唯稳律是一套因果律运行结构的白箱呈现工具，封装为通用型 AI 安全中间件 DSH。它基于完整因果链，在模型执行风险动作前做反溯审计、前向推演预测与风险拦截——不仅是事后可审计，更能向前推演并拦住"会作死"的那一步。作为通用型因果引擎，它不绑定任何模型或技术栈。Weiwen's Law is a white-box presentation of how causal law operates, packaged as a universal AI-safety middleware called DSH. Built on a complete causal chain, it performs retrospective audit, forward inference prediction, and risk interception before the model executes a risky action — not only auditable after the fact, but able to reason forward and stop the "self-destructive" step. As a universal causal engine, it is tied to no model or tech stack.
开放授权 · 分层适配 · 领域无关Open licensing · Tiered · Domain-agnostic同一句危险指令，模型有时拒绝、有时照做。越是自主的 agent，越可能在某个上下文里"顺手"执行删库、外传凭据、远程执行、绕过限制。The same dangerous instruction — a model sometimes refuses, sometimes obeys. The more autonomous the agent, the more likely it is to "casually" wipe a database, exfiltrate credentials, run remote code, or bypass limits in some context.
约束不能看模型心情。唯稳律把"拒不拒"从模型主观判断锚定到可复验的规则层——稳定、可审计、可推演、不依赖模型自觉。Constraint shouldn't depend on the model's mood. Weiwen's Law anchors "allow or deny" from the model's subjective judgment to a verifiable rule layer — stable, auditable, inferable, independent of the model's self-awareness.
实测：Measured: 高峰压力下 12 场对抗，9 场由引擎独立拦下，不依赖模型自觉。under peak load, 9 of 12 adversarial scenarios were intercepted by the engine alone, independent of the model's self-restraint.
下面不是截图，是真实开源引擎在你的浏览器里跑：把命令/代码贴进来，唯稳律按完整因果链 R→S→D→H→M 实时裁决，点亮它在哪一步、以什么理由拦下或放行。确定性的白箱规则层，零服务器、零成本；不接实时 API、不含闭源引擎。This is not a screenshot — it is the real open-source engine running in your browser: paste a command or code, and Weiwen's Law adjudicates live along the full causal chain R→S→D→H→M, lighting up where and why it stops or passes. The deterministic white-box rule layer — zero server, zero cost; no live API, no closed-source engine.
基于完整因果链，引擎同时具备反溯审计、前向推演预测与风险拦截；不替代模型内容生成，内部变量（想法/决策）不在白箱内被导出。Built on a complete causal chain, the engine performs retrospective audit, forward inference prediction, and risk interception; it does not replace model content generation, and inner variables (thoughts/decisions) are not exported from the white box.
你给 AI 下指令，它照做之前，有没有一道闸拦住危险动作？唯稳律就是这道闸。它不替 AI 思考，只在 AI 准备执行风险动作时，按因果链判断是否放行。现在它开放授权，你可以把它接进自己的 AI 系统，按需要选免费社区版或商业版。You give AI an instruction. Before it acts, is there a gate that stops dangerous actions? Weiwen's Law is that gate. It doesn't think for the AI — it only judges, by the causal chain, whether to allow the action when the AI is about to execute a risky one. Now open for licensing: integrate it into your own AI system, choose free community or commercial as needed.
把"拒不拒"从模型主观判断锚定到可复验的规则层；基于完整因果链，引擎既能反溯审计、又能向前推演预测后果并据此拦截风险；不替代模型生成，外部变量基于可观测事实，内部变量不在白箱内导出。36 场诱导/对抗场景实测，高峰与低谷均稳定，多场为模型照做时被引擎独立拦下。Anchor "allow or deny" from the model's subjective judgment to a verifiable rule layer; built on a complete causal chain, the engine both audits retrospectively and reasons forward to predict consequences and intercept risk accordingly; it does not replace model generation, outer variables rest on observable facts, inner variables are not exported from the white box. 36 induced/adversarial scenarios tested, stable at both peak and off-peak, multiple runs intercepted by the engine alone while the model obeyed.
想读代码、想自己跑开源部分，直接进仓库；想接生产，走授权。开源部分（核心 SDK + 审计引擎）可免费集成验证。Want to read the code or run the open-source part yourself? Go straight to the repo. Want production? Take a license. The open-source part (core SDK + audit engine) integrates and validates for free.
核心 SDK 与审计引擎已开源，含双语文档。Core SDK and audit engine are open source, with bilingual docs.
中文仓库 · weiwen-law-dsh English · KISS_Law-DSH闭源部分（量化引擎、领域配置）不在公开仓库，须通过授权获取。Closed-source parts (quantitative engine, domain config) are not in the public repo; available via licensing.
规则部分固化后可吃缓存，单轮实测新增成本约 ¥0.01 / 12 场（含高峰）。安全不靠堆算力。After the rule part is fixed it can hit cache; measured incremental cost ≈ ¥0.01 / 12 runs (including peak). Safety doesn't rely on brute-forcing compute.
数据为公开实测摘要，不含闭源引擎实现细节。Data is a public test summary; excludes closed-source engine implementation details.
闭源部分（量化引擎、领域配置）不在公开门面披露，须通过授权获取。Closed-source parts (quantitative engine, domain config) are not disclosed on the public front; available via licensing.
面向 AI lab、agent 基础设施厂商、受监管行业 AI 落地团队。
来信说明场景，我们回授权范围与对接方式。For AI labs, agent-infrastructure vendors, regulated-industry AI deployment teams.
Tell us your scenario; we reply with license scope and integration path.