Pre-release testing of a payment or transfer flow
Standard assessment against the release candidate, with multi-role coverage and business logic testing across amount, currency and state handling.
Industries · Financial Services
The systems that move money need more than an annual test
Payment flows, lending decisions, account servicing, open banking APIs — the logic that handles money is the logic attackers study hardest. It is also the logic no signature database describes.
AIPTx tests it the way someone trying to abuse it would, inside a scope you define, and hands back evidence rather than a probability.
01
Industry overview
Financial services runs on software that cannot be wrong twice.
The estate is unusually layered: a core banking platform that predates most of the team, a middle tier of services built to modernise access to it, a public API surface opened under regulatory pressure, mobile clients, partner integrations, and an acquired institution or two whose systems were never fully absorbed. Three forces make security testing harder here than almost anywhere else. Change control cuts both ways. Rigorous governance is a genuine control.
It also means testing is scheduled, documented and infrequent — while the mobile app and the API layer ship on a modern cadence regardless.
The attack surface expanded by mandate. Open banking and payment initiation regimes required institutions to expose functionality they had spent decades keeping internal. That surface is now core infrastructure.
Evidence is a business requirement, not a security one. Examiners ask. Enterprise clients ask during procurement. Partners ask before integrating. A security programme that cannot produce evidence on demand becomes a commercial constraint.
02
Security challenges
- R01
Business logic is where the money is
Amount manipulation, currency rounding, transaction replay, approval workflows that a single role can complete alone, limits enforced in the interface and not at the service. None of this has a signature. It is found by understanding what the transaction is supposed to do and then doing something adjacent.
- R02
Authorisation across a layered estate
Modern services front legacy cores. The new layer often trusts the old one, the old one trusts anything on the internal network, and the boundary between them is where authorisation assumptions quietly fail.
- R03
Open banking and partner APIs
Endpoints exposed to third parties, scoped by consent models that are complex by design. Consent scope enforced at the gateway but not at the service is a recurring and consequential pattern.
- R04
Third-party and vendor exposure
Core processing, KYC providers, payment gateways, data aggregators. Trust extended to a vendor is a path into the estate, and it sits outside the scope of most scheduled testing precisely because it belongs to someone else.
- R05
Acquired estates
Institutions grow by acquisition. Each one arrives with infrastructure that is not in the asset inventory and was not built to the acquirer's standards.
- R06
Testing windows that do not fit the risk
An annual engagement against a platform that deploys weekly leaves most of the year unexamined, and the parts most likely to have changed are the parts most likely to be customer-facing.
03
How AIPTx helps
- Stage 1
Testing bounded by governance, not fighting it
Scope is defined and verified before anything runs. Out-of-scope paths are declared and respected. Destructive actions are off by default — the agent will not delete data, run denial-of-service payloads or exhaust resources — and every run honours a request rate you set. Exploitation proves access by reading a record or retrieving a token, not by causing damage.
Most institutions start against a pre-production environment to establish confidence in the configuration, then extend to production with perimeter-limited scope. That progression is normal here and the product supports it.
- Stage 2
Business logic tested as logic
Standard mode covers business logic flaws; Deep mode adds race conditions and complex multi-step chains. Race conditions matter disproportionately in this sector — concurrent requests against a balance check are a well-understood way to break an assumption that looked sound in review.
The tests are shaped by what the application does rather than by a payload list, which is the only way a flaw with no signature is found at all. A transfer limit enforced on the client, a refund path that credits before it debits, an approval step that can be replayed: none of those match a pattern, and all of them pass a code review.
- Stage 3
Authorisation tested as a relationship
Configure users at different privilege levels and the agent cross-tests them. A retail customer session attempting to reach a corporate account, or a junior operations role reaching an approval function, only surfaces when a tool holds both sessions and compares.
Sessions are maintained across the run and re-established when they expire, so a long assessment does not quietly become an unauthenticated one halfway through. Bearer, basic, cookie, custom header and OAuth2/OIDC flows are all supported, which matters when the roles worth comparing sit behind the SSO the rest of the estate authenticates through.
- Stage 4
Evidence in the form the institution needs
Every confirmed finding carries the exact HTTP request, the response proving it worked, and a reproducible curl command, alongside CVSS 3.1 with the full vector, a CWE class and control mapping. Reports export to PDF, HTML, JSON, CSV and SARIF, with trend comparison against previous assessments.
- Stage 5
A record that survives an examination
Findings carry status — open, fixed, accepted, false_positive — with the person, date and reason recorded on every change. When someone asks why a high-severity finding from March remains open, “accepted, by this person, for this reason, on this date” is an answer. Silence is not.
04Features & Solutions
Relevant features and solutions
Business logic and race condition testing
Deep mode. The class that matters most in transaction systems and least in a signature database.
Multi-role authenticated testing
Bearer, basic, cookie, custom header and OAuth2/OIDC authorisation code flow, plus scripted login with token extraction. Sessions maintained across the run and re-established on expiry.
Web Application SecurityAPI testing across REST, GraphQL and gRPC
Spec-driven from OpenAPI or Swagger, so every declared endpoint is tested, including the ones no interface calls.
API SecurityInternal network assessment
The AIPTx agent deployed via Docker, covering internal IP ranges and CIDR blocks: port and service detection, version detection, CVE matching, TLS posture and default credentials.
JWT and session security
algorithm_none, weak secrets, expired tokens and missing claims; session fixation with regeneration verification, and timeout validation.
Sensitive data detection in responses
Passwords, secrets, tokens, national identifiers and card numbers returned where they should not be, plus PII detection and verbose error monitoring.
Compliance evidence
Control mapping and gap analysis for PCI DSS, SOC 2, ISO 27001, GDPR, NIST and CIS.
Pipeline integration
GitHub Actions, GitLab CI and Jenkins for pull-request gating; Jira and Linear for ticketing; Slack and Microsoft Teams for alerting.
05
Benefits
- Testing frequency stops being a budget decision
- Coverage tracks your release rate rather than your procurement cycle, which matters most for the customer-facing tier that changes fastest.
- Findings arrive proven
- Validation removes the first and most contentious phase of remediation: establishing whether the issue is real. In an organisation where changes require justification, an executed exploit is a stronger case than a severity label.
- Evidence on demand
- Client due diligence, partner onboarding and examiner requests are answered from generated output rather than from a fortnight of assembly.
- Accepted risk becomes governance
- A recorded, attributed acceptance is a control artefact. An unrecorded one is a finding nobody can explain.
- Specialists do specialist work
- Recurring breadth-first testing stops consuming expensive hours, so human engagements go to novel logic and architectural review.
- Acquisitions assessed quickly
- Point it at the inherited estate and find out what you bought, without a procurement cycle first.
06
Use cases
Open banking API assurance
Spec-driven testing of every declared endpoint, with consent scope tested by attempting cross-access between authorised parties.
Client due diligence response
An enterprise client asks when the platform was last tested and by what method. Run it, export the report, attach the control mapping.
Post-acquisition baseline
External discovery followed by internal agent-based assessment of an acquired institution's estate.
Pre-examination readiness
A Deep assessment before a regulatory window, with PCI DSS and NIST control mapping and retest history attached.
Vendor integration review
Assessing the surface exposed to a new processing or KYC partner before the connection goes live.
FAQs
Can we run this against production banking systems?
Yes, within a scope you define and verify first. Destructive actions are disabled by default, the agent respects a configurable request rate, and exploitation proves access rather than causing damage. Most institutions begin in pre-production to establish confidence in the configuration, then extend to production with limited scope.
Will the output satisfy our examiners?
Reports include an executive summary, technical detail, remediation guidance with code examples, control mapping and trend comparison against previous assessments, in PDF, HTML, JSON, CSV and SARIF. Control mapping covers PCI DSS, SOC 2, ISO 27001, GDPR, NIST and CIS.
Do you test business logic, or only technical vulnerabilities?
Business logic is one of the seven vulnerability classes and is covered in Standard mode, with race conditions and complex multi-step chains added in Deep mode. In transaction systems this is usually the most valuable class, because it has no signature and is therefore the least likely to have been tested before.
How do you handle our authorisation model?
Configure users per role and the agent cross-tests them against each other. Horizontal and vertical access-control failures (one customer reaching another's account, a junior role reaching an approval function) only surface when both sessions are held simultaneously and compared.
What about our legacy core?
Internal network assessment via the Docker-deployed agent covers internal ranges: port and service detection, version detection, CVE matching, TLS posture and default credentials. Application-layer testing covers the services fronting the core. Assessment of the core platform's own application logic depends on what it exposes. Worth a scoping conversation.
Can findings feed our existing risk register?
Findings export as JSON and CSV and are available through the REST API, and route into Jira and Linear as tickets. Each carries CVSS 3.1, a CWE class, control mapping and a status with full attribution.
The engine behind it
Test the transaction, not just the login page
Scope it, run it, and get evidence your examiners and your clients will both accept.
Scope verified before any test runs · Destructive actions off by default
Security testing for other sectors
Same engine, different threat model, different auditor. Each page covers the systems, regulations and attack paths that sector actually lives with.
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