Krita finds the handful of risks that actually matter across everything you build, everything you run, and everything you have to prove — without your source code ever leaving your infrastructure.
16 languages · 13 frameworks · 3 clouds · 6 IaC · 7 package managers
Catch it before it ships. Defend it while it runs. Prove it whenever you are asked. Each is sold on its own. Together they close the loop.
Is it safe to ship?
Review everything you build before it reaches production — code, dependencies, secrets, infrastructure, cloud, network — and get back the short list that is genuinely exploitable.
Read more →What is happening right now?
Watch what is actually running, separate the real attack from the noise, and respond inside limits you set in advance.
Read more →Can you prove it?
Governance, risk and compliance that maintains itself — evidence collected continuously, controls mapped automatically, audit packages ready when the auditor is.
Read more →Three offerings, one engine underneath. Adopting the second costs you almost nothing, because all of this is already shared.
Deploy inside your own infrastructure, air-gapped if you need it. Analysis happens on your side of the boundary and only findings cross it. For a regulated buyer this is the entire conversation.
Point Krita at any major provider or a model on your own hardware. Credentials are encrypted and held separately per configuration.
Anything the model works out about your codebase arrives as a candidate, not a fact. It takes effect when someone accepts it.
Every route under /admin must pass the tenant check before reading orders.
CANDIDATERefunds above the approval limit require a second reviewer.
CANDIDATESession tokens must never reach the log writer.
CONFIRMEDWhere Krita can act, it selects from a catalogue of actions you approved in advance and is structurally unable to compose its own. The level of authority is enforced at execution.
A finding whose code is unchanged since you last reviewed it comes back marked as the same finding, not as a new one. Repeat work stops arriving as fresh alarms.
What matters becomes a task with an owner and a clock, pushed into the tracker your team already uses. Nothing waits for someone to notice a dashboard.
Whose network does it run in?
Whose model reads your code?
Can you leave with your data?
The industry clock starts the day a flaw becomes public and runs for the better part of a year. Every manual-review figure is independent research, quoted from the report named beside it. The Krita figures are the clock we set — a service level the platform enforces, not a benchmark we ran.
The whole Krita ladder ends at seven days — the point at which the industry one has barely started.
Only 38% of known-exploited vulnerabilities were ever fully remediated. — Verizon DBIR 2025
Service levels the platform enforces on every finding it raises — targets, not measured outcomes. Krita publishes no timing benchmark of its own.
Left: independent research, sourced per row. Right: service levels the platform enforces. Krita publishes no timing benchmark of its own.
Buying another scanner is not security. It is the appearance of security, paid for with your team's entire week. Every figure on this page is independent research — none of it is our own measurement.
A scanner for code, another for dependencies, another for secrets, another for cloud, another for containers. Each honest about its own narrow surface. None of them talking to the others.
Every tool reports everything it can find, because a missed finding is a lawsuit and a false one is only your problem. So the pile grows, and the signal inside it gets harder to reach every quarter.
Which of these can actually be reached and exploited? Nothing in the stack answers that, so a person does — badly, under time pressure, on a Friday. That is where breaches come from.
of developers now use or plan to use AI coding tools
Stack Overflow Developer Survey, 2025
of AI-generated code introduced an OWASP Top 10 flaw
Veracode GenAI Code Security Report, 2025
of breaches now start with vulnerability exploitation — the #1 entry point
Verizon Data Breach Investigations Report, 2026
average cost of a US data breach
IBM Cost of a Data Breach, 2025
Most security budget buys the first one. Only the second changes an outcome.
| Point scanners | Aggregation platforms | Krita | |
|---|---|---|---|
| Core question | What patterns match? | How do I see it all in one place? | Which of these is actually real? |
| What you get back | More findings | The same findings, sorted | A short list you can act on |
| How it prioritises | A severity label | Severity plus asset context | Whether an attacker can reach it |
| Cross-file reasoning | No, matches file by file | No, inherits its inputs | Yes, reasons over the whole repository |
| Where it runs | Usually a vendor cloud | A vendor cloud | Your infrastructure, air-gapped if needed |
| Which model reads your code | Not applicable, or fixed | Fixed by the vendor | Whichever you choose, including your own |
| Scope | One surface | Many surfaces, one purpose | What you ship, what you run, what you prove |
| What the team ends up with | Alert fatigue | Organised alert fatigue | Fewer decisions, made with evidence |
These are categories of approach, not specific products, and no vendor is scored or named. Each row is a question a buyer actually asks during evaluation; the answers in the first two columns describe how that class of tool works by design, not how any one implementation performs. The Krita column describes shipped behaviour only — anything still being built carries its own marker elsewhere on this page. We publish no competitive benchmark, because we have not run one.
Four lines. What you carry today, what replaces it, and the size of the difference.
Measured against what the function already costs: about $2–2.5M a year at mid-market, past $12M at enterprise.
Ranges, not a quote. They describe what the levers are worth against your own baseline. We publish no customer savings figure, because we have not measured one.
worldwide security spend, 2026
Gartner
application security, growing 11–19% a year
MarketsandMarkets · Grand View
growth in the testing segment we start in
MarketsandMarkets
professional developers worldwide
SlashData, 2025
Point Krita at a repository, a cloud account, or a network range. Instead of a thousand findings ranked by severity, you get the few that an attacker could actually reach — each one with the exploit path, the fix, and a task already waiting in your tracker.
Injection, authentication bypass, unsafe deserialization, path traversal, race conditions and more — found by reasoning across the whole repository, not by matching patterns file by file.
Broken object-level authorization, privilege escalation, missing access control on a route nobody remembered. The flaws that live between files and that pattern matchers structurally cannot see.
Your full direct and transitive inventory, with licence and vulnerability correlation, and a judgement about whether the vulnerable path is reachable from your code at all.
Credentials committed to history or shipped to the browser, and infrastructure definitions that would deploy something exposed.
Misconfiguration and compliance drift across your accounts, mapped to the frameworks you actually report against.
What is reachable from outside, what is listening, and what is running a version that matters.
Detection that tells you what an attacker is doing rather than which rule fired, and response that is bounded by a catalogue of actions you approved in advance. Krita never invents an action it was not given.
Continuous ingest from your cloud and infrastructure telemetry, correlated into incidents rather than dumped as alerts.
Each incident arrives with a plain-language account of what the attacker appears to be doing and a confidence score you can inspect — never one opaque number.
Block an address, revoke a session, isolate an instance, disable a key, or simply alert. A fixed set of approved actions, chosen within bounds and executed by code.
Four levels of authority, starting at alert-only. Dry-run any response before you trust it. Every reversible action records its own undo. Resources you tag as protected are never touched automatically.
Four events, one story: an unfamiliar session gained administrator rights, minted a durable key, then tried to remove the record.
One clock for findings and incidents alike. You set the targets.
Governance, risk and compliance stops being a two-month scramble before an audit and becomes a state you are continuously in. Including the new regime written specifically for AI.
Policy lifecycle, control mapping, and defined roles — plus governance of AI itself: which models are approved, what authority they hold, and a full ledger of every decision they made.
A risk register with quantified exposure rather than a colour-coded grid, fed by what Review and Sentinel actually found.
SOC 2, ISO 27001, HIPAA, PCI DSS, NIST, GDPR, DORA and more — with controls mapped and gaps identified continuously, not the week before the auditor arrives.
The EU AI Act, ISO/IEC 42001 and the NIST AI Risk Management Framework. New obligations with real deadlines and no incumbent answer yet.
Collected automatically from your cloud, identity, source control and workplace systems. Written once, hash-chained, held under legal hold, and retrievable exactly as it stood on any past date.
No roadmap item is dressed up as a shipped feature. Read down an offering, or across a row.
Findings arrive where your engineers already are. No new dashboard to live in, no workflow to relearn.
Dimmed tiles are in development. Nothing here is listed as connected until it is.
Map a control once. Answer every framework that asks for it. Findings arrive already tagged, so the evidence is a query rather than a project.
Every finding is tagged against these as it is created.
Cloud posture is scored against these directly.
Controls map once and report to all of them.
New obligations with real deadlines and no incumbent answer yet.
Inventory and provenance formats we read and emit.
Coverage depth varies by framework. Marked available where the mapping ships today, in development where it is being built, on the roadmap where it is not started.
CWE, OWASP, CVSS, NIST, PCI DSS — auto-tagged on every finding. Role-based access, encryption, audit logging, and 43 compliance frameworks built in.
user_input flows from the HTTP request body directly into cursor.execute(query) without parameterisation or escaping. An attacker can exfiltrate the full database with a single crafted request.
We would rather show you the roadmap than imply it is already finished. Everything marked available today is running now.
Code, business logic, dependencies, secrets, infrastructure and cloud posture are available today. Network and exposure review, and dynamic testing against a running application, are in development.
Detection and correlation first, at alert-only authority. Graduated response, then multi-cloud coverage. Defence of AI systems themselves — model endpoints, prompt boundaries, agent behaviour — follows.
Core platform, evidence collection and the first framework packs are being built now. The EU AI Act and ISO 42001 packs come next, alongside the AI bill of materials that becomes mandatory in the EU in 2027.
Supply-chain risk does not end by catching a bad package after it is installed. It ends when the safe component is the easy one to reach for: checked before anyone pulls it, hosted for you, and kept alive when a critical dependency is abandoned.
A model specialised for security reasoning rather than general-purpose intelligence pointed at a security problem. Planned, not shipped — and Krita will always run on the provider you choose regardless.
No. Krita deploys inside your own environment, air-gapped if you need it. Analysis happens where your code already lives and only findings cross the boundary. If you would rather we host the control plane, that option exists too — but the choice is yours, and the self-hosted path is the one we designed for first.
The deepest analysis — whole-repository reasoning and cross-file business logic — currently covers TypeScript, JavaScript and Python, with more languages in development. Dependency, secret, infrastructure and cloud review are language-agnostic and work across your whole estate today.
Whichever you choose. Point Krita at a major provider or at a model running on your own hardware. Credentials are encrypted and held separately per configuration, and changing provider changes it everywhere at once. A security-tuned model of our own is on the roadmap; it will always be optional.
AI Review is running now: code, business logic, dependencies, secrets, infrastructure and cloud posture. AI Sentinel and AI GRC are in active development. We mark build state on every capability on this page rather than implying the roadmap is finished.
You probably do not need more findings. Independent research puts the share of static-analysis warnings that are security-relevant at 8 to 30 percent, and the share of dependency vulnerabilities actually reachable in your code below 10 percent. Krita's job is deciding which of your existing noise is real, then extending the same judgement to what runs and what you must prove.
Findings become tracked work in the tracker you already use, on a service-level clock you set. Scans trigger from your existing CI. Nothing asks your engineers to live in another dashboard.
By team for smaller organisations and by volume for larger ones, with self-hosted deployment available on every tier. We are onboarding design partners now, so pricing is a conversation rather than a page.
We are onboarding a small number of design partners who will run Krita against their own production code, in their own environment, and tell us the truth about what it finds.
Self-hosted · your model · your code never leaves your infrastructure