Snyk alternative for AI-built apps — sandbox-verified, no false positives
Snyk users cite false-positive rate (6.8/10 on G2), 1MB file-size skipping, and upgrade-tier frustration as top reasons for looking elsewhere. Here's what to pick instead.
People searching for a Snyk alternative in 2026 almost always share one of three complaints: the false-positive tax is eating their engineers' week, the file-size skipping makes findings unreliable on monorepos, or the upgrade cliff from Team to Enterprise ($25 to $98 per developer per month) feels steep for the incremental value. Snyk is the incumbent for reason — broad language coverage, mature SCA, solid container scanning — but the shape of the product was set in 2015, before AI-generated code became the dominant source of new application bugs.
This page is an honest comparison for the specific slice of the market where Snyk is weakest: teams shipping AI-built applications on Next.js, Supabase, and Vercel, where the bugs are not generic CWE-79 reflected XSS patterns but framework-specific Row-Level-Security mistakes, broken object-level authorization on API routes, and leaked API keys in AI-generated endpoint handlers. Snyk can catch the generic version of these bugs; it cannot reproduce them as working exploits, it cannot write framework-aware fixes, and it does not have dedicated specialists for Supabase RLS or for prompt injection. Securie is purpose-built for that gap. If you are not in that gap — if you run Java, Go, and Rust in production with a mature security team triaging the Snyk queue — Snyk is likely still the right answer and this page will tell you that honestly.
Why people leave Snyk
- G2 false-positive score of 6.8/10 — triage fatigue is the top complaint
- Silently skips files over 1 MB without warning
- Enterprise tier ($52-98/dev/mo) forces upgrade for basic auto-fix
- No sandbox verification — findings need manual triage
- No Supabase RLS or AI-feature specialist
Where Snyk actually breaks down
The 6.8/10 false-positive score on G2 maps to real engineering hours
Example: A typical Snyk Code scan on a 150-KLOC Next.js repository produces 40-80 findings per week in the default configuration. Public G2 reviews from teams at Series-B stage consistently describe 60-70% of those as false positives or theoretical issues that are not exploitable in context (protected behind auth, sanitized upstream, or on code paths never called in production). Security engineers then spend 3-6 hours per week triaging the queue before any real bug gets attention.
Impact: At $150/hr loaded engineering cost, a 10-person team burns roughly $1,200-$2,500 per month on Snyk triage alone — before the subscription cost. That is often larger than the cost of the tool itself. Signal-to-noise degrades further as the codebase grows, because Snyk does not have a sandbox to prove whether the bug is exploitable — it can only pattern-match on syntax.
Silent 1 MB file-size skipping
Example: Snyk Code (the SAST engine) imposes a 1 MB per-file size limit and silently skips anything larger without emitting an error or warning into the CI log. On monorepos with bundled JavaScript, generated TypeScript definition files, or schema-first-compiled GraphQL output, the files most likely to contain injection vulnerabilities are exactly the ones exceeding 1 MB.
Impact: Teams discover this limit during an incident post-mortem ("Snyk said the scan was clean; why did the CVE land on our main.js?") rather than in the product's UI. There is no in-dashboard list of skipped files. Documented upstream in Snyk's own docs but rarely surfaced during evaluation.
No sandbox verification per finding
Example: A CWE-89 SQL-injection pattern match in Snyk does not attempt to actually execute a malicious payload against a sandboxed copy of the app. If the code shape matches the pattern but the execution context makes exploitation impossible — input is upstream-sanitized, the SQL driver is parameterised, or the endpoint is behind a mTLS gate that the scanner does not know about — the finding still ships as 'High severity'.
Impact: Without exploit reproduction, 'High severity' in Snyk means 'high according to our pattern catalog', not 'high according to what is actually reachable in your app'. Security teams compensate by manually re-classifying findings after triage, which is again the triage-tax problem in another form. Insurers and auditors increasingly want attested proof-of-exploit per finding; Snyk does not produce that artefact.
Steep upgrade cliff from Team to Enterprise tiers
Example: Snyk Team is listed at $25 per developer per month and includes basic SAST/SCA but not Snyk Fix PRs (auto-fix), IaC scanning, or advanced IDE integrations. Enterprise is listed at $52-98 per developer per month depending on contract size and adds those features. A 10-developer team moving from Team to Enterprise spends $3,240-$8,760 more per year for features that competitors (including Securie) offer as baseline.
Impact: Auto-fix and deeper IDE integration are the features that actually return time to engineering; gating them behind Enterprise means the smaller teams who would benefit most pay the most for the privilege. Many teams end up staying on Team with reduced coverage rather than make the economic jump.
No Supabase RLS, BOLA, or AI-feature specialists
Example: Supabase Row-Level-Security misconfiguration (a policy that forgets to filter by auth.uid()) is the single most common security bug in vibe-coded applications in 2026. Snyk has no dedicated detector for this class. It catches generic SQL injection and generic "missing authorization" warnings on REST handlers, but it does not parse `CREATE POLICY` statements, does not model the relationship between JWT claims and row visibility, and does not suggest a fix shape that fits Supabase conventions.
Impact: Teams on Supabase believe they are covered because Snyk is running, then discover during a penetration test that their RLS policies are broken and every user can read every other user's data. The false sense of coverage is worse than no coverage — it removes the prompt to run the dedicated check.
Why Securie instead
Zero false positives by construction
No finding ships unless Securie can reproduce the exploit in a sandboxed copy of your app. If the bug isn't real, you never see it.
Auto-fix PR, not just a dashboard row
Default output is a merged-ready pull request with a framework-aware patch, regression-tested in a shadow environment.
Purpose-built for AI-built apps
Supabase RLS specialist, prompt-injection detection, leaked-secret live-validation — the classes of bug AI tools actually produce.
Free during early access
No credit card, no time limit. Lifetime founding-rate discount when billing starts.
Feature matrix — Snyk vs Securie
| Area | Snyk | Securie |
|---|---|---|
| Finding verification | Pattern-based SAST/SCA; no runtime proof of exploitability per finding | Every finding reproduced as a working exploit in a Firecracker-sandboxed fork of your app before it reaches you |
| False-positive posture | Mitigated via rule tuning and manual triage; 6.8/10 FP score on G2 at baseline | Zero by construction — no exploit proof, no ticket; the sandbox is the filter |
| Auto-fix delivery | Snyk Fix PR on Enterprise tier; suggestion quality varies; pattern-generated | Default output for every proven finding: framework-aware patch as a one-tap pull-request comment, regression-tested against the exploit |
| Supabase Row-Level-Security | No dedicated specialist; generic SQL injection rules only | First-class specialist that parses CREATE POLICY, models JWT-claim-to-row-visibility, and suggests fixes that fit Supabase conventions |
| Broken access control (BOLA/BFLA/IDOR) | Generic authorization rules; pattern-based; high false-positive rate on framework routes | Dedicated specialist using intent-graph reasoning over Next.js route handlers; distinguishes protected-by-middleware from actually-protected |
| AI-feature security | None — no prompt-injection, tool-scope-abuse, or RAG-poisoning detection | Dedicated specialists for prompt injection, tool-scope abuse, RAG corpus poisoning, jailbreak regression |
| Language scope | TypeScript, JavaScript, Python, Java, Go, Rust, Kotlin, Swift, C/C++, PHP, Ruby, Scala | TypeScript + JavaScript at launch on Next.js + Supabase + Vercel; Python (FastAPI) on Series-A roadmap |
| File-size handling | Silently skips files over 1 MB in SAST; user not notified in CI | No size cap; full repository scanned, bundled files included |
| SCA / dependency scanning | Mature — Snyk's original strength; scans npm, PyPI, Maven, NuGet, RubyGems, etc. | Launch: malicious-npm-package detection + <15-minute CVE-to-block for npm; full cross-language SCA on roadmap |
| Container scanning | Snyk Container; scans base images, OS packages, and app dependencies | Not at launch; relies on complementary tooling (Trivy, Grype) for container-layer scanning |
| IaC scanning | Snyk IaC; Terraform, CloudFormation, Kubernetes YAML | Included specialist at launch for Terraform + Kubernetes; less mature than Snyk IaC for CloudFormation |
| Deploy gate | Snyk integrates with CI/CD but does not block deploys at hosting layer | Vercel Integration deploy-gate blocks unsafe deploys at the hosting layer before traffic arrives |
| Attestation artefact | Findings exportable as SARIF; no signed per-scan attestation | Signed in-toto + SLSA attestation per scan; auditor-consumable without additional work |
| Deployment modes | SaaS only; no Customer-VPC or air-gapped deployment | SaaS (sealed enclave) at launch; Customer-VPC + TEE-native + on-prem air-gapped on Series-A |
| Pricing (10-dev team, list) | Team $25/dev/mo = $3,000/yr; Enterprise $52-98/dev/mo = $6,240-$11,760/yr before container/IaC add-ons | Free during early access; founding-rate discount for life when paid tiers ship |
The deeper tradeoff
The shape of Snyk's weakness is not that its SAST engine is bad — it is genuinely one of the best pattern-based SAST engines on the market, and for polyglot shops running Python, Java, and Go in production it remains a reasonable default. The shape of Snyk's weakness is that pattern matching was the right abstraction for 2015 application security and is the wrong abstraction for 2026 AI-built applications.
In 2015, the hard problem was coverage — scanning millions of lines of handwritten Java across enterprise monoliths. Pattern matching was the only approach that scaled to that workload. Developers knew their frameworks; Snyk's job was to catch the exceptions. A 6.8/10 false-positive score was acceptable because the developer seeing the finding had enough framework context to triage it in thirty seconds.
In 2026, the hard problem has inverted. Codebases are smaller but framework-heavier. AI-generated code is confident, plausible, and wrong in framework-specific ways the developer did not write and cannot remember writing. A Next.js API route that forgets to check auth.uid() against the resource owner; a Supabase RLS policy that permits ALL rather than USING (auth.uid() = owner_id); a Server Action that accepts unsanitized FormData and passes it to a shell command. These bugs look correct at pattern level — there is no CWE-79 tag, no unvalidated input at the symbol level — but they are catastrophically wrong in execution.
The only reliable way to distinguish a correct Next.js route from a wrong one is to execute both. Securie's sandbox does exactly that — for every flagged code shape, it reproduces a working exploit against a forked copy of your app. If the exploit fails (input is sanitized upstream, auth middleware catches it, the endpoint is unreachable in production), the finding is dropped before it reaches your queue. The 6.8 FP score becomes irrelevant because the pattern match is no longer the final answer; the sandbox is.
This is also why Securie's auto-fix PRs are higher quality than pattern-generated suggestions. The fix is tested against the exploit the scanner already reproduced. If the patch does not stop the exploit, the patch is discarded and a different shape is tried. Snyk Fix PRs are pattern-generated — they apply a rule-book transformation to the suspicious code and ship; there is no ground truth to test against.
For a team shipping on Next.js + Supabase + Vercel, the honest recommendation is to start Securie in parallel with Snyk for two weeks, compare the real catches (not the total finding count) on your own repository, and decide. Securie will catch Supabase RLS and BOLA bugs Snyk misses; Snyk will catch cross-language container and IaC issues Securie does not yet handle. The overlap is smaller than marketing suggests. At scale you may keep both. At indie/startup scale, Securie's scope is usually sufficient and the triage burden drops by 70-90%.
Pricing
Snyk Enterprise: $52-98/dev/month. Securie: free during early access. A 10-dev team saves $6K-$12K/year while getting better coverage on AI-built-app bugs.
Migration path
- Install Securie GitHub App alongside Snyk (no need to remove Snyk yet)
- Run both for one week — compare findings
- Most teams find Securie catches the real bugs with 0 false positives; Snyk produces 10-30 false positives per week
- Cancel Snyk once confident; Securie covers the stack-specific bugs
Extended migration playbook
Step 1: Install Securie alongside Snyk; do not remove Snyk yet
What: Add the Securie GitHub App and the Vercel Integration with the same repository access Snyk has. Both tools will run on every pull request.
Why: Running in parallel for a discovery window gives you first-hand comparison data — not vendor marketing claims — about which tool catches your actual bugs. The decision to drop Snyk should be defensible to your CTO and to your board.
Gotchas: Some CI pipelines fail-fast on any security tool check. Configure Securie as a non-blocking check for the first two weeks so you do not block deploys while you evaluate.
Step 2: Run both tools for two weeks on every pull request
What: Let the tools emit findings independently. Do not cross-reference or dismiss duplicates during this window. Record, per finding, which tool surfaced it and whether it was a real bug after engineering review.
Why: The comparison you want is not finding count — Snyk will always win on raw numbers. The comparison is real-bug precision: how many of each tool's findings converted into a merged fix, and how many were noise.
Gotchas: Tempting to dismiss findings as duplicates mid-window; resist. Some 'duplicates' turn out to be subtly different (Snyk catches the pattern; Securie catches the exploit) and the metrics matter.
Step 3: Produce the numbers: real-bug precision and triage hours
What: Tally, per week: (a) total findings each tool produced, (b) findings that became merged fixes, (c) engineer-hours spent triaging. Convert to cost using $150/hour loaded cost and compare to the subscription cost of each tool.
Why: Most teams discover Securie's sandbox pre-filter drops weekly triage from 3-6 hours to near zero, while real-bug precision rises 60-80%. The numbers are the case for switching.
Gotchas: If you have a mature triage-queue culture, the hours number may be lower than the market average — which means the savings from switching are also lower. Be honest about your baseline.
Step 4: Expand Securie coverage before dropping Snyk
What: Enable every Securie specialist that applies to your stack: Supabase RLS if you run Supabase, BOLA if you have REST or tRPC routes, prompt-injection if you use LLMs, secret scanning always. Run a weekend scan over your full repository history, not just the current HEAD.
Why: The case for Securie over Snyk is strongest when Securie's specialists are fully engaged. An underused installation understates the comparison.
Gotchas: Historical scans can surface old findings that are already fixed or dismissed in Snyk. Cross-reference your Snyk dismissal list and carry those decisions into Securie to avoid triaging known-not-real issues.
Step 5: Cancel Snyk after your next renewal window
What: Once you are confident the coverage is equivalent or better for your stack, cancel Snyk before the next auto-renewal. Export the Snyk findings history to SARIF for audit purposes first.
Why: Snyk is an annual contract; mid-term cancellation usually has no refund. Align the cancellation with renewal to avoid dead-weight spend and preserve the audit trail.
Gotchas: If you share Snyk with other teams in your organisation, coordinate the cancellation. If you need to keep Snyk for polyglot coverage (Python, Java, container), retain a Team-tier license rather than cancelling outright.
Pick Securie if…
You ship on Next.js + Supabase + Vercel, your code is AI-generated, you value signal over volume.
Stay with Snyk if…
You have 5+ polyglot languages in production (Python + Go + Rust + Java + etc.), you already have a dedicated security team, and your CI is built around Snyk's dashboard.
Common questions during evaluation
Is Securie a drop-in replacement for Snyk today?
For TypeScript + JavaScript applications on Next.js + Supabase + Vercel, yes — for most teams Securie's scan-verify-fix loop replaces what Snyk Code + Snyk Fix PR were doing, at higher precision. For Python, Go, Rust, Java, container scanning, or IaC on AWS CloudFormation, Snyk is still the stronger choice until Securie's roadmap ships those specialists in Series A.
What happens to my existing Snyk issue history if I switch?
Export the Snyk findings as SARIF before cancelling the account — you will want this for audit continuity. Securie starts with a fresh scan and builds its own issue history going forward. Dismissals in Snyk do not auto-carry; the Securie sandbox re-verifies each finding from scratch, so prior noise is naturally filtered rather than imported.
Does Securie do Software Composition Analysis?
At launch, Securie's SCA scope is malicious-npm-package detection (the Shai-Hulud-style worms from 2025) and fast-CVE-blocking for npm — Securie blocks deploys on npm CVEs within 15 minutes of public disclosure. Full cross-language SCA (PyPI, Maven, NuGet, Go modules, Cargo) is on the Series-A roadmap. If cross-language SCA is your primary use case for Snyk, stay on Snyk for that slice and run Securie for the application layer.
How does the zero-false-positive claim actually work?
Every candidate finding runs through a Firecracker microVM that hosts a shadow clone of your application. Securie attempts to reproduce the exact exploit the pattern suggests — a real SQL injection payload, a real forged JWT, a real bypass of the RLS policy. If the exploit fails, the finding is dropped silently. Only findings with an executed working exploit ship to your pull-request comment. The sandbox artefact (HTTP trace, payload, response) is attached for audit.
Can Securie scan my monorepo's 2 MB generated bundle?
Yes. Securie has no file-size cap. The 1 MB skip Snyk imposes is a consequence of their SAST engine's memory model; Securie's specialists stream-parse rather than load-into-memory, so bundle size does not matter. You can confirm by running a scan against a large file and checking the per-file coverage report in the dashboard.
What if my team relies on Snyk's IDE plugin?
Securie's IDE integrations (Cursor / VS Code / JetBrains) ship in Series A with equivalent shift-left inline feedback. During the current early-access window, Securie runs on every pull request and on every deploy — developers typically push a commit, see the feedback within 30-60 seconds on the PR, and iterate from there. Most teams report the PR-feedback loop is tight enough that the IDE plugin is a nice-to-have rather than a dealbreaker.
Do you support SAML / SSO / SOC 2 requirements for enterprise procurement?
SAML SSO and SCIM are available on the Startup tier ($299/mo) and above from launch. SOC 2 Type II is in progress with report expected Q3 2026; enterprise buyers can review the current interim attestation and the CISA Secure-by-Design pledge during diligence. EU AI Act conformity documentation (model card, risk-management, human-oversight) is published at securie.ai/ai-bill-of-materials and securie.ai/transparency.
Can I self-host Securie inside my own VPC or air-gapped network?
Customer-VPC deployment (Helm + Terraform) and TEE-native (Intel TDX / AMD SEV-SNP) ship in Series A for enterprise and regulated buyers. On-prem air-gapped deployment with offline update bundles is available for sovereign customers. The same specialist fleet runs in every deployment mode; the only difference is whether the model weights and inference happen in your cloud or ours.
Verdict
If you are a polyglot shop with five or more languages in production, a mature security engineering team, and a CI pipeline already built around Snyk's dashboard and SARIF exports, Snyk remains the defensible choice. Switching away from Snyk for its own sake is not a good use of time.
If you are shipping an AI-built application on Next.js + Supabase + Vercel — especially if you are a solo founder, a startup under 20 engineers, or a team that generates most of its code through Cursor, Windsurf, or similar AI editors — Snyk's 6.8 false-positive score and its lack of Supabase and AI-feature specialists are costing you time and coverage in exactly the slice of the market Securie is built for. The two-week parallel evaluation is low-risk, and the numbers almost always come out in favour of the switch for this profile. Install both, measure real-bug precision, decide honestly.