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.NETWhat application security covers
Application security focuses on the software you build and run: its design, code, dependencies, configuration and the way it handles data. Most breaches that affect growing companies exploit application weaknesses — broken access control, injection flaws, vulnerable libraries, exposed secrets — rather than exotic network attacks.
We work as an extension of your engineering team: reviewing architecture before features are built, testing and reviewing existing code, fixing what we find and putting automated checks in place so the same problems do not return.
Problems we solve
- Nobody has reviewed how users’ data is separated in a multi-tenant product
- Dependencies years out of date with published vulnerabilities
- API endpoints that trust whatever the client sends
- Secrets and keys committed to repositories
- Security issues discovered by customers or researchers rather than your team
What’s included
Threat modelling
Structured review of how a feature could be attacked, done before it is built.
Architecture review
Authentication, authorisation, data flows, encryption and trust boundaries.
Secure code review
Manual review of high-risk code paths backed by static analysis.
Vulnerability remediation
We fix issues, not just report them.
DevSecOps
SAST, dependency, secret and container scanning in CI/CD.
Developer training
Practical secure-coding sessions using examples from your codebase.
Security in the development life cycle
- Plan — security requirements and abuse cases written alongside user stories.
- Design — threat models for features touching authentication, payments or personal data.
- Build — secure defaults in frameworks, peer review and pre-commit secret detection.
- Test — automated scans on every pull request and periodic manual testing.
- Release & operate — dependency patching cadence, logging and alerting for suspicious activity.
Prioritising what to fix first
Security reviews can produce long lists of findings. We rank each issue by real-world exploitability and business impact, not just a scanner’s severity label, and group fixes so they can be delivered in normal sprints. Critical issues are fixed immediately; the rest join a remediation plan with clear owners and dates. Retesting confirms each fix works.
The most common application weaknesses we find
Most real-world breaches of business applications do not involve exotic techniques. They exploit a small set of recurring mistakes that are easy to introduce under deadline pressure and easy to miss in code review:
| Weakness | How it happens | How we prevent it |
|---|---|---|
| Broken access control | An endpoint checks that a user is logged in but not that the record belongs to them | Central authorisation layer and automated tests for every role |
| Injection | User input concatenated into SQL, shell commands or templates | Parameterised queries, ORM defaults, input validation |
| Secrets in code | API keys committed to the repository or baked into builds | Secret managers, pre-commit scanning, key rotation |
| Vulnerable dependencies | Libraries left un-updated for months | Automated dependency scanning and scheduled updates |
| Weak session handling | Long-lived tokens, missing logout invalidation | Short-lived tokens, refresh rotation, secure cookie flags |
| Excessive data exposure | APIs return whole objects and rely on the front end to hide fields | Explicit response schemas per role |
Questions to ask before your next release
A short pre-release review catches a surprising number of issues. We encourage product teams to ask these questions for every significant feature:
- Who should be able to see or change this data, and is that enforced on the server?
- What happens if a request is replayed, reordered or sent with another user’s ID?
- Does this feature log enough to investigate misuse — without logging passwords or personal data?
- Have new dependencies been checked for known vulnerabilities and licence issues?
- Are error messages helpful to users without revealing internal details?
- If this feature were abused at scale, would rate limits or alerts notice?
None of these require a security specialist to answer, but they do require the question to be asked. We build them into pull-request templates so they become habit rather than an afterthought.
Security tooling in the pipeline
Automated tools catch whole classes of issues on every change, leaving people free to focus on design flaws and business logic. A typical pipeline combines static analysis (SAST) on source code, software composition analysis for dependencies, secret scanning on every commit, container and infrastructure-as-code scanning, and dynamic scanning (DAST) against a running test environment. The tools are cheap to run; the real work is tuning them so developers trust the results. We start with a small set of high-confidence rules that block merges, report the rest as warnings, and raise the bar gradually as the backlog shrinks.
Threat modelling in practice
Threat modelling is the cheapest security activity there is, because it happens before code is written. We run short, structured sessions with the people who design and build the feature, using four questions:
-
What are we building?
A simple diagram of components, data flows and trust boundaries — where data crosses from users, partners or the internet into your systems.
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What can go wrong?
Walk each boundary using a checklist such as STRIDE: spoofing, tampering, repudiation, information disclosure, denial of service and elevation of privilege.
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What will we do about it?
Agree a control for each realistic threat and turn it into backlog items with acceptance criteria.
-
Did we do a good job?
Check the controls during code review and testing, and revisit the model when the design changes.
A focused session for a single feature typically takes one to two hours. For a whole system, a few sessions spread across components works better than one marathon meeting.
Application security activities compared
| Activity | Finds | Best timing |
|---|---|---|
| Threat modelling | Design flaws and missing controls | Before and during design |
| Static analysis (SAST) | Insecure code patterns | Every pull request |
| Dependency scanning (SCA) | Known-vulnerable libraries | Every build, plus daily alerts |
| Dynamic testing (DAST) | Runtime issues in a running app | Nightly or per release on staging |
| Manual code review | Logic and authorisation flaws tools miss | High-risk changes |
| Penetration testing | Exploitable chains across the system | Before major launches and periodically |
Each activity catches different classes of problem; mature programmes combine several.
Penetration testing is covered in detail on our penetration testing page.
Building a security champions programme
Central security teams cannot review every change. A security champion — one developer per team with extra training and time — scales good practice across the organisation. We help set up the programme: choosing champions, a short training path covering secure coding and threat modelling, a regular call to share findings, and clear guidance on when to escalate to specialists. Champions do not replace security engineers; they make sure security questions get asked early, inside every team.
Measuring application security
- Mean time to fix critical and high findings, tracked against agreed targets
- Share of repositories with scanning enabled in the pipeline
- Number of findings reintroduced after being fixed (a sign of missing regression tests)
- Percentage of high-risk features that went through threat modelling
- Age of the oldest open high-severity finding
Trends matter more than absolute numbers: a rising count of findings after enabling a new scanner is progress, not failure.
Related services
Part of our cybersecurity engineering services. See also penetration testing and identity & access management.
This page is part of Cybersecurity Engineering Services — see the full overview for related services, approach and pricing.