Security
Security Testing Services
We wire security testing into your pipeline so vulnerabilities are caught on the commit that introduces them, cheaply and continuously, not in an annual audit long after the flaw shipped.
What Security Testing means in practice
Who it’s for: Teams handling sensitive data or facing a compliance requirement, who want vulnerabilities caught continuously in the pipeline rather than in an annual audit, and who want an honest account of what automation catches and what still needs a human.
Security testing is the engineering discipline of finding vulnerabilities in software as it is written and shipped, rather than discovering them in an incident report. It is distinct from a penetration test: a pen test is an adversarial human assessment run at a point in time, whereas security testing is the continuous, mostly-automated layer that runs on every commit, static analysis of your code, dynamic analysis of the running application, scanning of the dependencies you pull in, detection of secrets before they reach a repository, and inspection of the container images you ship. The two are complements, and the honest position is that you want both; this service is the continuous half.
The organising idea is to shift security left: to move the checks earlier, into the pipeline that builds and deploys your software, so a flaw is caught on the branch that introduced it rather than a year later when it is expensive to trace and embarrassing to explain. A SQL injection found by a static analyser in code review costs a few minutes to fix. The same flaw found by an attacker in production costs a breach notification, a regulator’s attention and a rebuild under pressure. Everything we do here is about collapsing that gap: catching the known, common classes of vulnerability automatically and repeatedly, at the point they are cheapest to remove.
We are deliberately honest about the limits, because overselling automated scanning is how teams end up with false confidence. Scanners are very good at the known and the common: the injection flaw, the outdated dependency with a published CVE, the hardcoded key, the missing security header. They are poor at business-logic flaws, broken access control that only makes sense in the context of your domain, and the chained exploits where three individually-minor issues combine into a compromise. Automated testing finds the cheap things cheaply and produces false positives that need triage; it does not replace a human penetration test, and it does not turn security into a certificate you earn once. Security is a continuous property, and we build the machinery that keeps it continuous.
What you get
- Static application security testing (SAST) wired into CI so your own code is scanned for injection, unsafe deserialisation, path traversal and the other source-level flaws on every pull request, with findings surfaced in review rather than in a report
- Software composition analysis (SCA) that inventories every direct and transitive dependency, flags the ones with known vulnerabilities, and tells you which are actually reachable, so you patch what matters instead of drowning in advisories for code you never call
- Dynamic application security testing (DAST) against the running application to catch what only appears at runtime, misconfiguration, exposed endpoints, missing security headers, authentication and session weaknesses the source alone will not show
- Secrets scanning across your code and git history, so an API key, database password or private key is caught before it is committed, and the historic leaks already sitting in your history are found and rotated
- Container and image scanning that checks base images and installed packages for known vulnerabilities and flags insecure build practices, so you are not shipping a patched application on top of an unpatched operating system
- Secure code review by a senior engineer on the security-sensitive paths (authentication, authorisation, payment, data access), where a human reading intent catches the logic and access-control flaws that no scanner can see
- Security gates configured in the pipeline with a policy that fits reality: build-breaking on the serious and the certain, warning on the rest, and tuned to suppress the noise so developers trust the signal instead of learning to ignore it
What Security Testing does for you
Fix flaws while they are cheap
The cost of a vulnerability rises sharply the later it is found. A flaw caught by a static analyser in code review is a few minutes of a developer’s time; the same flaw caught in production is an incident, a disclosure and a rebuild under scrutiny. Building security testing into the pipeline moves the discovery to the earliest, cheapest possible point (the commit), and keeps it there for every change, so you stop paying the late-discovery premium on issues that were entirely findable early.
Turn compliance into working machinery
Most security frameworks and customer questionnaires ultimately ask the same thing: do you find and fix vulnerabilities systematically, and can you show it. A pipeline that scans code, dependencies, secrets and images on every change produces exactly that evidence as a by-product of doing the work: a record of what was scanned, what was found and what was fixed. Instead of writing a policy that describes security you do not actually practise, you get the practice, and the audit trail comes free with it.
Stop shipping known-vulnerable dependencies
Most of a modern application is code you did not write, open-source libraries pulled in directly and transitively, any of which may carry a published, exploitable vulnerability. Composition analysis gives you a live inventory of what you actually depend on and which pieces have known flaws, and reachability analysis tells you which of those you genuinely call. That turns dependency risk from an unknown into a managed, prioritised list, so a newly-disclosed vulnerability in a library you use is something you find and patch deliberately rather than something an attacker finds first.
Why teams choose us for Security Testing
- You want security testing built into how software is delivered (running on every commit), not commissioned once a year as an event that is out of date the day after it finishes.
- You want the scanning tuned by someone who understands both the tools and the code, so the findings are real and prioritised by genuine exploitability, instead of an untuned firehose of false positives your developers will learn to ignore.
- You want an honest account of the boundary between automated scanning and human testing, what the pipeline catches cheaply, and where you still need a penetration test, rather than a vendor pretending a scanner is the whole of security.
- You are handling sensitive data or facing a compliance requirement and need real, demonstrable vulnerability management with an audit trail, delivered by senior engineers who have operated the systems they secure.
What Security Testing includes
The concrete pieces of work this covers, scoped to what your problem actually needs.
Static analysis (SAST) in the pipeline
Static analysis reads your source code without running it, tracing how untrusted input flows through the application to find the source-level vulnerability classes. SQL and command injection, cross-site scripting, unsafe deserialisation, path traversal, insecure use of cryptography. We integrate it into CI so it runs on every pull request and reports in the review, and (just as importantly), we tune the rules to your stack so the output is signal rather than a thousand style-adjacent warnings. SAST is strongest on the code you own and the well-understood flaw patterns; it sees the source but not the runtime, which is why it is one layer of several rather than the whole answer.
Dynamic analysis (DAST) against the running app
Dynamic analysis tests the deployed, running application from the outside, the way a client would, sending crafted requests and observing responses to find the issues that only exist at runtime. That covers misconfiguration, missing or wrong security headers, exposed administrative or debug endpoints, authentication and session-management weaknesses, and injection points reachable through the live interface. Because it needs no source and sees the assembled system including its configuration and infrastructure, DAST catches a different, complementary set of problems from SAST. It is slower and noisier to run continuously, so we place it where it earns its keep, typically against a staging environment on a regular cadence.
Dependency and supply-chain scanning (SCA)
Composition analysis builds a bill of materials for your application (every direct and transitive dependency and its version), and cross-references it against known-vulnerability databases so you know precisely which libraries carry published, exploitable flaws. The step that turns this from noise into action is reachability: distinguishing a vulnerability in code your application actually executes from one buried in a code path you never touch, so remediation effort goes where the real exposure is. We wire this into CI and into dependency-update automation, so a newly-disclosed CVE in a library you use raises an alert you can act on rather than sitting undetected until it is exploited.
Secrets scanning and history remediation
Hardcoded credentials (API keys, database passwords, private keys, tokens), are among the most common and most damaging leaks, because a committed secret is a working key handed to anyone who can read the repository, and git history means deleting it from the current code does not remove it. We add secrets scanning that blocks new secrets before they are committed, and we sweep the existing history to find what is already there. Because a leaked secret must be assumed compromised the moment it lands, the remediation is rotation, not just deletion, and we set out the process so a future leak is caught at the boundary rather than discovered after it is abused.
Container and image scanning
A secure application shipped on top of an unpatched base image is not a secure deployment. Container scanning inspects the images you build (the base OS, the system packages, the language runtime), for known vulnerabilities, and flags insecure build practices such as running as root, embedded secrets or needlessly large attack surface. We integrate it into the build so an image with a critical, fixable vulnerability is caught before it is pushed, and pair it with guidance on minimal base images and rebuild cadence, because an image scanned clean today accumulates newly-disclosed vulnerabilities simply by sitting unrebuilt.
Secure code review by a human
The most damaging vulnerabilities are frequently the ones no scanner can see: broken access control where a user can reach another user’s data, authentication logic with a subtle bypass, a business rule that can be abused, a chained sequence of individually-minor issues. These are failures of intent and context, and finding them needs an experienced engineer reading the security-sensitive paths (authentication, authorisation, payment, data access), and reasoning about what an attacker could do. We do this focused human review on the parts that matter most, because it is exactly the layer automated scanning cannot provide, and the layer where the expensive breaches actually live.
Where it fits
Standing up security testing from nothing
A team shipping to production with no security checks in the pipeline, vulnerabilities, if found at all, are found late and by luck. The work is to establish the full layered baseline: SAST and secrets scanning on every pull request, dependency and container scanning in the build, DAST against staging on a cadence, and a gate policy tuned so the signal is trustworthy from day one. The outcome is that the common, known classes of vulnerability start being caught automatically and continuously, and the team gains a security floor that holds on every change rather than depending on someone remembering to look.
Producing evidence for a compliance or due-diligence review
A SOC 2 audit, an ISO 27001 certification or an enterprise customer’s security questionnaire wants proof of vulnerability management and secure development. Rather than writing aspirational policy, we build the machinery that both does the work and generates the evidence: scanning on every change, a record of findings and their remediation, a documented gate policy. The engagement gives you a defensible, honest answer to "how do you find and fix vulnerabilities", backed by a pipeline that actually does it, so the audit becomes a matter of showing what already runs.
Cleaning up before a launch or major release
A product approaching a launch or a significant release, where the team wants the known, common vulnerabilities found and fixed before real users and real attackers arrive. We run the full sweep: static and dynamic analysis, dependency and secrets and image scanning, and a focused human review of the authentication and access-control paths, and hand back a prioritised list of what to fix and why. This is the pre-launch cheap-and-known pass; where the stakes warrant an adversarial human assessment as well, we say so and scope a penetration test alongside it.
Systematising security after an incident or near-miss
An incident or a close call has revealed that security was ad hoc. A leaked key, an unpatched dependency, an injection that should have been caught. Beyond the immediate fix, the durable answer is to make the class of failure impossible to ship silently again: secrets scanning at the commit boundary, dependency scanning that would have flagged the vulnerable library, SAST that would have caught the injection. We wire those in so the specific weakness that caused the incident becomes a pipeline check, and the near-miss becomes the reason the next one is caught early rather than lived through.
How we approach Security Testing
We start by wiring the checks into the pipeline you already have, because security testing that lives outside the delivery process is security testing that gets skipped under deadline pressure. SAST, dependency scanning, secrets detection and container scanning become steps in CI that run on every commit and pull request, with the results shown where developers already look: in the code review, not in a quarterly PDF nobody opens. The goal is that a vulnerability introduced on Tuesday is flagged on Tuesday, by the person who introduced it, while the context is still fresh and the fix is a small change rather than an archaeology project.
The harder, more valuable part is tuning the noise out. An untuned scanner floods a team with hundreds of low-value and false-positive findings, and the entirely predictable result is that developers stop reading them: at which point the real issue hides among the false ones and the whole exercise has made security worse, not better. So we calibrate: build-break on the high-confidence, high-severity findings, triage and suppress the rest with documented reasons, and prioritise by what is genuinely reachable and exploitable in your context. A quiet, trustworthy signal that developers act on beats a loud, ignored one every time. And where the automation reaches its limit. The logic flaws, the chained exploits, the access-control decisions that only make sense in your domain. We say so plainly and point to where a human penetration test is the right next step.
How the engagement runs
We begin by understanding what you are protecting and how you ship it: the kind of data you hold, the compliance pressures you are under, the languages and frameworks in your stack, and the shape of your existing pipeline. That determines which layers matter most and where they belong. SAST and secrets scanning on every pull request, dependency scanning in the build, DAST against a running environment on a cadence, container scanning at image build. We add the tools appropriate to your stack rather than a generic checklist, and we establish a baseline scan so you can see the current state honestly before anything is gated.
From there the work is integration and calibration. We wire each check into CI so it runs automatically and reports where developers already work, then we tune (the single most important step), triaging the initial flood, suppressing false positives with documented reasons, and setting a gate policy that breaks the build only on the serious and the certain. We review the security-sensitive code paths by hand, prioritise every finding by genuine exploitability, and hand back a clear remediation order. Then we make it durable: the checks keep running on every change, the policy is written down, and your team knows how to read the findings, triage new ones and keep the noise low so the signal stays trusted.
Where security testing fits the SDLC: shifting left
The cost of a vulnerability climbs with every stage it survives undetected. Caught in the editor or the pull request, it is a small edit by the developer who wrote it, with full context, before it has shipped anywhere. Caught in production by an attacker, the same flaw is an incident, a disclosure obligation, a forensic investigation and a fix applied under pressure by people reconstructing what happened. Shifting left means deliberately moving the security checks as early in the software development lifecycle as they can meaningfully run, so that discovery happens at the cheap end of that curve by default. It is not a slogan; it is the recognition that when a check runs decides how much the flaw it finds will cost to fix.
Concretely, that means placing each kind of testing at the point in the pipeline where it fits. Secrets scanning and SAST belong at the commit and pull-request stage, running in seconds to minutes on the developer’s own change, breaking the build on high-confidence findings so a serious flaw cannot merge. Dependency and container scanning belong in the build, gating an artefact before it is published. Dynamic analysis, which needs a running system and is slower, belongs against a staging deployment on a regular cadence rather than blocking every commit. Human secure code review sits in the pull-request review of security-sensitive changes. The result is layered gates, each catching what it is best at, at the earliest stage it can, so security becomes a property of the delivery pipeline itself rather than an audit bolted on at the end. The essential discipline is that these gates must be trustworthy: a gate that fires on noise gets disabled or ignored, so tuning the signal is not optional polish but the thing that makes shifting left actually work.
The vulnerability classes we test for: the OWASP Top 10
The OWASP Top 10 is the industry’s consensus on the vulnerability classes that cause the most real-world harm, and it is the backbone of what this testing looks for. Injection (SQL, command, and their relatives), remains among the most damaging: untrusted input treated as code or query, letting an attacker read or destroy data the application was never meant to expose. Cross-site scripting injects hostile script into pages other users load, hijacking their sessions and actions. Broken authentication and session management lets an attacker become someone else: through weak credential handling, guessable tokens or flawed session logic. Security misconfiguration (default credentials, verbose errors leaking internals, unnecessary exposed services, missing security headers), is the quiet, pervasive category that DAST and configuration review are built to surface. And vulnerable, outdated dependencies remain one of the commonest routes to compromise, which is why composition analysis is a first-class layer rather than an afterthought.
The category that deserves particular honesty is broken access control (a user reaching data or actions that should be denied them), because it is consistently among the most damaging and the hardest to catch automatically. Whether a given user should be able to view a given record is a question about your domain and your intent, not a pattern a scanner can recognise, which is exactly why we pair automated testing with human review of the authorisation paths. This is the crux of the honest position on this service: automated scanning is excellent at the mechanical, pattern-matchable classes (injection, known-vulnerable dependencies, leaked secrets, missing headers, unsafe configuration), and finds them cheaply and repeatedly. It is weak on access-control logic, business-logic abuse and the chained exploits where several small issues combine into a breach. Those require an adversarial human (a penetration test), and the two disciplines are complements, not substitutes. We are explicit about where the line falls so you know precisely what the pipeline covers and what it does not, and we point to our penetration-testing service for the part that needs a human adversary rather than a scanner.
Signs it’s time
- You handle sensitive data (personal, financial, health or credential), and the cost of a breach is high enough that you need to be finding vulnerabilities before an attacker does, continuously rather than once a year
- A compliance framework or customer security questionnaire (SOC 2, ISO 27001, a due-diligence review) requires evidence of vulnerability management and secure development practices, and you need real machinery rather than a policy document
- You are approaching a launch or a major release and want the known, common classes of vulnerability found and fixed before the doors open. The injection flaws, the vulnerable dependencies, the leaked secrets, the misconfigured endpoints
- You have had an incident or a near-miss, and it exposed that security today is something someone checks occasionally rather than something the pipeline enforces on every change, and you want to close that gap systematically
Our working method
The principle underneath everything is that security is a continuous property, not a certificate you earn once. A point-in-time scan or an annual audit tells you about the code as it was on the day it ran; the moment a developer merges a change or a new vulnerability is disclosed in a dependency you use, that snapshot is out of date. So the method is to build testing into the pipeline where it runs on every change and against every dependency update, keeping the property alive rather than proving it once and watching it quietly decay. That is what shifting left buys you: not a one-off clean bill of health, but a floor that holds continuously and cheaply.
The second principle is signal over noise, because it is the difference between security testing that works and security theatre that makes things worse. An untuned pipeline floods developers with false positives and low-value findings until they route around it and stop reading, and then the one real issue hides among the noise. So we invest in calibration as a core deliverable: high-confidence, high-severity findings break the build; the rest are triaged, prioritised by genuine reachability, and suppressed with documented reasons where they are false. And we are honest to the point of bluntness about the boundary of automation. Scanners catch the known and the common; they miss logic flaws and chained exploits, and they produce false positives that need human judgement. We will always tell you where the pipeline stops and a human penetration test needs to begin, rather than letting a green build stand in for security it cannot actually provide.
Technologies we build it with
Chosen per problem, not per fashion. This is the stack we most often reach for on this work.
How we deliver
- 01
Discover
We map the system, the constraints and the business it serves, including the parts nobody documented.
Architecture brief
- 02
Architect
Decisions get made, written down and defended before a line of production code exists.
Decision records
- 03
Build
Short cycles against working software. You see progress in the product, not in a status deck.
Shipping increments
- 04
Operate
Monitoring, incident response and iteration. The system is alive, so the engagement is too.
Runbooks & SLOs
Want a straight answer on Security Testing?
A short call with a senior engineer, before you write a brief. If Security Testing is the wrong answer for your situation, we will say so and tell you what we think is right.
What changes
Caught on the commit
Vulnerabilities flagged on the pull request that introduces them, while the fix is a small change, not discovered a year later when it is a breach and an investigation.
A signal developers trust
Scanning tuned so the findings are real and reachable, not a wall of false positives, so the team acts on them instead of learning to ignore the whole thing.
Continuous, not a certificate
Security testing running on every change and every dependency update, so the property is maintained over time rather than proven once and quietly decaying.
Industries we serve
Domain knowledge changes what gets built. A few of the sectors we know before the first meeting.
How pricing works
- A fixed-scope setup engagement to stand up security testing across your pipeline. SAST, SCA, secrets, container scanning and DAST integrated, tuned and gated, with a documented policy, quoted once we understand your stack and delivery setup, so you are paying for working, calibrated machinery rather than tools dropped in untuned.
- A one-off security testing sweep for a launch or milestone: the full layered scan plus a focused human review of the security-sensitive paths, delivered as a prioritised remediation list, priced by the size and complexity of the codebase.
- An ongoing engagement where we maintain the pipeline over time, keeping rules and tools current, triaging findings, handling newly-disclosed dependency vulnerabilities and keeping the noise down, for teams who want the continuous discipline maintained rather than set up and left to rot.
- A scoped secure code review of a specific high-risk area (authentication, authorisation, payment, a sensitive data flow), where a senior engineer reads the code for the logic and access-control flaws automation cannot see, priced by the area under review.
Typical timeline
- 01
Assessment and baseline
A few days to understand what you hold, the compliance pressures, the stack and the existing pipeline, and to run an initial baseline scan so the current state is visible honestly before anything is gated or tuned.
- 02
Integration into the pipeline
Wiring each layer into the right stage, secrets and SAST at the pull request, dependency and container scanning in the build, DAST against staging on a cadence, so the checks run automatically and report where developers already work.
- 03
Tuning and human review
The critical step: triaging the initial findings, suppressing false positives with reasons, setting a gate policy that breaks the build only on the serious and certain, and reviewing the security-sensitive code paths by hand.
- 04
Handover and continuity
A prioritised remediation list, a documented gate and triage policy, and your team equipped to read findings and keep the noise low, or an ongoing arrangement where we maintain the machinery as your code and its dependencies change.
What working with us actually means
Senior engineers who tune, not just install
The value in security testing is not dropping a scanner into CI. Anyone can do that, and the untuned result is a firehose of false positives your team learns to ignore. The value is calibration by someone who understands both the tools and the code well enough to separate real, reachable risk from noise, and to gate on the former without burying it under the latter. That is what we bring, and it is the difference between security testing that developers trust and security theatre they route around.
We operate what we build
Because we run systems in production, we know which findings actually matter and which are advisories for code paths nobody reaches. That operational judgement is why we prioritise by genuine exploitability rather than by a scanner’s severity label, and why we treat leaked secrets as compromised-and-must-rotate rather than delete-and-forget. We secure software the way people who carry the pager think about it, not the way a checklist does.
Honest about what automation cannot do
We will tell you plainly that automated scanning finds the known and common cheaply but misses logic flaws, broken access control and chained exploits, and that it therefore complements, rather than replaces, a human penetration test. That boundary is uncomfortable to sell and we state it anyway, because a green pipeline standing in for security it cannot provide is exactly how teams get breached while believing they were covered.
Built to stay continuous
We set up security testing so it keeps running on every change and every dependency update, with the policy documented and your team able to maintain it, not a one-off scan that is out of date the moment the next commit lands. Security is a continuous property, and we build the machinery that keeps it that way rather than a certificate that decays quietly after we leave.
How to engage us
Three ways to work with us on this, chosen to fit the problem, not our margin.
- Dedicated team A standing team that works only on your product, in your rituals and your tooling. Best when the roadmap outlives the project. Ongoing product development
- Staff augmentation Named senior engineers embedded into your existing team, reporting into your leads. Best when you know what to build and need capacity. Filling a capability gap
- Software outsourcing A defined outcome delivered end-to-end by an accountable team. Best when you want the result owned, not just the hours filled. Outcome-owned delivery
Related services
Part of Cybersecurity. Other work we do alongside this.
Common questions
How is this different from a penetration test?
They are complementary halves of security assurance. Security testing is the continuous, mostly-automated discipline (SAST, DAST, dependency and secrets and container scanning, plus focused code review), built into your pipeline so the known, common vulnerability classes are caught on every commit, cheaply and repeatedly. A penetration test is a point-in-time adversarial assessment where a human actively tries to break in, and it finds the things automation cannot: business-logic flaws, broken access control, and chained exploits where several small issues combine. You want both. This service is the continuous layer; where you need a human adversary, we point you to our penetration-testing service and are explicit about the boundary.
Will scanning just bury us in false positives?
It will if it is dropped in untuned, and that is precisely the failure we work to avoid. An uncalibrated pipeline floods developers with false and low-value findings until they stop reading them, and then the one real issue hides in the noise, which is worse than no scanning at all. So tuning is a core part of what we do, not an afterthought: we triage the initial results, suppress false positives with documented reasons, prioritise by genuine reachability, and set the gate to break the build only on the serious and the certain. A quiet, trustworthy signal developers act on is the whole point; a loud, ignored one is security theatre.
Does automated security testing mean we are secure?
No, and we would be misleading you to imply it. Automated scanning is excellent at the mechanical, pattern-matchable vulnerability classes (injection, known-vulnerable dependencies, leaked secrets, missing headers, unsafe configuration), and finds them cheaply and continuously. It is weak on the things that require understanding intent: broken access control, business-logic abuse, and chained exploits. It also produces false positives that need human judgement. So a clean pipeline means the common, known issues are being caught, not that the application is secure in every sense. Real assurance combines this continuous automated layer with periodic human penetration testing, and we are always clear about where one ends and the other must begin.
What does "shift left" actually mean in practice?
It means moving the security checks as early in the development lifecycle as they can meaningfully run, because when a flaw is found decides how much it costs to fix. Caught in a pull request, a vulnerability is a small edit by the person who wrote it, with full context, before it ships. Caught in production, the same flaw is an incident and an investigation. In practice we place secrets scanning and static analysis at the commit and pull-request stage, dependency and container scanning in the build, and dynamic analysis against staging on a cadence: layered gates each catching what they are best at, at the earliest point they can. The effect is that discovery happens at the cheap end of the curve by default.
We handle sensitive data and have a compliance requirement, is this enough on its own?
It is a large and necessary part of the answer, and often the part that is missing. A pipeline that scans code, dependencies, secrets and images on every change gives you both real vulnerability management and the evidence trail that frameworks like SOC 2 and ISO 27001 and customer security questionnaires ask for: what was scanned, what was found, what was fixed. But "enough" depends on your risk: for genuinely sensitive data most frameworks and prudent practice also expect periodic human penetration testing, secure architecture and access controls, and an incident response capability. We will tell you honestly which of those this service covers and which sit alongside it, so you are not treating a scanning pipeline as the whole of a security programme when your data warrants more.
Thinking about Security Testing?
Tell us the problem in your own words, not in requirements. A senior engineer reads it and comes back with a straight view on whether Security Testing is the right answer here, or what would be.
- 01A senior engineer reads it. Not a form queue, and not an account manager.
- 02We reply either with questions or with a straight answer that we are not the right fit.
- 03If it looks like a fit, a technical call with the person who would actually run the delivery.
- 04Then scope, effort and risk in writing, before anyone signs anything.