Vulkro vs Snyk

Snyk analyses in its platform. Vulkro analyses on your machine.

Both tools look for security defects before you ship, and both have a CLI you run locally. The difference that no feature release on either side reverses is where the analysis itself happens: Snyk Code sends your source to Snyk and returns findings, while Vulkro reads the tree on your disk and sends nothing anywhere. Everything below follows from that, including the several places where Snyk is the better buy.

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No head-to-head score exists
Source never uploaded
Deterministic engine
Five languages parsed

01 / The short answer

Which one you should be buying

Put at the top because it is what you came for. Neither column is a decoy: if the left one describes you, buy the left one.

Choose Snyk if

Their ground

You want one vendor across dependencies, containers, infrastructure code and application code, in many more languages than the five Vulkro parses.
You want fixes raised for you: automated dependency upgrade pull requests against your repositories, and an assisted code fix inside the tool.
You want the platform around the scanner: organisation-wide dashboards over hundreds of repositories, policies, role-based access, source-control and ticketing integrations, and an account team on the other end.
Sending source to a vendor for analysis is acceptable under your contracts, or your security review has already cleared it.
Your team already runs it. A second scanner has to earn a second triage queue, and often it does not.

Choose Vulkro if

Our ground

Source leaving the machine is a hard no: your contract, your regulator or your own policy says the code stays where it is.
You need the scan to run where there is no route out at all, on a build machine or an air-gapped workstation.
You want the same verdict twice. The engine is deterministic and the build asserts it, which is what makes a gate safe to leave switched on.
You want the path printed with the finding: where the request value entered, the hops it took, and the call that trusted it.
You want the accuracy claim to arrive with its method, its misses and the artifact each figure was read from.

If both columns describe you, the two are not exclusive. Section 06 is the shape teams usually run while they decide.

02 / The architectural difference

A local CLI is not the same as local analysis

Both products ship a command you run in your own terminal. What happens next is the whole comparison.

Snyk is a platform, and the CLI is a surface onto it. For Snyk Code the analysis happens in Snyk rather than on your machine: the CLI sends your source, the engine runs there, and the findings come back and live in your Snyk organisation. Snyk documents that posture carefully. Code is cached only for the cloud provider’s minimum storage period and then removed, what is retained afterwards is the issue location, its id and its explanation rather than the code itself, and Snyk states that customer code is not used to train its engine.

That is a serious data-handling posture, and it is worth saying before anything else. It is also still an upload, and for a set of buyers the upload is the thing that is not allowed, however well it is handled. A defence contractor, a bank’s core systems team and a health provider under a data agreement are not asking how long the code is cached. They are asking whether it leaves, and the answer has to be no.

Snyk has an answer for those teams: Snyk Code Local Engine, a self-hosted deployment of the analysis engine for organisations with a stricter upload policy. It is fair to say it exists, and it is equally fair to say that Snyk’s own documentation marks it deprecated with removal planned in a future release. If it matters to your decision, ask them directly rather than taking either vendor’s word for its future.

Vulkro has no upload path to deprecate, because there is no upload path. The parser, the call graph, the taint engine, the detectors and the CVE bundle are all on your disk, and the findings are written to a local database. Exactly one thing crosses the wire and it is the account layer: an entitlement check carrying at most eight usage fields on a debounced cadence, with no field a file path, a repository name or a finding could travel in. VULKRO_OFFLINE=1 refuses that call too, as a refusal rather than a silent skip: a command that would need the network exits and tells you which call it wanted. Air-gapped machines pair it with a signed, machine-bound licence file instead of signing in.

trust boundaryVULKRO_OFFLINE=1 closes it

Everything the scan needs stays on your machine: the code it reads, the map it builds of how your product fits together, the findings it writes, and the optional local model it can consult without leaving the machine. One line leaves.

Stays on this machine: source code, call graph + taint, findings, account layer, and the local model on 127.0.0.1
One crossing: The entitlement check: eight usage fields at most, on a debounced cadence. No field carries a path, a repository name or a finding.
Never crosses: source code, file paths, file names, repository names, finding contents, finding counts, the hardware fingerprint

Vulkro's trust boundary. The scan pipeline never touches the wire, and the one line that does carries an entitlement check rather than your code.

03 / Measured, or not measured

There is no head-to-head number on this page

Not a soft one, not an indicative one, not one with an asterisk. No scored run of Snyk against our corpus exists, so nothing comparative can honestly be printed here.

Our benchmark harness can add a tool, but Snyk is not in the committed scorecard. Running it would need an authenticated account, the harness skips it when unauthenticated, and publishing scored results for a commercial tool raises a terms question we have not cleared. So the run has not happened, and a number that has not been measured is not a number we will print.

The comparison in the rest of this page is therefore architecture and capability: where the analysis runs, what each tool is built to find, and what each one does not do. Those are checkable against both vendors’ documentation, which is more than a fabricated score would ever be.

What we can say: Vulkro’s own scored result exists and is published with its method: precision 0.78, recall 0.57, F1 0.66 on our corpus of real projects with independently documented bugs, at the confidence floor we recommend in CI, with 36 of the 83 catalogued bugs missed and still in the corpus. It has one column. A single column is a result, not a comparison.
What we cannot say: Anything at all about Snyk’s precision, recall or false-positive rate, and anything of the form "more accurate than". We have not run their product against our corpus and we have not run ours against theirs. Any site that shows you both columns without saying which binary, which corpus and which date produced them is showing you a graphic rather than a measurement.

Artifactbench/comparison/scorecard-high.md · vulkro 0.18.0 · measured 2026-07-18 · Tier 1 corpus, min-confidence high, match window file + line plus or minus 5

The method, the scoring rules and the list of what the scanner misses are on /proof and in the benchmark documentation. The engine is closed; the method and the misses are not.

04 / Where Snyk wins

The things they are simply better at

Written without a qualifier on the end of each sentence. A comparison page that cannot concede is an advertisement, and you would be right to discount the rest of it.

Dependency intelligence, not just matching

Snyk maintains its own curated vulnerability database with a research team behind it, and the advisory detail, exploit maturity and fix guidance that come with it are richer than matching a package against a public feed. Vulkro matches against a checksummed bundle on your disk built from public sources. For triage depth on a dependency finding, theirs is the better artifact.

Fixes raised for you

Automated upgrade pull requests against your repositories, and an assisted code fix in the product. Vulkro applies deterministic fix templates locally and opens nothing on your behalf. If what you want is a queue of ready-to-merge upgrades, that is a real feature and Vulkro does not have it.

Language breadth

Snyk Code reads far more languages than the five Vulkro parses. If your estate is C#, Ruby, PHP, Swift or Kotlin, Vulkro reads none of it: those files are counted in the inventory and skipped. That is not a close call, and no amount of depth on five languages answers it.

Containers, images and infrastructure at product scale

Container scanning with base image guidance, and an infrastructure-as-code product line beside it. Vulkro runs a configuration and image pass in the same scan, but it is one pass in a code scanner rather than a product line, and the breadth is not comparable.

The platform, and the paperwork

Portfolio reporting across an estate, policy and role-based access, integrations most enterprises already have wired, and a vendor relationship with the contractual coverage a procurement process asks for. Vulkro is a scanner with a local console, not a platform to roll out.

Already being there

A team standardised on Snyk has its pipelines, its exceptions and its muscle memory built around it. Switching costs are real, and the honest question is not which tool is better in the abstract but whether the difference below is worth the move for you.

05 / Coverage

Capability against capability, with the gaps left in

Both columns have holes. Ours are the language list and everything a platform does around a scanner; theirs is the boundary the first two rows describe.

Capability comparison between Vulkro and Snyk: where analysis runs, what is uploaded, offline operation, language coverage, dataflow depth, dependency matching, fixes, stability and output formats.
Capability	Vulkro	Snyk
Where the analysis runs	On your machine, every time	In Snyk for Snyk Code by default. A self-hosted engine is documented for teams that cannot upload
Source sent to the vendor	Never. No request body has a field a file could travel in	Yes for Snyk Code by default, cached for the provider minimum then removed, and Snyk states it is not used to train the engine
Runs with no network at all	Yes. VULKRO_OFFLINE=1 refuses every outbound call, paired with a signed machine-bound licence file	Not the documented path for the platform products
Languages read as code	Python, JavaScript, TypeScript, Go, Java. Everything else is counted and skipped	Many more. Check their list against your stack
Dataflow across file boundaries	Python, JavaScript, TypeScript and Go up to four hops. Java taint is same-file only	Interfile analysis is documented. We have not measured its depth and make no claim about it
Dependency CVE matching	Offline, against a checksummed bundle on disk, five manifest formats parsed	Against their own curated database, broader ecosystem coverage
Reachability on dependency findings	From the call graph. Unreachable findings are downgraded to informational and kept, never dropped	Offered on their platform. Not measured by us
Automated fix pull requests	No. Deterministic fix templates applied locally	Yes
Run-to-run stability	Deterministic, asserted by tests in the build: same binary, same tree, same settings, same findings in the same order	Snyk describes Snyk Code as AI-based. We have not measured its run-to-run stability and make no claim either way
SARIF for GitHub Code Scanning	Yes, one of the output formats the CLI emits	Yes

Capability rows, not measurements: nothing in this table is scored, and no cell is a benchmark result. The Vulkro column is read from the scanner and its own documentation. The Snyk column is read from Snyk’s published product documentation (2026-08-15) and describes their product as documented rather than as measured by us. Where a row says we have not measured something, that is the whole of what we know.

How deep the analysis goes per language →

The dataflow row is the one worth reading twice, in both directions. Vulkro follows a tainted value across file boundaries in Python, JavaScript, TypeScript and Go for up to four hops, and Java taint does not cross a file boundary at all, so a Java result set is narrower than a Python or Go one on the same codebase. Snyk documents interfile analysis of its own; we have not measured how far it goes and this page does not guess.

Salesforce sits outside this table entirely. Apex, Lightning components, Flow and org metadata are read by Vulkro for Salesforce, the same review pointed at a Salesforce build, and comparing it to a general code platform on that ground would be the like-for-like mistake this page is trying to avoid.

vulkro explain VULK-10424 hops

Dataflow pathSQL injection in order lookupVULK-1042

01checkout.py:214request handlersource
order_id read from request.args, no type or format check
02services/orders.py:88helper
passed through lookup_order(order_id) unchanged
03db/query_builder.py:41query builder
concatenated into the WHERE clause with an f-string
04db/session.py:57sinksink
cursor.execute(sql) runs the assembled statement

4 hops resolved. No sanitiser between the source and the sink.

What Vulkro hands back with a finding: the resolved hops from the request value to the call that trusted it, built on your machine and printed with the report.

06 / Migration, or running both

What switching actually costs

There is no rule-import shortcut here, and pretending otherwise would waste a week of yours. The realistic path is to run both for a cycle and decide on your own findings.

Start with what does not exist. There is no Snyk rule importer in either Vulkro edition: we know of no portable export of Snyk Code’s rule set to read, so there is nothing to convert. Rule import does exist, for the Semgrep and Checkmarx rule formats, and it ships in Vulkro for Salesforce rather than in the core scanner. An earlier version of this page implied that migration path was available in core. It was not, and it is not.

What does carry across is the report format. Both tools emit SARIF, GitHub Code Scanning ingests either file, and nothing stops the two running in the same job.

01
Leave Snyk exactly where it is
Nothing about adding a second scanner requires turning the first one off, and turning it off before you have your own data is how an evaluation becomes a leap of faith.
02
Add Vulkro to the same pipeline
Both tools emit SARIF and GitHub Code Scanning ingests either file. Your first CLI sign-in starts a 14-day trial of the full product, with no card, and every scan runs on the runner itself.
03
Diff the two reports for one release cycle
Count what only one tool found, and read a sample of both. The question is not which report is longer: it is which findings your team acted on and how much of each report they threw away.
04
Decide by the end of the cycle
Two scanners means two triage queues, and a queue nobody owns goes stale. Either the second tool earned its place on your own numbers or it did not, and either answer is a good outcome.

# application scan on the runner itself
$ vulkro scan . --format sarif > vulkro.sarif

# your existing scanner, unchanged
$ snyk code test --sarif-file-output=snyk.sarif

# upload both to Code Scanning, then diff what only one of them found

Two SARIF files from one pipeline run. Vulkro analyses on the runner; the other command follows whatever posture your Snyk organisation is configured for.

One warning worth having in advance: the two reports will overlap most on dependency findings and least on application logic, so give the dependency class a single owner before you start or you will triage the same package twice.

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