hire an ai that
thinks like an attacker.
Impactr is an AI that pentests your web apps and APIs the way a senior offensive security engineer would - investigating, chaining vulnerabilities, and proving impact with evidence. No more vulnerability scanners producing PDFs of noise.
Kill Chain
Architecture Pivot
endpoints mapped per scan, avg.
attack-chain steps traced, avg.
findings confirmed with a working PoC
from kickoff to first report
from internal testing on pre-launch benchmark targets
the problem
You don't have a scanning problem. You have an investigation problem.
Scanners flag, they don't investigate
Traditional DAST tools pattern-match against known signatures and hand you a list of maybes. Triage takes longer than the scan.
Real vulnerabilities live in the chain
The IDOR that leaks a tenant ID. The auth flaw that unlocks it. The logic bug that turns it into account takeover. Scanners see none of it - they check boxes, not paths.
Manual pentests happen twice a year
Your app ships fifty times before your next scheduled pentest even starts. The gap between releases and review is where breaches live.
the approach
Built to reason about your application, not just crawl it.
It investigates
Impactr explores your app the way a human tester would - following redirects, testing role boundaries, probing every parameter it finds along the way.
It chains
Individually low-severity findings get combined into real attack paths: an information leak revealing an IDOR, which leads to account takeover.
It proves impact
Every finding ships with a reproducible proof of concept - the request, the response, and the exact steps a developer needs to fix it.
how it works
From URL to confirmed attack path.
Point it at your app
Give Impactr a URL, an API spec, or a set of authenticated roles. No agents to install, no code changes required.
It maps and investigates
Impactr builds a live model of your attack surface - endpoints, roles, data flows - and starts probing for weaknesses the way a human would.
It chains what it finds
Individual findings are tested together for exploitable paths, not reported in isolation. If three low-severity issues chain into one critical one, you'll see the chain.
You get evidence, not a wall of text
Every confirmed finding includes a reproducible PoC, the exact request/response pair, and a fix recommendation your team can act on same-day.
capabilities
Everything a senior pentester does. None of the scheduling.
AI investigation
Explores your app dynamically instead of matching static signatures.
Attack chain discovery
Combines individually minor findings into confirmed, exploitable paths.
Developer-ready reports
Findings written for the engineer who has to fix them, not just an auditor.
Evidence collection
Every finding ships with request/response pairs and a working PoC.
Continuous testing
Re-runs on every deploy so new code gets tested before attackers find it.
API understanding
Parses OpenAPI/GraphQL schemas to test business logic, not just endpoints.
Context-aware analysis
Understands auth roles and tenant boundaries to find access-control flaws.
False positive reduction
Every finding is actively validated before it's reported - not just flagged.
why not just-
Scanners are fast. Manual pentests are thorough. Rarely both.
| DAST scanner | Manual pentest | Impactr | |
|---|---|---|---|
| Finds known CVEs / signatures | |||
| Chains findings into real attack paths | |||
| Reasons about business logic | |||
| Provides reproducible evidence | |||
| Runs on every deploy | |||
| Available in days, not months | |||
| Low false-positive rate |
early access
What early access users are finding.
“We ran it against an API we thought we knew well. It found an auth chain three of our engineers had missed in review.”
“The report read like something our own pentest vendor would write - not a scanner dump we had to triage for two days.”
“What sold us was the evidence. Every finding came with a request we could replay ourselves.”
faq
Questions, answered directly.
Scanners match traffic against known signatures and report every possible match, leaving you to triage. Impactr investigates the way a person would: it follows leads, tests role and tenant boundaries, and chains individually low-severity findings into confirmed attack paths - then proves exploitability before reporting anything.
Think of it as what happens between your scheduled pentests. Impactr runs continuously as you ship, so the gap between releases and review - where most real-world exploitation happens - gets covered. Many teams will use both.
Impactr is built for web applications and APIs - REST and GraphQL, with or without an OpenAPI spec. Give it a URL or a spec and a set of authenticated roles to test against.
No. Impactr tests your application the way an external attacker would - over HTTP, using credentials you provide for the roles you want covered.
Every finding is actively validated, not just flagged. If Impactr can't demonstrate real impact with reproducible evidence, it doesn't make it into your report.
We're onboarding early access users in small batches so every team gets real attention during setup. Join the waitlist and we'll reach out with next steps.
get access
Find out what your scanner is missing.
Join the waitlist to get early access as we onboard new users.