨架(三相)

Recon (fan-out)     每维一个 finder, 并行深读, schema 出结构化 findings
   |                pipeline 而非 barrier: 维度A的发现可在维度B还在找时就进验证
   v
Verify (三棱镜)     每条 finding 派 N 个 verifier, 各执一镜, 默认怀疑
   |                可利用性 / 正确性 / 证伪猎杀 —— 票数 >= 多数 才保留
   v
Synthesize / Ship   合成定级报告; 若是修复任务 -> 证明测试 guard -> build-first 上线

对应 Workflow 工具的 pipeline(items, findStage, verifyStage)(默认无栅栏,墙钟最短)。仅当"下一阶段需全部上一阶段结果"(去重 / 早退 / 跨条比较)才用 parallel 栅栏。

四大护栏(实战血泪,按重要度)

  1. 三棱镜对抗验证(防 finder 噪音)——每条发现派视角各异的 verifier(可利用性 / 正确性 / 证伪猎杀),默认怀疑,多数票 confirmed 才保留。
  2. 证明性测试 guard / load-bearing(防 implementer 谎报)——修复配真行为测试,且测试本身能"反向证伪"(退回漏洞版必 FAIL)。本 skill 的命门。
  3. build-first + 退出码 guard(防误删 / 半成品上线)——先构建验证新件再动旧件;cmd | tail 会吞掉 cmd 的退出码,判码用 cmd > log 2>&1; rc=$?。
  4. 语境校准降噪——fan-out 前钉死威胁模型 / 评判语境,否则收一堆无效发现。

每条护栏的细节、PoC 判据、反向证伪实操、安全审计 worked example,见 references/workflow.md。

反模式

  • 信单 agent "已修复 / 没问题 / 全覆盖"——必过对抗验证 + 证明测试。
  • up --build 2>&1 | tail && rm <old>——管道吞码,build 失败仍删旧件。
  • N 个同质 verifier 复读同一判断——要视角多样,否则冗余不抗错。
  • 多 agent 同一工作区并行写同批文件——冲突;要么单 implementer,要么 isolation: worktree。
  • 用户未 opt-in 时擅自 fan-out 大舰队——先确认或估算成本。

参见

  • securing-systems —— 攻防知识总路由(找什么洞)。
  • shipping-changes —— 单上下文变更闭环脊柱。
  • cultivating-skills —— 本 skill 的孵化器 / 安全脊柱 / 升级漏斗。
  • Workflow 工具 —— 编排引擎(pipeline / parallel / schema / budget)。
SKILL.md on GitHub

Sponsors

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Details

Repository
github.com/telagod/code-abyss
Categories
Security, DevOps & CI/CD, Git & Pull Requests, Code Review & Quality, AI & Agent Building, Data Science & ML, Productivity & Planning, Automation & Workflows
License
MIT
First seen
Jun 11, 2026

More from telagod/code-abyss

All 30
  • Processing Docx
  • Processing Pdfs
  • Provisioning Infrastructure
  • Reducing Aigc Detection
  • Securing Cloud And Supply Chain
  • Securing Systems
  • Shipping Changes
  • Verifying Modules
  • Analyzing Changes
  • Analyzing Security
  • Analyzing Spreadsheets
  • Applying Ui Design System
  • Architecting Security
  • Automating Devops
  • Building Agent Systems
  • Checking Code Quality
  • Creating Presentations
  • Cultivating Personas
  • Cultivating Skills
  • Defending Applications
  • Designing Architectures
  • Designing Hardware Products
  • Detecting And Responding
  • Developing Mobile Apps

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