A scanner reads syntax. We read intent.

Automated scanners catch known bug patterns. They can't tell whether your code lets a user skip a payment, escalate their access, or abuse a feature you built to help them.

We read your code the way an attacker would, for the business logic flaws that actually cost you.
Code snippet in auth.js defining an authenticate function that verifies a token using jwt.verify with a secret. If the payload lacks a userId, it throws an AuthError with status 403; otherwise, it returns the payload.Dark-themed source code editor window labeled SOURCE CODE showing a file named auth.js with lines 1 to 9, with line 6 highlighted. The code content is blurred or redacted.Red circular dot on a transparent background.A bright green circular dot on a white background.Red circular dot on a transparent background.Bright green circular pattern with multiple smaller green dots arranged concentrically, forming a mandala-like design on a green background.Red circular dot on a transparent background.Bright green circular pattern with multiple smaller green dots arranged concentrically, forming a mandala-like design on a green background.Red circular dot on a transparent background.Bright green circular pattern with multiple smaller green dots arranged concentrically, forming a mandala-like design on a green background.
Red text on dark background reading 'Weak crypto implementation'.Green text reading 'Crypto implementation hardened' on a black background.Red text on a dark background stating 'Hardcoded credentials found.'Text in bright green on a dark background reading: Hardcoded credentials removed.Red warning text on black background stating 'Insecure deserialization found'.The phrase 'Deserialization secured' displayed in bright green text on a black background.Red text reading 'Broken auth logic' on a black background.Green text on black background saying 'Auth logic fixed'.
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The question that matters

Your code passes every automated scan. But can someone abuse the logic you built to serve customers?
WHY MOST CODE REVIEWs FALL SHORT

A scanner reads syntax.
It doesn't understand your business.

Automated tools match patterns for known bugs. They have no idea what your app is supposed to do, so they miss the logic flaws, privilege escalations, and abuse paths that don't look like 'bugs' at all. Those take a human reading the code with an attacker's mindset.
Most Code Reviewers
Automated scanner-driven review
Pattern matching for known bugs
Generic security checklists
Findings with no exploitation context
Scanner output defines thoroughness
Mechanical severity ratings
Payatu
AI-native and researcher-led: manual-first review with selective automation
Business logic and workflow analysis, by hand
Adversary-driven threat mapping
Exploitation thinking and real impact assessment
Human reasoning over tool dependency
Risk prioritised by business context
What we Review

Line by line

We read the code that matters most, by hand, for the flaws scanners miss.
Java
Java
JavaScript / TypeScript
Go
C / C++
PHP
Kotlin & Swift
Third-party libraries
Java
Python
JavaScript / TypeScript
Go
C / C++
PHP
Kotlin & Swift
Third-party libraries

Business logic & access

Business logic & workflow abuse
Authentication & authorization in code
Privilege escalation paths
Input handling & injection
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Business logic & access

Data & secrets

Sensitive data handling
Hardcoded secrets & keys
Cryptography use
Error handling & logging
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Data & secrets

Dependencies & design

Third-party libraries & SDKs
Insecure design & anti-patterns
Trust boundaries between components
Update & supply-chain risk
Dependencies & design
Gradient background with smooth transition from dark blue on the lower left to deep red on the lower right, blending into black at the top.
Business logic & access
Business logic & workflow abuse
Authentication & authorization in
code
Privilege escalation paths
Input handling & injection
Data & secrets
Sensitive data handling
Hardcoded secrets & keys
Cryptography use
Error handling & logging
Dependencies & design
Third-party libraries & SDKs
Insecure design & anti-patterns
Trust boundaries between
components
Update & supply-chain risk
Process

How it works

Simple, step by step, from first read to confirmed fix.

Understand the app

You share the code and what it does. We learn the risky parts before we read a line.
01

Map the code

We trace how data and users move through the code, so we know where to look hardest.
02

Prove the impact

For each flaw, we show how it could
be abused and what it would cost.
04

Read it by hand

Our reviewers read the code like an attacker, backed by tools for coverage.
03

Report with fixes

Clear findings ranked by business risk, with secure code examples in your language.
05

Re-review

After you fix, we check the changes and confirm the flaw is truly closed.
06
Process

How it works

Simple, step by step, from first read to confirmed fix.

Understand the app

You share the code and what it does. We learn the risky parts before we read a line.
01

Map the code

We trace how data and users move through the code, so we know where to look hardest.
02

Read it by hand

Our reviewers read the code like an
attacker, backed by tools for
coverage.
03

Prove the impact

For each flaw, we show how it could
be abused and what it would cost.
04

Report with fixes

Clear findings ranked by business
risk, with secure code examples in
your language.
05

Re-review

After you fix, we check the changes
and confirm the flaw is truly closed.
06
Process
How it works
Simple, step by step, from first read to confirmed fix.

Understand the app

You share the code and what it does. We learn the risky parts before we read a line.
01

Map the code

We trace how data and users move through the code, so we know where to look hardest.
02

Read it by hand

Our reviewers read the code like an attacker, backed by tools for coverage.
03

Prove the impact

For each flaw, we show how it could be abused and what it would cost.
04

Report with fixes

Clear findings ranked by business risk, with secure code examples in your language
05

Re-review

After you fix, we check the changes and confirm the flaw is truly closed.
06
Real world impact

Real applications, real findings.

IT/SaaS
Secure Source Code Review

Source Code Review of an Internationally Renowned MNC

View Details
IT/SaaS
IT/SaaS
Secure Source Code Review
Fintech
Secure Code Review

Secure Code Review for One of the Largest Online Payments Service Providers

View Details
Fintech
Fintech
Secure Code Review
Testimonials

What engineering teams say about working with us

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Carthic Kameshwaran

Head of Delivery - neoEYED

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Arockiaraj Martin

CISO- Enkash

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Payatu's focus on in-depth defence, quality, and proactive approach to all their services were precisely what our fast-growing publicly listed company needed.
Payatu's Services have helped us in ensuring that not only do we exceed strict compliance standards, but also ensure that security is not just a tick box exercise in our organisation. We have been able to make security an integral part of...

Simran Gambhir

Chief Information Officer - Butn, Sydney

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CheckRed Security company logo with a stylized red cloud and checkmark icon next to the black and red text.
Payatu delivered a 360-degree penetration testing exercise across our web applications and internal network. Their structured, methodical approach and deep technical understanding were evident throughout the engagement. They didn’t just give us a list of vulnerabilities, they provided actionable insights that helped to improve our security posture. The engagement was constructive.

Sushil Vanve

Director of Engineering - CheckRed

WHY PAYATU

Why engineering teams pick us

We lead with human review, not scanner output. So you get the logic and design flaws that tools miss, with fixes your developers can use.
OSCP, OSWE, eWPT & eWPTX certified
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ISO 17025 accredited · CERT-In empanelled
Founders of Nullcon &
hardwear.io
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CVEs in major frameworks & libraries
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Secure code examples in your language
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Contributors to OWASP guidelines
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White text on a black background that reads 'Safer, stronger software.'
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What you get

The whole story, and fixes your team can act on.

Complete explaination

Every flaw we found and how we found it, in plain words your team can follow.

Fixes in your language

Secure code examples in your own framework, so developers can act the same day.
Young person sitting on a chair using a laptop, surrounded by glowing orange and blue digital code spiraling around them in a dark space.

Proof it can be abused

For each finding, how an attacker would exploit it and what it would cost.

A re-review

After you fix, we check the changes and confirm the flaw is truly closed.
FAQ

Questions Web Application teams ask us

What is Web Security Testing?
Web Security Testing identifies vulnerabilities in web applications that attackers could exploit, helping organizations protect sensitive data and prevent security breaches.
What vulnerabilities are tested during a Web Security Assessment?
Web Security Testing identifies vulnerabilities in web applications that attackers could exploit, helping organizations protect sensitive data and prevent security breaches.
How is Web Security Testing different from a vulnerability scan?
Web Security Testing identifies vulnerabilities in web applications that attackers could exploit, helping organizations protect sensitive data and prevent security breaches.
When should we perform Web Security Testing?
Web Security Testing identifies vulnerabilities in web applications that attackers could exploit, helping organizations protect sensitive data and prevent security breaches.
What do we receive after the Web Security Assessment?
Web Security Testing identifies vulnerabilities in web applications that attackers could exploit, helping organizations protect sensitive data and prevent security breaches.
Can Web Security Testing identify business logic vulnerabilities?
Web Security Testing identifies vulnerabilities in web applications that attackers could exploit, helping organizations protect sensitive data and prevent security breaches.