umbra

Everyone is vibecoding. Nobody is verifying. Umbra scores it.

Umbra is a deterministic Trust Score (0–100) for AI-generated code: the vibe coding security scanner that verifies what your agent shipped, not what it claimed. One command, fully local, evidence for every finding.

Quickstart · Demo · The Audit · How it works · The Four Axes · FAQ · Roadmap · Contributing

Why Umbra exists

Studies put exploitable vulnerabilities in 40 to 60 percent of AI-generated code, and coding agents routinely claim "all tests pass" when three do. The tooling for writing code with AI is a year ahead of the tooling for trusting it. Umbra closes that gap: SAST rebuilt for how software gets written now, plus sandboxed verification that catches what static rules cannot.

One command scans any repo an agent produced (Claude Code, Cursor, Copilot, Windsurf, Lovable) and returns a score with file:line evidence for every finding. With --deep it goes further: Umbra builds and boots the repo in a locked-down Docker sandbox, then replays the agent's own claims against reality. If the agent is lying about tests, the score is capped below passing, with receipts.

The audit: 61 vibe-coded repos, scanned

We ran Umbra over 61 public, actively-maintained AI-built repos and published everything. The Vibe-Coding Security Audit:

Mean trust score: 74/100. One in five repos fails outright. The full report has per-class deep dives with representative snippets and fixes, the complete per-repo table, and an honest methodology section — including the false positives we found in our own rules while running it, and fixed (rubric v4).

Quickstart

npx umbra-scan            # check — scans the directory you're standing in
npx umbra-scan --fix      # heal — applies provably-safe fixes, shows the score climbing
npx umbra-scan --setup    # protect — pre-commit gate, PR checks, agent guardrails

That's the whole interface. Three verbs: check, heal, protect.

Using an AI coding agent? Umbra is built to be driven by agents, not just run by humans:

• Any agent — it reads this repo's AGENTS.md / llms.txt and knows what to do. Or tell yours: "check this repo with umbra."
• Claude Code / Kimi Code — --setup installs PreToolUse hooks so every file the agent writes is guarded before it lands.
• Claude Code, Cursor, Copilot, Windsurf — the trust-review skill makes the agent scan its own work before declaring done.
• MCP-native agents — add umbra-mcp (npx --yes -p @elberacasa/umbra umbra-mcp) and the agent gets scan_repo, guard_content, and get_score as tools.

Real output, scanning a typical vibe-coded Next.js app (fixtures/bad-app in this repo, Trust Score 30/100):

$ npx umbra-scan ./fixtures/bad-app

UMBRA TRUST SCORE: 30/100  🔴

SAFE   🔴 5/100 — 14 findings
CLEAN  ✅ 87/100 — 10 findings
RUNS   — not measured — run with --deep
HONEST — not measured — run with --deep

Score computed over measured axes only (full rubric: SAFE 35%, RUNS 25%, HONEST 25%, CLEAN 15%). Rubric v4.
…plus 7 further findings beyond the per-rule cap (see report)

Top findings:
  [safe/hardcoded-secrets] Hardcoded Supabase service_role JWT — bypasses all row level security — .env:2
  [safe/hardcoded-secrets] Hardcoded Supabase service_role JWT — bypasses all row level security — lib/supabase.ts:5
  [safe/supabase-antipatterns] Supabase service_role key reachable from client-side code — full database bypass for anyone who opens the bundle — .env:2
  [safe/supabase-antipatterns] Supabase service_role key reachable from client-side code — full database bypass for anyone who opens the bundle — app/components/UserList.tsx:10
  [safe/hardcoded-secrets] Committed environment file with secret values: .env — .env:1

Notes (low confidence — not scored):
  [safe/missing-rate-limit] Auth endpoint with no rate-limiting signal in the repo — brute-force / credential-stuffing exposure (heuristic) — app/api/login/route.ts:3

Badge: [![Umbra Trust Score](https://img.shields.io/badge/Umbra_Trust_Score-30-red)](https://github.com/elberacasa/umbra)

The exit code is 1 when the score is below 50, so CI can gate on it.

umbra [path]               # path defaults to the current directory
umbra [path] --json        # machine-readable output
umbra [path] --offline     # skip npm registry checks, fully local
umbra [path] --deep        # verify RUNS and HONEST in a Docker sandbox
umbra [path] --report      # write UMBRA.md: an agent-actionable task list
umbra [path] --fix         # apply provably-safe fixes and re-scan (score before → after)
umbra [path] --dry-run     # preview --fix without writing anything
umbra [path] --baseline-write  # write .umbra-baseline.json: grandfather current findings, gate only on new ones
umbra [path] --baseline <path> # use an explicit baseline file ("write" is shorthand for --baseline-write)
umbra setup                # install everything (hooks + Action + agent guards)
umbra init                 # only the pre-commit hook + GitHub Action
umbra protect              # only the agent PreToolUse hooks (--remove uninstalls)
umbra guard --stdin        # hook entrypoint (agents call this, not humans)
umbra mcp                  # run the MCP server (bin: umbra-mcp)

How it works

repo in
   │
   ▼  Layer 0 · static rules (17 SAFE + CLEAN rules, 0 tokens, <1s)
   ▼  Layer 1 · evidence gating (confidence-scored, low never moves the score)
   ▼  Layer 2 · --deep sandbox (Docker: build, boot, HTTP probe, claim replay)
   │
   ▼  deterministic Trust Score + verdict + badge

Every finding carries a confidence level and file:line evidence. Only high and medium confidence findings move the score; hunches go to a notes section. The rubric is versioned (currently v3), so the same repo always gets the same score. Full math in RUBRIC.md.

The immune layer: guard the write, not just the repo

Scanning finds problems after they land. The immune layer checks every file your agent writes before it lands. umbra protect installs PreToolUse hooks into Claude Code and Kimi Code (auto-detected, one command); the same engine backs the umbra-mcp server for MCP-native agents.

flowchart LR
    CC[Claude Code hook] --> E
    KC[Kimi Code hook] --> E
    MCP["umbra-mcp: guard_content"] --> E
    E{"guardContent(file, content)<br/>file rules + path guard"} -->|allow / warn| W[write lands]
    E -->|"block (exit 2)"| B["reason fed back:<br/>agent fixes the root cause"]

npx umbra-scan protect   # install the hooks; --remove uninstalls cleanly

A leaked Stripe key or an alg: none JWT never reaches the file. The path guard hard-blocks agent writes into .git/hooks and .git/config (CVE-2026-26268, the agent-planted git hook escape), and live credentials going into .env. Blocking is reserved for high-confidence critical/high findings; everything else warns, and every failure fails open. Verdicts land in ~0.2 ms, so the guard never slows the agent down. Full story: docs/immune-layer.md.

--deep: verify AI code, don't trust it

The fast scan is static. --deep is LLM code verification with evidence. Umbra copies the repo into a throwaway Docker container (no network at runtime, 512 MB / 1 CPU hard limits, 120-second kill switch), builds it, boots it, HTTP-probes its endpoints, and replays every claim found in READMEs and agent artifacts against what actually happens. Slower (minutes, not seconds) and needs a running Docker daemon. Without Docker the sandboxed axes are skipped and left out of the score; unverifiable is never punished.

Real output, deep-scanning a repo whose README lies (fixtures/claims-app, capped at 49/100 by the liar cap):

$ npx @elberacasa/umbra ./fixtures/claims-app --deep

UMBRA TRUST SCORE: 49/100  🔴

SAFE   ✅ 100/100 — 0 findings
CLEAN  ✅ 100/100 — 2 findings
RUNS   — not measured — No detectable run path (no Dockerfile, no package.json start script or main entry)
HONEST ⚠️ 50/100 — 2 claims failed, 2 verified, 1 unverifiable

Score computed over measured axes only (full rubric: SAFE 35%, RUNS 25%, HONEST 25%, CLEAN 15%). Rubric v4.
Score capped below passing: a documented claim was verified false. Trust is the product.

Claim receipts:
  CLAIM FAILED: "14 tests pass" — README.md:7 — actually 3 tests pass, 0 fail
  CLAIM FAILED: "build passes" — README.md:9 — actually build exits 1
  CLAIM VERIFIED: "All tests pass" — CLAUDE.md:3 — 3 tests pass
  CLAIM VERIFIED: "All tests are passing" — README.md:8 — 3 tests pass

Any claim verified false caps the total at 49: a repo caught lying does not get a passing trust score. For contrast, a genuinely working app (fixtures/runnable-app) scores 100/100 under --deep.

The Four Axes

The SAFE rules cover the failures AI-generated code security actually ships: hardcoded secrets (Stripe keys, JWTs, connection strings), Supabase service-role keys exposed client-side and missing Supabase RLS, missing auth on API routes, injection sinks, rate-limit hints, hallucinated and typosquatted dependencies, CORS wildcard with credentials, JWT misconfig (alg: none, no expiry, decode-as-authorization), debug flags and stack-trace leaks, committed sensitive files (.pem, id_rsa, SQL dumps), and default credentials.

It also lints the agent's own setup — the surface nobody else covers: prompt-injection payloads in instruction files (CLAUDE.md, .cursor/rules, skills: zero-width Unicode, override phrases in HTML comments) and dangerous MCP configs (literal API keys in .mcp.json, unpinned npx -y servers, curl | sh installers). These run in the guard too, so an agent editing its own config gets checked mid-write.

Umbra vs. existing tools

Existing tools answer "is this code pattern dangerous?" Umbra answers the question vibe coding actually raises: "the AI wrote this, can I trust it?"

The badge

Every scan prints badge markdown. Paste it in your README and your repo advertises its own trust score:

[![Umbra Trust Score](https://img.shields.io/badge/Umbra_Trust_Score-30-red)](https://github.com/elberacasa/umbra)

One engine, every surface

• CLI (npx @elberacasa/umbra): the core, available today. Short alias: npx umbra-scan.
• Agent skill: a trust-review skill installable into Claude Code, Cursor, Copilot, and Windsurf, so the agent checks its own work before you do. Claude Code / Cursor / Copilot security, from inside the agent.
• GitHub Action: uses: elberacasa/umbra@v1 comments the Trust Score on every PR. Trust gating in CI, zero local setup.
• umbra setup: the one-word installer — pre-commit gate, PR score comments, and PreToolUse guard hooks for detected agents, all idempotent and clobber-free. (init and protect remain for piecemeal installs.)
• umbra protect: installs PreToolUse hooks into Claude Code and Kimi Code (auto-detected, idempotent, --remove to uninstall) so Umbra reviews every agent write mid-stream and blocks dangerous ones before they land.
• MCP server (umbra-mcp): agents call Umbra mid-stream and catch their own mistakes before the code lands. Add it with npx --yes -p @elberacasa/umbra umbra-mcp.

Day-to-day recipes (CI gating, JSON parsing, hooks): docs/daily-use.md.

Roadmap

• v0.1 (shipped): CLI, SAFE + CLEAN static axes, deterministic score, verdict output, badge markdown.
• v0.2 (shipped): the surfaces. Agent skill, GitHub Action, umbra init.
• v0.3 (shipped, current): RUNS axis (sandbox build, boot, HTTP probe) and HONEST axis (claim receipts plus the liar cap).
• v1.0 (shipped): the immune layer. Umbra sits between the agent and your codebase, intercepting writes mid-stream and scoring them before they land. Full story in docs/immune-layer.md.
• Beyond: attack graphs across your dependency tree, a security twin of your app that gets probed so production doesn't, hosted report permalinks behind every badge.

The wedge is a score. The destination is the verification layer every AI-built repo runs through.

FAQ

How do I adopt Umbra in a repo that already has findings? Run npx umbra-scan --baseline-write once. Umbra writes .umbra-baseline.json into the repo root, and from then on the gate only blocks new issues — existing findings are grandfathered (the verdict shows baseline: N existing findings grandfathered (M new)), so you fix forward instead of boiling the ocean. Commit the baseline file so the whole team and CI share it.

How is Umbra different from Semgrep, Snyk, or trufflehog? They scan code patterns; Umbra verifies outcomes. Static rules are one input to the SAFE axis. Umbra additionally boots the app in a sandbox to prove it runs, and replays the agent's documented claims to prove it isn't lying. "README says 14 tests pass, actually 3 do" costs the repo a passing grade.

Does Umbra send my code anywhere? No. Scanning is fully local; --offline skips even the npm registry checks. --deep runs your repo in a local Docker container with no network at runtime. Nothing leaves your machine.

Does it need Docker? Only for --deep (RUNS and HONEST). The default fast scan is pure static analysis. Without Docker the sandboxed axes are skipped and excluded from the score, never punished.

What languages does it support? JavaScript and TypeScript (including Next.js and Supabase apps) have the deepest coverage today, which is where most vibe-coded repos live. The rule engine is extensible; new rules need a fixture and a test.

Is the score reproducible? Yes. Same repo, same rubric version, same score, every time. The rubric is versioned (v2) and printed in every report, and low-confidence findings never affect it. Skipped axes are excluded and renormalized over, never punished.

What does it catch that my AI agent won't mention? The classics of AI-generated code: a Supabase service_role JWT shipped to the browser (bypasses all row level security), live Stripe keys in .env, API routes with no auth check, alg: none JWTs, CORS * with credentials, hallucinated dependencies that don't exist on npm, and whether its own claims about tests and builds are true.

Can Umbra stop my agent mid-write? Yes, via hooks. Run npx @elberacasa/umbra protect and Umbra installs a PreToolUse hook into Claude Code and/or Kimi Code that reviews every Write/Edit/MultiEdit before it lands. Only high-confidence critical and high severity findings block (a wrong block gets tools uninstalled, so when in doubt Umbra warns), the .git/hooks path guard blocks git-hook planting (CVE-2026-26268) outright, and the guard fails open on its own errors so it never breaks your flow. Hooks are a guardrail, not a sandbox; details in docs/immune-layer.md.

Can my AI coding agent use Umbra directly? Yes, that is the design. The repo ships an AGENTS.md and llms.txt so assistants know exactly when and how to run it, and the agent skill makes Claude Code, Cursor, Copilot, and Windsurf scan their own work before declaring a task done.

Contributing

Issues and PRs welcome. See CONTRIBUTING.md. The highest-value contributions right now: new SAFE/CLEAN rules with fixtures and tests, false-positive reports (severity-one bugs here), renders against real AI-generated repos, and new harness adapters for umbra protect.

Build and test before submitting:

npm install
npm run build
npm test

Ethical use

Umbra is a defensive tool. Scan repos you own, repos you are about to depend on, or repos you have permission to audit. Findings point at weaknesses; they are not exploits, and publishing someone else's low score to shame them is not the point. The point is that "the AI wrote it" stops being the end of the verification conversation.

License

MIT