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Lakera alternatives

9 tools we tested head to head against Lakera, ranked — and what each one actually does differently.

last reviewed 29 jul 2026 · from our best 10 ai red-teaming tools ·list curated by Onur Ozcanxin

first — what you'd be leaving

Lakera ranks #5 of 10 in our ai red-teaming tools testing. the only commercial vendor here you can start using without talking to anyone..

76/100

genuinely lower friction than anything else commercial here — with the red-teaming service sold separately from the product you can actually sign up for.

why people look for an alternative
  • pricing page shows no figures for any paid tier
  • red-teaming service is separate from the self-serve product
  • no first-party compliance-framework mapping found
  • red-team methodology and benchmarks not detailed

stay with Lakera if only commercial vendor here with free self-serve signup is the thing you care about most — nothing below beats it on that.

the short version
best alternativePromptfooany team that wants to start testing this week without a procurement conversation.88/100
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  1. 1

    Promptfoo

    #1 in ai red-teaming tools · mit-licensed, free for ten thousand probes a month, and the only free tool here that tests agent tool access.

    88/100

    verdictthe most capable thing here you can run today, and the only free option that understands your application rather than just your model.

    Promptfoo vs Lakera
     LakeraPromptfoo
    pricefree tier availablefree
    free tieryesyes
    pricingfree tier; paid unpublishedfree tier; enterprise quote-only
    self-serveyes, for guardrailsyes
    testsapplication layer, runtimemodel, application and agent tools
    licenceproprietarymit
    compliance mappingowasp, via third partyclaimed, not itemised

    switch forany team that wants to start testing this week without a procurement conversation.

    pros
    • +mit licence with a real 10,000-probe monthly free tier
    • +50+ named vulnerability types including tool discovery
    • +tests the application and agent layer, not just the model
    • +self-serve install with no sales contact
    cons
    • enterprise and on-premise pricing is quote-only
    • compliance mapping claimed but not itemised
    • supporting research hosted separately and unverified
    • free tier cap will bind on any serious programme
  2. 2

    Garak

    #2 in ai red-teaming tools · apache 2.0 from nvidia, twenty-plus probe modules, and a peer-reviewed paper behind it.

    85/100

    verdictthe most rigorous free option and the narrowest in scope — it tests a model beautifully and knows nothing about the application around it.

    Garak vs Lakera
     LakeraGarak
    pricefree tier availablefree
    free tieryesyes
    pricingfree tier; paid unpublishedfree
    self-serveyes, for guardrailsyes
    testsapplication layer, runtimemodel only
    licenceproprietaryapache 2.0
    compliance mappingowasp, via third partynone

    switch forscanning a specific model for known failure modes, with something citable to show for it.

    pros
    • +apache 2.0 with no paid tier or account required
    • +20+ probe modules covering a wide failure taxonomy
    • +peer-reviewed arxiv preprint behind the methodology
    • +actively maintained under nvidia's organisation
    cons
    • model-level only — no application or agent testing
    • cannot assess agentic tool abuse at all
    • no compliance-framework mapping out of the box
    • command-line only, no reporting layer
  3. 3

    Adversa AI

    #3 in ai red-teaming tools · the most itemised attack taxonomy and the only vendor naming five compliance frameworks — behind a demo form.

    82/100

    verdictthe most concrete commercial vendor here on both what it tests and what it maps to — and you cannot find out what any of it costs.

    Adversa AI vs Lakera
     LakeraAdversa AI
    pricefree tier availablenot published
    free tieryesno
    pricingfree tier; paid unpublishednone published
    self-serveyes, for guardrailsno
    testsapplication layer, runtimemodel, agent and application
    licenceproprietaryproprietary
    compliance mappingowasp, via third partyfive named frameworks

    switch forteams securing ai coding agents, where its current flagship is aimed.

    pros
    • +most itemised attack taxonomy across model, agent and application
    • +maps to owasp asi, nist ai rmf, eu ai act, cosai and mitre
    • +publishes named vulnerability research with real findings
    • +continuous runtime testing rather than point-in-time only
    cons
    • no pricing or self-serve path whatsoever
    • flagship narrowed to ai coding-agent runtime security
    • general red-teaming is now a companion service
    • no free tier to evaluate
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  4. 4

    PyRIT

    #4 in ai red-teaming tools · microsoft's mit-licensed red-team framework — build your own attacks, and the repository just moved.

    79/100

    verdictthe most flexible free option and the one that gives you least out of the box — it's a toolkit, not a scan.

    PyRIT vs Lakera
     LakeraPyRIT
    pricefree tier availablefree
    free tieryesyes
    pricingfree tier; paid unpublishedfree
    self-serveyes, for guardrailsyes
    testsapplication layer, runtimewhatever you build
    licenceproprietarymit
    compliance mappingowasp, via third partynone

    switch forsecurity teams with engineering capacity who want to encode their own threat model.

    pros
    • +mit licence, maintained by microsoft
    • +fully flexible — encode your own threat model
    • +no account, no sales contact, no cost
    • +built by and for practising red teams
    cons
    • no out-of-box probe catalogue — significant setup effort
    • repository moved; the old azure location is archived
    • no published compliance-framework mapping
    • model-versus-application scoping is left to you
  5. 5

    HiddenLayer

    #6 in ai red-teaming tools · fifty disclosed cves and thirty patents, across the broadest claimed scope here.

    73/100

    verdictthe most credible research track record among the commercial vendors, attached to product claims too broad to verify without a sales call.

    HiddenLayer vs Lakera
     LakeraHiddenLayer
    pricefree tier availablenot published
    free tieryesno
    pricingfree tier; paid unpublishednone published
    self-serveyes, for guardrailsno
    testsapplication layer, runtimesupply chain, application, runtime
    licenceproprietaryproprietary
    compliance mappingowasp, via third partynone found

    switch forenterprises wanting model supply-chain scanning alongside runtime protection from one vendor.

    pros
    • +50+ disclosed cves and 30+ patents
    • +model supply-chain scanning, rare in this category
    • +spans discovery, supply chain, simulation and runtime
    • +publishes an annual threat landscape report
    cons
    • no pricing published at all
    • red-teaming methodology page returns 404
    • attack coverage described broadly rather than itemised
    • no compliance-framework mapping found
  6. 6

    SPLX

    #7 in ai red-teaming tools · publishes red-team findings against named frontier models, and open-sourced the agent-mapping half of its product.

    71/100

    verdictthe most useful free artefact of any commercial vendor here, alongside published attacks on models people actually use.

    SPLX vs Lakera
     LakeraSPLX
    pricefree tier availablenot published
    free tieryesyes
    pricingfree tier; paid unpublishednone published
    self-serveyes, for guardrailsagentic radar only
    testsapplication layer, runtimemodel, application and agent
    licenceproprietaryopen component, closed platform
    compliance mappingowasp, via third partygeneric, unnamed

    switch forteams wanting to map an agent's tool graph for free before deciding whether to buy the platform.

    pros
    • +published red-team reports on gpt-5, claude opus 4.1 and grok 4
    • +agentic radar open-sourced for agent and tool mapping
    • +covers model, application and agent layers
    • +agentic red-teaming whitepaper published
    cons
    • core platform pricing entirely undisclosed
    • no named compliance framework
    • agentic radar licence not verified
    • rebranded from splxai — older references are stale
  7. 7

    Mindgard

    #8 in ai red-teaming tools · a hundred disclosures against systems you've heard of, from a lab with a decade of university research behind it.

    68/100

    verdictthe disclosure record is the argument, and it's a decent one — everything else about the commercial offer is behind a form.

    Mindgard vs Lakera
     LakeraMindgard
    pricefree tier availablenot published
    free tieryesno
    pricingfree tier; paid unpublishednone published
    self-serveyes, for guardrailsno
    testsapplication layer, runtimemodel, application and agent
    licenceproprietaryproprietary
    compliance mappingowasp, via third partynone — soc 2 only

    switch forbuyers who weight demonstrated findings against real systems over published methodology.

    pros
    • +100+ public disclosures naming real frontier systems
    • +over a decade of university ai-security research heritage
    • +covers model, application and agentic workflows
    • +soc 2 type ii certified
    cons
    • pricing page contains no pricing
    • no self-serve path at all
    • soc 2 is general infosec, not ai-framework mapping
    • no detailed public methodology document found
  8. 8

    Gray Swan AI

    #9 in ai red-teaming tools · runs a public attack competition that finds real exploits — and describes its actual product in adjectives.

    65/100

    verdicta genuinely novel model for finding novel attacks, wrapped around a commercial offer you cannot evaluate from outside.

    Gray Swan AI vs Lakera
     LakeraGray Swan AI
    pricefree tier availablenot published
    free tieryesyes
    pricingfree tier; paid unpublishednone published
    self-serveyes, for guardrailsarena only
    testsapplication layer, runtimemodel and agent, scope vague
    licenceproprietaryproprietary
    compliance mappingowasp, via third partynone named

    switch forfrontier labs commissioning pre-release adversarial evaluation, and researchers wanting to compete.

    pros
    • +crowdsourced arena competition genuinely surfaces novel attacks
    • +publishes system cards for frontier model evaluations
    • +names deepmind, openai, anthropic and meta as partners
    • +arena is openly accessible to researchers
    cons
    • commercial products entirely sales-gated with no pricing
    • testing scope described in marketing language, not categories
    • no named compliance framework
    • most arena findings are unpublished
  9. 9

    Repello AI

    #10 in ai red-teaming tools · a free scan you can run without a sales call, behind numbers nothing supports.

    60/100

    verdictthe free entry point is real and useful; the headline capability claims have no methodology, paper or benchmark behind them that we could find.

    Repello AI vs Lakera
     LakeraRepello AI
    pricefree tier availablefree scan available
    free tieryesyes
    pricingfree tier; paid unpublishedfree scan; platform unpublished
    self-serveyes, for guardrailsyes, for recon
    testsapplication layer, runtimeapplication and agent, black-box
    licenceproprietaryproprietary
    compliance mappingowasp, via third partyclaimed, not itemised

    switch fora no-commitment first look at how an application responds to adversarial input.

    pros
    • +free self-serve recon scan with no sales call
    • +black-box and model-agnostic across major providers
    • +covers agent autonomy and tool abuse explicitly
    • +claims multimodal and 100+ language coverage
    cons
    • 270+ vulnerability types claim has no supporting evidence
    • 15m attack patterns claim likewise unsupported
    • about and company pages return 404
    • full platform pricing unpublished

how these were compared

every tool on this page went through the same test as Lakera — same tasks, same order, scored the same way. the comparison tables are the figures from that testing, not vendor spec sheets.

the ai red-teaming tools test in full →
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