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Umami

Privacy-focused, cookie-free open-source web analytics — a lightweight, self-hostable alternative to Google Analytics.

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इंस्टॉल4.1k
⟳ upstream v3.3.0 · updated 6d ago
↗ सोर्स रिपॉज़िटरी
← More MarketingMarketing leaderboard →How we grade security →Source ↗
! Grade B · 75/100 · ReviewSecurity assessment
✓No compromise signals10capabilities surfaced1known CVE8of 20 OWASP controls clear
External endpoints declaredSuspicious code patternsExternal endpoints declaredExternal endpoints declared
scanned 1d ago·osv · gitleaks · opengrep · picklescan + heuristics·full breakdown in the Security tab ↓

Umami

Umami is a simple, fast, privacy-focused open-source web analytics tool and a lightweight alternative to Google Analytics. It gives marketers and site owners the essential metrics — page views, visitors, referrers, campaigns (UTM), and events — without using cookies or collecting personal data, which simplifies GDPR/PECR compliance and avoids consent-banner friction.

Key features

  • Cookie-free, privacy-first tracking that does not collect personal information
  • Clean real-time dashboard: page views, visitors, bounce rate, and session duration
  • UTM campaign and referrer tracking for marketing attribution
  • Custom event tracking and per-URL/goal reporting
  • Self-hostable (Docker) on your own domain with unlimited websites and users

Umami runs on Node.js with PostgreSQL or MySQL and installs in minutes. A single script tag starts collecting data, and the tracker is only a couple of kilobytes, so it has negligible impact on page performance. With tens of thousands of GitHub stars, it is one of the most popular open web-analytics projects and a common choice for teams that want marketing insight while keeping full ownership of their visitor data.

Curated mirror of the open-source Umami (MIT). Get it from the source.

Rating rank
#1
of 13 in Marketing
Install rank
#13
of 13 in Marketing
Security score
75/100 · B
review
Security rank
#10
of 13 in Marketing
Installs
4.1k
cat avg 80k
This listing vs category average
Installs
this
cat avg
Security (of 100)
this
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See the Marketing leaderboard →
! Security: Review · 7575/100 · grade Bscanned 1d ago
✓ no compromise signals11 risk-surface · 6/20 OWASP controls flagged

Compromise signals — malicious or tampered code (leaked secrets, backdoors, a dropped executable) — reduce the score, and known dependency CVEs carry a bounded penalty (they warrant review but never QUARANTINE — update the dependency to clear). Other dangerous-by-capability traits are risk surface, expected for some capabilities. Every finding is mapped to its OWASP control below.

What this capability can do · med confidence (static)
⚑ network⚑ secrets
egress → nextjs.org, content.umami.is, img.shields.io, cloud.umami.is, umami.is, api.example.com, docs.nginx.com, twitter.com +3
19 steps⚑ uses secretsgithub.comactions/checkout@v3mr-smithers-excellent/docker-build-push@v6actions/checkout@v5docker/setup-qemu-action@v3docker/setup-buildx-action@v3docker/login-action@v3docker/build-push-action@v5

Findings mapped to the OWASP Top 10 for LLM Applications (2025) and the OWASP Machine Learning Security Top 10. Expand any flagged control for the exact findings — compromise reduces the score; expected/risk-surface do not, except a known CVE, which carries a small bounded penalty (high/critical → Review).

OWASP Top 10 for LLM Applications
⚠LLM03Supply Chaincritical
Vulnerable/compromised dependencies, models or archives in the artifact.
•Dependency manifest — 88 npm dependencies declared · umami-software-umami-de474a1/package.jsonrisk surface
•Vulnerable dependencies — 35 known vulnerabilities in: @babel/core@7.28.3, @babel/core@7.29.0, brace-expansion@1.1.12, brace-expansion@2.0.2, d3-color@2.0.0, esbuild@0.27.7, fast-uri@3.1.4, js-yaml@4.1.0 (CWE-1395)known CVE · -25 pts
⚠LLM05Improper Output Handlinghigh
Code that pipes model/user output into shell, eval, SQL or paths unsafely.
•Suspicious code patterns — destructive rm -rf / · umami-software-umami-de474a1/Dockerfile (CWE-78)risk surface
•Suspicious code patterns — child_process exec · umami-software-umami-de474a1/scripts/bump-components.js (CWE-78)risk surface
•Suspicious code patterns — environment/secret exfiltration · umami-software-umami-de474a1/src/app/api/record/route.ts (CWE-200)risk surface
⚠LLM06Excessive Agencymedium
Over-broad tool/permission surface or unrestricted egress.
•External endpoints declared — 1 distinct host(s) · umami-software-umami-de474a1/.github/ISSUE_TEMPLATE/config.ymlrisk surface
•External endpoints declared — 2 distinct host(s) · umami-software-umami-de474a1/Dockerfilerisk surface
•External endpoints declared — 12 distinct host(s) · umami-software-umami-de474a1/README.mdrisk surface
•Broad capability surface — 3 high-impact capability categories referenced — verify least-privilege · umami-software-umami-de474a1/pnpm-lock.yaml (CWE-272)risk surface
•External endpoints declared — 5 distinct host(s) · umami-software-umami-de474a1/src/app/api/send/route.test.tsrisk surface
•External endpoints declared — 3 distinct host(s) · umami-software-umami-de474a1/src/app/api/send/route.tsrisk surface
⚠LLM07System Prompt Leakagemedium
Secrets, internal hosts or proprietary logic exposed in shipped prompts.
•Internal host / private infrastructure reference — shipped content references a private IP range or internal-only host · umami-software-umami-de474a1/src/lib/detect.test.ts (CWE-200)risk surface
§LLM09MisinformationGovernance
Artifacts designed to produce false/deceptive output.
Detectable only by runtime behavioral evaluation; addressed via responsible-use attestation.
◷LLM10Unbounded ConsumptionRuntime-enforced
Unbounded loops/recursion causing DoS or runaway cost.
Enforced at runtime by the gateway (rate limits + spend caps + size caps); static check flags unbounded loops.
✓LLM01Prompt InjectionPassed
✓LLM02Sensitive Information DisclosurePassed
✓LLM04Data and Model PoisoningPassed
Backdoors/poisoning in training data or serialized models.
Behavioral poisoning needs model execution; static check covers unsafe serialization + dataset skew only.
✓LLM08Vector and Embedding WeaknessesPassed
PII or plaintext source leakage in embedding/vector exports.
Embedding inversion/poisoning is largely runtime; static check covers PII in vector exports.
OWASP Machine Learning Security Top 10
⚠ML06AI Supply Chaincritical
Compromised PyPI/npm packages, typosquats, unsafe serialized models.
•Dependency manifest — 88 npm dependencies declared · umami-software-umami-de474a1/package.jsonrisk surface
•Vulnerable dependencies — 35 known vulnerabilities in: @babel/core@7.28.3, @babel/core@7.29.0, brace-expansion@1.1.12, brace-expansion@2.0.2, d3-color@2.0.0, esbuild@0.27.7, fast-uri@3.1.4, js-yaml@4.1.0 (CWE-1395)known CVE · -25 pts
⚠ML09Output Integrityhigh
Middleware tampering with model outputs in transit.
Gateway enforces TLS + response integrity; static check flags output-rewriting code.
•Suspicious code patterns — destructive rm -rf / · umami-software-umami-de474a1/Dockerfile (CWE-78)risk surface
•Suspicious code patterns — child_process exec · umami-software-umami-de474a1/scripts/bump-components.js (CWE-78)risk surface
•Suspicious code patterns — environment/secret exfiltration · umami-software-umami-de474a1/src/app/api/record/route.ts (CWE-200)risk surface
§ML01Input Manipulation (Adversarial)Governance
Models vulnerable to adversarial perturbations.
Requires runtime robustness evaluation; addressed via publisher robustness attestation.
§ML03Model InversionGovernance
Training data reconstructable from a model's outputs.
Runtime/evaluation property; addressed via model-card data-provenance + DP attestation.
§ML04Membership InferenceGovernance
Determining whether a record was in the training set.
Runtime/evaluation property; addressed via overfitting disclosure + DP attestation.
§ML08Model SkewingGovernance
Models trained on skewed data producing biased output.
Requires fairness evaluation; addressed via model-card bias/limitations disclosure.
✓ML02Data PoisoningPassed
Poisoned training datasets with triggers or anomalous distributions.
Static check covers trigger phrasing, PII and label skew; full poisoning detection is runtime.
✓ML05Model TheftPassed
Unlicensed re-distribution / license-incompatible derivatives.
Static check verifies license declaration; extraction throttling is runtime.
✓ML07Transfer Learning AttackPassed
Backdoored base models / LoRA adapters propagating to derivatives.
Backdoor detection needs behavioral probing; static check covers unsafe serialization + provenance.
✓ML10Model Poisoning (Weights)Passed
Tampered model weight files; integrity must be verifiable.
Static check enforces safe formats + records a content hash for downstream verification.
Other findings (7) · hygiene / uncategorized
•Unrecognized file type — '.dockerignore' is not on the allowlist · umami-software-umami-de474a1/.dockerignorerisk surface
•Unrecognized file type — '.gitignore' is not on the allowlist · umami-software-umami-de474a1/.gitignorerisk surface
•Unrecognized file type — '.?' is not on the allowlist · umami-software-umami-de474a1/Dockerfilerisk surface
•Unrecognized file type — '.sample' is not on the allowlist · umami-software-umami-de474a1/podman/env.samplerisk surface
•Unrecognized file type — '.service' is not on the allowlist · umami-software-umami-de474a1/podman/umami.servicerisk surface
•Unrecognized file type — '.prisma' is not on the allowlist · umami-software-umami-de474a1/prisma/schema.prismarisk surface
•Unrecognized file type — '.webmanifest' is not on the allowlist · umami-software-umami-de474a1/public/site.webmanifestrisk surface
✔ verified source · pinned umami-software-umami-de474a1
Check against a policy

The same gate an agent runs before installing (POST /api/v1/trust/umami-web-analytics/check). Click a policy:

Consume Umami programmatically. Authenticate with an API key or session — see Authorize an agent.

# Agents: CHECK BEFORE YOU INSTALL (no auth) — score, grade, level, capability manifest
curl https://ai-supply.store/api/v1/trust/umami-web-analytics

# Gate against your org policy (returns { pass, violations })
curl -X POST https://ai-supply.store/api/v1/trust/umami-web-analytics/check \
  -H "Content-Type: application/json" \
  -d '{"minGrade":"B","denyPermissions":["shell"],"denyUnknownEgress":true}'

# CLI
npx ai-supply add umami-web-analytics

# REST (install → download)
curl -X POST https://ai-supply.store/api/v1/listings/umami-web-analytics/install \
  -H "Authorization: Bearer $AIM_KEY"

# MCP tool
install_listing({ "slug": "umami-web-analytics" })
OpenAPI spec →
vlatest
! Security: Review · 751mo ago

Curated mirror — latest upstream source. See the repository for tagged releases.

Sign in and install this listing to leave a review.

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