What it is
Scoped, authorized identification and validation of real security issues — across conventional applications and infrastructure, and across AI agent systems specifically, where standard security review often misses agent-specific threats like prompt injection, tool poisoning, and confused-deputy authority escalation. Every finding is reproduced, not assumed, and every material result is reviewed independently before it goes to you.
- Scoped, authorized testing across web, API, network, cloud and container targets
- AI agent-specific threats — prompt injection, tool poisoning, confused-deputy, authority escalation
- CVSS-scored findings with reproducible proof, not severity labels taken on trust
- DevSecOps pipeline gates — SAST, DAST, SCA, IaC and secrets scanning
- Independent review of every material finding before it is reported
Why it matters
A vulnerability scanner's severity label is a starting point, not a verdict — plenty of "critical" findings turn out unreachable in practice, while real exploitable issues hide behind clean-looking code. AI agent systems add a newer class of risk most security reviews are not built to catch at all.
How it could help you
We identify and validate security issues in your application, infrastructure or AI agent system, reproduce each one with real evidence rather than trusting a scanner's severity label, and deliver a CVSS-scored report with a working proof, ranked by real risk, that a technical team or a non-technical stakeholder can both act on.
The problem
Automated scanners generate volume, not confidence — many findings are unreachable, mislabeled, or miss the AI-agent-specific threats a generic scanner was never built to detect.
Who this is for
Teams shipping an application, platform or AI agent capability that needs real validated findings before release, not just a scan report.
Evidence base
-
Applied directly on this website's own production deployment: a tar-slip (path-traversal) vulnerability in a privileged release-staging script was identified and fixed before use, and confirmed against an actual malicious tarball rather than assumed fixed.
https://codevolt.co.uk/capabilities/code-and-application-hardening.html -
Independent CVE reachability discipline applied in practice: dependency-scanner findings on this same deployment were checked against actual code paths (an unused parser, a dormant image-processing dependency) rather than accepted or dismissed on severity label alone.
https://codevolt.co.uk/capabilities.html
Open questions
These are questions CodeVolt is still working through. Naming them is part of the honest framing of this capability.
- Which system or workflow carries the highest real exposure if a hidden authority or trust boundary is crossed — that scopes where assessment effort pays off first.
Prerequisites
- A recorded scope and authorization before any active testing begins — no testing starts without it
- Read access, or an authorized scanning window, appropriate to the target
Risks to hold
- A finding reported without reproduction risks wasted remediation effort on the wrong problem
- AI agent systems in particular can look secure under a normal test and still be exposed to prompt-injection or tool-poisoning paths a conventional review does not check
Discuss this with us
There is genuine thinking behind this capability. If you are working through a similar problem, we would like to hear about it.
Start a conversation We review suitability before agreeing any work.