What is the best free tool to pentest an API?

OWASP ZAP is the best free starting point for most teams. It covers proxying, passive and active scanning, and already supports serious work on REST and GraphQL APIs. Add Postman to replay your test cases and Kiterunner to discover routes. With no budget at all, start with ZAP, then add a simple replay tool to save time when you build proof.

Burp Suite or OWASP ZAP for testing a REST API?

Burp Suite is usually more comfortable for deep manual analysis and fast request manipulation. ZAP holds up very well when the budget is tight or when you want more open automation. For a highly sensitive REST API, pick Burp when speed of analysis matters and ZAP when standardisation matters more. In practice, many teams end up using both, for different situations.

How do you test a GraphQL API effectively?

Start with introspection, query depth, query complexity, field-level authorization and error verbosity. Then replay queries with different identities to see whether objects and nested objects stay visible. GraphQL tests often fail on query overload and on sensitive fields exposed too broadly. Check the field, then the parent type, then the nested relations, because that is where access control usually breaks.

Can you pentest an API with only an OpenAPI spec?

For a large share of the technical tests, yes. Schemathesis, 42Crunch and other schema-based tools use OpenAPI to generate valid and invalid cases. But a spec does not replace manual validation of sensitive flows or the discovery of undocumented endpoints. An up-to-date spec speeds up the work; an outdated one gives you a false sense of coverage.

Which tools automate API pentesting in CI/CD?

Schemathesis, StackHawk, Nuclei and 42Crunch are the most useful options, depending on your maturity. The right choice depends on your spec, your deployment speed and how much noise you can tolerate. If your pipeline changes often, keep checks targeted rather than running one broad scan. The goal is not to have a CI scan, it is to stop changes to the attack surface that nobody reviewed.

Best API penetration testing tools: how to choose in 2026

The best tools to pentest an API are not the same depending on whether you need to discover a hidden surface, replay requests, fuzz an OpenAPI schema or validate object-level authorization. In practice, teams combine Burp Suite or OWASP ZAP for manual work, Schemathesis or 42Crunch for schema-driven testing, then Nuclei, Kiterunner, Postman, mitmproxy or StackHawk depending on how much automation they want. The question is rarely "which single tool is best". It is how much of the real risk your stack actually covers.

Key takeaways

No single tool properly covers discovery, authentication, rate limiting, BOLA/IDOR, injection and business logic.
The OWASP API Security Top 10 remains the best grid to prioritise, with API1 Broken Object Level Authorization and API3 Broken Object Property Level Authorization at the top.
Burp Suite and OWASP ZAP remain the base for manual testing, while Schemathesis, 42Crunch and StackHawk mostly automate tests from a spec or a pipeline.
The right choice depends first on your type of API, the quality of your OpenAPI specs and your ability to fix fast, not on how popular the tool is.

The best tools depend on the API risk you need to cover

What a good tool really covers

A good tool covers a useful surface, not a marketing promise. For a serious API pentest, I would start from this shortlist: Burp Suite, OWASP ZAP, Postman, Insomnia, Nuclei, Schemathesis, StackHawk, Kiterunner, mitmproxy, SoapUI and 42Crunch. Each one has a strong zone, and none replaces the others across the whole spectrum. A banking API, an e-commerce back office and a B2B platform do not need the same thing: the critical route changes, the business logic changes, and so do the exploitable flaws.

The OWASP API Security Top 10 (2023) is the modern reading grid. API1 Broken Object Level Authorization and API3 Broken Object Property Level Authorization remain among the most rewarding risks to test, because they break access to objects or to their fields without any visible noise on the client side.

Why business logic changes the ranking

With zero budget, take OWASP ZAP, Postman, Kiterunner and some mitmproxy. With a mature AppSec team, Burp Suite, Schemathesis and 42Crunch give much finer coverage. If you are a product team that wants to automate without losing control, StackHawk, Nuclei and a good OpenAPI spec are a sound compromise. The real sorting criterion is the type of risk to cover, not the logo. A 12-person team shipping twice a day does not have the same need as a group running a quarterly audit.

Map the API before you attack it

Discovery from specs and traffic

The first useful step is the inventory. Forgotten endpoints, shadow versions, exposed test routes and less visible GraphQL or gRPC services often yield more value than yet another full scan. Your real entry points are OpenAPI, Swagger, Postman collections and, for GraphQL, introspection when it is still enabled. On a real target, half the work is often understanding what still exists in production while the team believes the old version was cleaned up.

Kiterunner helps discover undocumented routes and parameters. Postman lets you replay concrete cases cleanly. mitmproxy is handy to observe real traffic and spot the gap between what the documentation promises and what the API actually does. We have seen an API expose /v1 and /internal side by side: the internal version was never meant to be reachable from outside, and it changed the whole test plan. That is exactly the kind of surprise a pure scanner misses.

The most expensive blind spots are rarely the most visible. An API with clean documentation can still expose old routes, pre-production environments or unexpected methods. Mapping early tells you where to test authorization, where to test pagination, and where to look for hidden parameters before you launch the noisier tools. I would rather spend twenty minutes on the route map than two hours rerunning a scan that only sees half the ground.

For manual exploration, Burp and ZAP stay central

When to prefer Burp Suite

Burp Suite remains the default choice when manual testing has to go fast and deep. Its proxy, Repeater and extensions make fine-grained manipulation easy: replaying a JWT, changing an object ID, testing cache headers or bypassing client-side validation. On sensitive flows, that speed matters as much as coverage. When you need to understand a call chain in fifteen minutes, Burp usually gives the best ratio between reading, acting and producing exploitable proof.

OWASP ZAP does almost everything many teams need, with an excellent cost-to-control ratio. Its passive scan is easy to integrate, its active scan is good enough to find repeatable errors, and its openness appeals when you want to write scripts or industrialise checks without lock-in. Burp is often faster for advanced analysis; ZAP is more comfortable on a tight budget and for open automation. For a mid-sized company that has to keep costs under control, it is often the right balance.

When ZAP is enough, and even excels

ZAP is perfectly adequate if your goal is to replay flows, check error responses, test redirects, manipulate parameters or run regular checks on stable endpoints. It also shines when a team wants to share tests without buying a seat per analyst. But these tools mostly find technical defects. Business logic flaws need scenarios designed by the tester, not just a well-tuned proxy. A billing API can be clean at the HTTP level and still allow a sequence of actions that doubles a credit note.

The best automated API tools target the schema

Spec-driven fuzzing

Schema-based testing starts from OpenAPI to generate valid, invalid and edge cases. Schemathesis is very strong at this, 42Crunch pushes spec conformance and analysis, StackHawk integrates well into a CI/CD chain, and Nuclei is useful when you want fast templates against known targets. They complement each other more than they replace each other.

GraphQL deserves its own attention. According to Apollo GraphQL's API orchestration research, 70% of organisations now use GraphQL. That is why tests on query depth, complexity and field-level authorization have moved from nice-to-have to baseline work.

The real gain is simple: you find defects that manual testing misses through fatigue or lack of time. An unexpected enum, a bypassed required field, a 500 on a malformed type or unbounded pagination surface quickly once case generation becomes systematic. Provided, of course, that the spec is reliable and current. If the spec lies, the tool lies to you too, only faster.

CI/CD and continuous testing without noise

In a pipeline, the goal is not to break everything on every commit. It is to catch new deviations, access regressions and exposed surfaces that change without review. GitLab's 2023 DevSecOps survey found that respondents practising CI/CD were twice as likely to deploy to production multiple times per day. At that pace, a check that runs on every release has to be targeted, readable and fast to triage.

A CI check catches regressions; it does not replace a pentest. Between audits, Fleuret runs agentic pentests on REST and GraphQL APIs and returns results in hours, with a replayable proof of concept for every finding and a retest once the fix ships. For a broader view of how to keep that rhythm, see our guide to continuous API security assessment.

Authentication and authorization need different tests

OAuth 2.0, JWT and API keys

An authenticated API is not a secure API. You need to test OAuth 2.0, OpenID Connect, JWT, mTLS, API keys and rate limiting as real controls, not as boxes to tick. The classic failures come from scopes that are too broad, reused tokens, keys that are never rotated, or the assumption that a valid token is enough to authorise an action. In the field, the flaw is rarely a missing authentication. It is the gap between the identity that was proven and the rights that are actually enforced.

The simple method takes four steps: take account A, capture the request, replay it with the identifier of account B, then check whether the object or its properties are still accessible. It is basic, but it is what reveals BOLA/IDOR in real life. On a REST API, /users/123 replayed as user 456 can still return the email and the address. In GraphQL, a field like adminNotes can leak despite correct authentication if field-level authorization is missing.

BOLA, roles and privilege escalation

The most sensitive point remains role separation. Teams often check who is logged in and forget what that person is allowed to do. That is where privilege escalation slips in, especially when backends mix object-level and property-level access control in the same place. Tests must cover roles, objects, fields and session states together. I would rather test three well-chosen identities with different rights than twenty near-identical accounts that produce results nobody can read.

What scanners see poorly

Classic scanners see business logic, action sequences, fraud and API abuse poorly. That is where you find stacked coupons, bypassed KYC steps, a price changed by the order of calls, or mass extraction despite correct authentication. These flaws do not look like syntax errors; they look like a poorly designed user journey. When the problem is in the business logic, you have to read the sequence, not only the HTTP response.

In a product team that deploys often, false positives cost time, but false negatives cost incidents. A small number of reliable alerts beats an avalanche of noise nobody reads. The trade-offs between tooling and human testing are covered in more depth in automated vs manual penetration testing.

How to cut false positives

The right reflex is to tie every alert to a reproducible request and a technical owner. Otherwise you pile up tickets that go nowhere. A good stack reduces noise not by hiding results, but by filtering on active routes, live versions and risks that can be confirmed. In practice, keep the results that point to observable behaviour: an object identifier, a modified header or a difference between roles. The rest goes to the verification backlog, not to the dashboard.

The right stack for your maturity and budget

Minimal stack

For an open source team or a very tight budget: OWASP ZAP, Postman, Schemathesis and Nuclei. The goal is to cover basic manual testing, validate a few critical routes and run automated tests against your most reliable specs. It is the best option if you want to start fast without blocking the team. With this base you already cover simple discovery, replay and part of the fuzzing without buying heavy tooling.

Intermediate stack

For a product team that ships often: Burp Suite, Postman, Schemathesis and Kiterunner. You add the quality of advanced manual testing to better surface discovery. Then measure endpoint coverage, triage time and the share of APIs with an up-to-date spec. Without those numbers, you cannot tell whether the stack is improving. This is the combination I would pick for a team of about ten developers that has to audit regularly without a full AppSec lab.

Advanced stack

For a mature AppSec program: Burp Suite, 42Crunch or StackHawk, manual validation of critical flows, and regular pentests with a retest after each fix. This combination works well when APIs change fast and tests have to feed straight into remediation. I would choose this path for a scale-up handling payments, KYC or high-volume operations. It is also the right model when a failed control should not just create a ticket but block a deployment until the risk is understood.

Simple rule: choose first by API type, spec quality and your team's capacity to fix. The tool's reputation comes after.

What to put in place now

Start with a clean map of your endpoints, then split testing into three blocks: manual, schema-based and business logic. That split avoids duplicate work and false feelings of safety. If you can pick only one priority this week, take coverage of the real routes and object-level authorization. Everything else gets easier after that. Once you can see the live routes, you stop testing blind and start covering what actually breaks.

Fleuret runs agentic pentests on web apps, REST and GraphQL APIs, with replayable PoCs pushed to Jira, Linear or Slack. See Fleuret in action.

Sources

OWASP Top 10 API Security Risks, 2023, OWASP API Security Project, 2023
Apollo GraphQL unveils first comprehensive API orchestration research study, Apollo GraphQL
Best practices leading orgs to release software faster, GitLab, 2023