DiffGate

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Coding agents don't write textbook vulnerabilities anymore — they delete your guardrails while editing.

We measured it 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. And editing existing code is most of what an agent does. The measurement →

DiffGate is the deterministic tripwire for exactly that residue — a review pass that runs before any review bot sees a PR, at the keystroke and the commit, where fixing is cheapest. It grades only the lines that changed (🟢 merge · 🟡 glance · 🟠 verify) in milliseconds, runs your tests only when a change earns it, and blocks only when it's earned: 0 false blocks on a public, versioned corpus (BENCHMARK.md). Not a model grading its own homework — the same verdict inside your coding agent (MCP), your editor, your pre-commit hook, and your CI.

Tier	Meaning	What you do	Examples
🟢 Green	Safe / self-contained	merge freely	comments, local logging
🟡 Yellow	Review (soft dependency)	take a look	deprecated APIs, raw SQL, network calls, dependency edits
🟠 Orange	High-impact, gate it	verify before merge	schema/migrations, hardcoded secrets, auth/crypto, public-API changes, injection sinks

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Why a tripwire, not another review bot

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 sits earlier — with the agent and the human writing the code — and decides what deserves your attention, your tests, or a block, staying 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.

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Quick start

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

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

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

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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.

# 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.

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:

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 agents
diffgate scan <path>           # analyze files directly (no git needed)
diffgate watch                 # live review as you edit
diffgate 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:

diffgate check --since=HEAD~20        # last 20 commits, one block per commit
diffgate check --since="2 weeks ago"  # by date instead of a rev
diffgate check --ai-authored          # only agent commits (Claude/Copilot/Cursor/… — heuristic)
diffgate check --author="Claude"      # matches author *and* Co-authored-by trailers
diffgate 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, …).

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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).

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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.

Tier	Languages	Depth
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.

Tier	Languages	Depth
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.
Text	YAML, Terraform, JSON, any text	Secrets 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.

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Configuration

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

{
  "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.

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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/MEASUREMENT.md: what agents actually ship unprompted and how to reproduce it (diffgate marginal).
• MCP.md: MCP tools, prompts, resources, and AI configuration.

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Try it

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

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.