Diffgate

io.github.srbsa由 GitHub 帳號 srbsa 發布v0.8.0更新於 Oct 24, 2026

Deterministic guardrail your coding agent runs on itself: diff-scoped findings, zero LLM tokens.

已驗證STDIO僅桌面開發者工具安全與監控

概覽

AI 產生的概覽

一個確定性、依差異範圍審查的程式碼護欄,編碼代理透過 MCP 呼叫它,在程式碼寫入磁碟前檢查自己的變更。

可以做什麼
審查待提交或已暫存的變更,只對變更行回傳結構化發現,依綠、黃、橙分級,且不消耗 LLM token。稽核最近的提交(包括 AI 撰寫的提交),每條發現歸屬於特定提交。不需 git 即可直接掃描檔案,或監看工作區進行即時審查。對高影響變更有選擇地執行設定的測試指令,並回報真實結束碼與輸出。記錄對規則的忽略或確認回饋,藉此抑制重複的誤報。
適用情境
適用於編碼代理修改既有程式碼、希望在代理迴圈內快速取得可重現自檢,而不是等待 PR 審查機器人或提交前鉤子的情境。也適合希望本機、編輯器與 CI 得到相同結論的團隊。
執行需求
以本機 stdio 程序執行,從 npm 套件 diffgate-review 安裝,透過 npx 或全域安裝啟動。依差異的檢查需要 git 儲存庫;受閘控的變更需在 .diffgate.json 中設定測試指令。未宣告任何帳號、API 金鑰或環境變數。
安裝前請注意
閘控會在高影響變更時執行你設定的測試指令,該指令會執行儲存庫中的程式碼。它會將設定與學習記錄檔寫入儲存庫,安裝提交前鉤子會修改 git 鉤子。涵蓋範圍因語言而異,乾淨的結果只表示在該層級沒有符合項目,並不代表程式碼已被證明安全。選用的 AI 說明與程式碼圖附加功能預設關閉。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Diffgate,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

DiffGate

[npm version] [npm downloads] [VS Code Marketplace] [Open VSX] [License] [GitHub stars]

A deterministic guardrail your coding agent runs on itself — before the code reaches your disk.

Every other check fires too late. A review bot needs a PR. A pre-commit hook runs after the agent has finished and moved on. DiffGate is an agent hook: your agent calls it over MCP, gets back structured findings in milliseconds for zero LLM tokens, and fixes the problem while it still has the context — then the same engine, same verdict runs in your editor, your pre-commit hook, and CI. Not a model grading its own homework: the same input always produces the same answer.

It stays quiet by construction. It grades only the lines that changed (🟢 merge · 🟡 glance · 🟠 verify), runs your tests only when a change earns it, and blocks only when it's earned — 0 false blocks on a public, versioned corpus you can rerun yourself with diffgate bench (BENCHMARK.md). Everyone claims low noise; this one ships the corpus.

Why this catches things a scanner doesn't — we measured what agents actually get wrong

Across local and frontier models: 0% classic OWASP bugs (SQL injection, XSS, hardcoded secrets) in code written from scratch. But the same frontier model that wrote flawless greenfield code reintroduced security footguns in 13% of edits — an unguarded recursive merge (prototype pollution), a bare cors() (any origin), a path built from request data with no containment check. Editing existing code is most of what an agent does, and the residue lives in the diff, not in the textbook. Rerun it yourself with diffgate marginal. The measurement →

The same shift shows up in third-party maintainability data: GitClear's 2026 analysis finds block duplication up 81% since 2023 (40.3 → 73.0 per million changed lines) and cross-file function connectivity down 35% — agents reinvent code rather than reuse it. That's what the reinvented-helper rule is for (docs/STRUCTURAL-RULES.md).

[DiffGate demo: diffgate check on a real repo, mostly green with one orange finding and its reason]

TierMeaningWhat you doExamples
🟢 GreenSafe / self-containedmerge freelycomments, local logging
🟡 YellowReview (soft dependency)take a lookdeprecated APIs, raw SQL, network calls, dependency edits
🟠 OrangeHigh-impact, gate itverify before mergeschema/migrations, hardcoded secrets, auth/crypto, public-API changes, injection sinks

Why an agent hook, not another review bot

Every check in the pipeline fires after the code exists, and each one is later than the last:

Fires whenProblem
Review bot (CodeRabbit, Greptile)a PR existsthe code is finished, defended, and someone is waiting on it
Pre-commit hookyou're done and committingthe agent has moved on; you're re-loading context to fix it
DiffGate over MCPthe agent is still writingit fixes its own output before the code lands

Being early is not the only thing that matters, though — it has to be quiet, or the agent learns to ignore it. Review bots comment after the PR exists; linters and scanners flag everything they see. Neither guarantees the risky line gets discussed: we scanned 350 merged AI-assisted PRs — of the 109 with flagged AI-attributed changes, only 3 drew public discussion from any human besides the author. DiffGate decides what deserves your attention, your tests, or a block, and stays quiet otherwise. That's the whole product:

  • Diff-scoped. Findings report only on the lines that changed, against the committed baseline — no whole-file noise, no re-litigating code you didn't touch.
  • Tiered triage, not a flat list. Three tiers route attention: green merges, yellow is a glance, orange is gated.
  • The gate runs your tests — selectively. On an orange change, DiffGate runs your testCommand and shows the real exit code and output. Green and yellow pass instantly. The pre-commit hook is fast because tests fire only when a change is genuinely high-impact.
  • Earns the right to block. Broad cross-language injection findings stay advisory on their own; they escalate to a blocking finding only when the optional code graph proves the sink is reachable from an untrusted entry point (an HTTP/event handler). Recall from the rules, the right to block from the graph.
  • Change-impact aware. With an optional code graph, a finding carries its cross-file blast radius — caller counts, suggested reviewers, untested call sites — and an exported symbol nobody calls is de-escalated. Cross-file context makes reviews quieter, not louder.
  • Fast. A review runs in milliseconds on the changed lines — quick enough to sit in the agent and editor inner loop, not only in CI.
  • Provably low-noise. diffgate bench runs a versioned corpus offline: 100% precision / 0 false blocks on clean changes. Reproduce it yourself — that's the point of shipping the corpus. See BENCHMARK.md.

The measurement is reproducible

The 0% / 13% numbers aren't a marketing line — they come from a scripted experiment (four models from local to frontier, greenfield vs. edit mode, Wilson confidence intervals) that you can rerun with diffgate marginal. Methodology, per-model tables, and caveats: docs/MEASUREMENT.md. DiffGate's security rules are tuned to that measured residue, not to maximizing rule count.


Quick start

bash
npm install -g diffgate-reviewcd your-repodiffgate init                    # auto-detects language + test command, writes .diffgate.jsondiffgate check --since=HEAD~20   # see what it catches in your own history — no PR requireddiffgate check                   # review your pending changes right now

No git history or uncommitted changes yet? See the output on bundled examples first:

bash
diffgate init --demo   # live scan, no config or git changes needed

The surfaces (one shared engine, one verdict)

1. In your coding agent (via MCP)

The highest-leverage spot: the agent self-checks generated code before it's written to disk, gets back structured findings (zero LLM tokens), and surfaces what it corrected (original + fix + why) instead of silently rewriting. A trustworthy, deterministic self-check is what makes it safe to grant the agent more autonomy.

bash
# Claude Code — one command:claude mcp add diffgate -- diffgate mcp
# One-click via Smithery (zero config):npx @smithery/cli install diffgate-review --client claude
# Cursor — add to MCP settings:# { "diffgate": { "command": "diffgate", "args": ["mcp"] } }

Or one-click in Claude Desktop: download diffgate.mcpb and open it. The server also exposes prompts and resources; see MCP.md.

2. In your editor (VS Code / Cursor)

Inline squiggles on changed lines, hover cards (why · who owns it · quick-fix), a Risk Review tree, a status-bar summary, and Deep Review (agentic blast-radius analysis for orange findings). The same verdict you'd get from the CLI, on the diff you're reviewing.

Install from the VS Code Marketplace or Open VSX (Cursor / Windsurf / Gitpod).

3. On the command line — and in CI

diffgate check reviews your diff and exits non-zero on high-impact findings: a pre-commit hook locally, the same gate in your pipeline.

bash
diffgate install-hook  # adds .git/hooks/pre-commit; only runs tests on 🟠 orange changes

The local loop is the wedge — fix while the context is fresh — and the same engine runs as a PR gate so the verdict carries to where it's enforced for the whole team. See docs/TEAM.md for the GitHub Action, shared learnings, and org policy packs. CI runs can optionally layer an external scanner (Semgrep) through the same gate for broader language coverage — advisory-only, off by default (docs/CONFIG.md).

Common commands:

bash
diffgate check                 # review pending changes (the gate)diffgate check --staged        # staged-only (pre-commit)diffgate check --since=HEAD~20 # audit recent history, per-commit (see below)diffgate check --agent         # machine verdict for coding agentsdiffgate scan <path>           # analyze files directly (no git needed)diffgate watch                 # live review as you editdiffgate guidelines            # review diff against AGENTS.md / CLAUDE.md etc.diffgate feedback <rule> <f> <l> --dismiss   # suppress a false positive (shared via git)diffgate mcp                   # start the MCP stdio server

Audit recent AI-authored history. Point check at commits already in your log — each finding is attributed to a specific commit, so you get a story, not a repo-wide report card:

bash
diffgate check --since=HEAD~20        # last 20 commits, one block per commitdiffgate check --since="2 weeks ago"  # by date instead of a revdiffgate check --ai-authored          # only agent commits (Claude/Copilot/Cursor/… — heuristic)diffgate check --author="Claude"      # matches author *and* Co-authored-by trailersdiffgate check <sha>                  # a single commit by hash

History mode is report-only (it audits the past — it never runs your test command or blocks a commit) and honors --json and --limit=<n> (default 50). Merge commits are skipped.

Run diffgate --help for the full list (report, bench, stats, graph, marginal, …).


How it works

  • Diff-aware: git diff (CLI) or an in-memory LCS diff (editor, accurate on unsaved buffers) finds changed lines; findings only report on those lines.
  • Real AST where it counts: @babel/parser (JS/TS) and tree-sitter (Python, PHP, Go, Ruby, Java, C#, Kotlin — via WASM, no native build) power precise rules: deprecated calls aren't matched inside comments or strings, exported-signature changes are detected structurally, and SQL injection is sink-targeted, parameter-aware, and sanitizer-aware — cur.execute(f"… {uid}") / $pdo->query("… $id") block, while cur.execute("… %s", (uid,)), $pdo->prepare("… ?"), a single-quoted '… $id', and a SELECT in a log line don't.
  • A deterministic floor everywhere else: comment-aware pattern rules for secrets, destructive/schema changes, auth/crypto, dynamic execution / shell-out, raw queries, and network calls across Go, Java, Ruby, and any text. Commented-out code (# os.system(x)) isn't flagged; a secret committed inside a comment still is. Docs/prose files (.md, .rst, …) are held to the same standard: the word "oauth2-provider" in a changelog isn't auth code, but a key pasted in a README is still a leak.
  • Earned blocking: broad cross-language injection advisories for the non-AST languages (Ruby #{}, Go/Ruby shell-out) escalate to blocking only when the optional code graph proves reachability from an untrusted entry point — community CodeGraph, no Pro taint engine required. (JS/TS, Python, and PHP block on local AST evidence and don't need this.)
  • The gate: on a high-impact change, DiffGate runs your testCommand and shows the actual exit code and output.
  • Learnings: diffgate feedback records dismiss/confirm verdicts; dismissed findings (same rule + same code) are suppressed everywhere. Stored in .diffgate/learnings.json; commit it to share across the team.
  • Optional add-ons: a provider-agnostic AI layer (plain-English explanations + fixes) and a cross-file blast-radius pass via an optional code graph. Both are off by default and degrade gracefully to a no-op.

Engine layout: src/core (shared) · src/cli.ts (CLI) · src/mcp.ts (MCP) · extension/ (VS Code).


Coverage scales with language

How deeply DiffGate analyzes a change depends on the file's language — be explicit about this so you can calibrate how much to trust a clean result.

TierLanguagesDepth
Deep (AST)JS / TS (@babel)All injection classes + public-API & signature changes + deprecated-API quick-fixes. Prototype pollution and NoSQL injection are JS/TS-only; JS/TS findings are also eligible for code-graph taint confirmation.
Deep (AST)Python, PHP, Go, Ruby, Java, C#, Kotlin (tree-sitter)Sink-targeted, parameter- and sanitizer-aware injection detection — placeholders, argument-vectors, and escapers are correctly treated as safe. Sink classes per language below.

Sink classes per Deep-AST language (full detail — every sanitizer and safe-form, plus the code-graph boundary — in docs/SCOPE.md):

  • Python (7) — SQL · XSS · path traversal · CORS · command · code · deserialization
  • PHP (8) — SQL · command · code · file inclusion · deserialization · XSS · path traversal · CORS
  • Go (4) — SQL · command · path traversal · CORS
  • Ruby (6) — SQL · command · code · deserialization · XSS · CORS
  • Java (6) — SQL · command · deserialization · path traversal · XXE · CORS
  • C# (7) — SQL · command · deserialization · path traversal · XSS · XXE · CORS
  • Kotlin (6) — SQL · command · deserialization · path traversal · XXE · CORS

SSRF is a cross-language advisory across all eight Deep-AST languages (a request-tainted URL into an outbound-request sink; library-qualified and tainted-only, so static/config URLs aren't flagged). XXE covers the JVM (Java, Kotlin) and .NET (C#), suppressed when the file shows recognized hardening. Permissive CORS now also covers all eight — wildcard Access-Control-Allow-Origin, allow-all framework configs (gin/rs-cors, Spring @CrossOrigin, ASP.NET AllowAnyOrigin(), Ktor anyHost(), rack-cors), and request-reflected origins; explicit allowlists aren't flagged.

TierLanguagesDepth
Floor (pattern)C/C++, Rust, Swift, Scala, …Secrets, destructive/schema changes, auth/crypto, dynamic exec / shell-out, raw queries, network calls, TODO. Cross-language injection advisories that escalate via the code graph.
TextYAML, Terraform, JSON, any textSecrets and TODO/FIXME markers.

Fast by design — and scoped to match. A review runs in milliseconds on the changed lines, which is exactly what lets the same check sit in the agent and editor inner loop. That speed is a deliberate trade: DiffGate is the deterministic gate on the diff, not an exhaustive whole-repo taint engine. Coverage is per-language (deep where there's an AST, a pattern floor elsewhere), the security rules are tuned to the residue agents actually ship rather than to maximize raw rule count, and a clean result means "nothing matched at this language's tier," not "proven safe." For deep cross-file taint analysis across many languages, pair it with a dedicated SAST. Full per-language detail and the code-graph boundary: docs/SCOPE.md.


Configuration

diffgate init writes a tailored .diffgate.json at your repo root. Minimal example:

jsonc
{  "testCommand": "npm test",          // run for orange changes (the gate)  "gate": { "mode": "working", "failOn": "orange" },  "deprecated": [    { "pattern": "StripeClient.charge", "replacedBy": "StripeClient.createPaymentIntent" }  ]}

Any rule — built-in or custom — can be path-scoped with include/exclude globs, the escape hatch for the one file where a forbidden idiom is legitimate (e.g. process.env inside the config loader itself). Full schema, the built-in rule table, LLM providers, and per-rule tuning: docs/CONFIG.md.


More

  • The PR was reviewed. The risky line wasn't. — our PR-trail study: 350 merged AI-assisted PRs, 109 with flagged AI-attributed changes, 3 with public human discussion beyond the author.
  • docs/SCOPE.md: per-language coverage tiers (deep AST vs. pattern vs. text-only) and what the code graph does and doesn't do.
  • docs/CONFIG.md: full .diffgate.json schema, all built-in rules, LLM providers, native precision & test-scope behavior.
  • docs/TEAM.md: rolling DiffGate out to a team (GitHub Action / PR gate, shared learnings, org-wide policy packs, SOC 2 evidence, metrics for leaders).
  • docs/CODE-GRAPH.md: optional cross-file blast radius (caller counts, suggested reviewers, test gaps, reachability, taint analysis).
  • docs/STRUCTURAL-RULES.md: the structural pack — over-engineering rather than vulnerabilities (needless abstractions, pass-through wrappers, complexity spikes), all non-blocking, with per-language thresholds.
  • docs/MEASUREMENT.md: what agents actually ship unprompted and how to reproduce it (diffgate marginal).
  • MCP.md: MCP tools, prompts, resources, and AI configuration.

Try it

bash
diffgate scan mock_project

You'll see green findings (logging), yellow findings (a deprecated call), and orange findings (a DROP COLUMN migration, a public export).

Tests

bash
npm test    # builds the extension, runs the full unit/integration suite + extension smoke test

Support the project

If DiffGate caught something for you — or you just like the idea of a deterministic gate for agent code — star the repo ⭐. It's the signal that tells other people this is worth trying.

  • 🐛 Found a false block, or a sink it missed? Open an issue — a false block is a bug we treat as P0.
  • 💡 Want a language or rule covered? File a feature request with the idiom you'd like caught.
  • 🔒 Security report? Please disclose privately — see SECURITY.md.

Contributing & License

See CONTRIBUTING.md. Apache 2.0; see LICENSE.

來源:README.md,提交 174b4a9

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版本歷史

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  1. v0.8.0最新Sep 16, 2026

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