Startup shipping fast with AI coding assistants
A London startup using Copilot heavily across the team gets guardrails specifically tuned to catch the insecure-default patterns AI assistants tend to suggest, before they reach production.
AI Code Security & Supply Chain in the UK
CyberSecurity · United Kingdom
AI code security and supply chain protection in the UK from 4hosting covers the code you and your AI coding assistants write, and everything that code depends on: SAST and DAST scanning with LLM-assisted triage to cut noise, secret scanning before a credential reaches a commit, SBOM and dependency scanning, and signed container images. Built as pre-commit and CI gates, so issues get caught before deployment, not after.
- SAST/DAST with LLM triage to cut false positives
- SBOM, dependency and secret scanning wired into CI
- Guardrails specifically for AI-generated code patterns
- Application code, dependencies, containers and IaCScope
- 1–8 h/month on VPS; 5–10 h/month on dedicated servers depending on the plan; 10 h/month on GPU serversIncluded hours
- Pre-commit and CI/CD gatesDelivery
- EUR, with UK VAT (20%) itemised on the invoiceBilling
01
What gets scanned, and where
Static analysis (SAST) catches insecure patterns in source code before it ships; dynamic analysis (DAST) tests the running application for issues static analysis can't see. Secret scanning stops API keys and credentials from ever landing in a commit, ideally as a pre-commit hook rather than after the fact. Infrastructure-as-code scanning checks Terraform and similar configs for the same class of misconfiguration issues that cause real breaches.
- SAST and DAST as CI/CD gates, not a one-off pre-launch scan
- Secret scanning at the pre-commit stage
- IaC scanning for Terraform and similar configuration
02
Why AI-generated code needs its own guardrails
Code written or heavily assisted by tools like Copilot ships faster, but studies of AI-generated code have repeatedly found a higher rate of specific vulnerability classes — insecure defaults suggested confidently, outdated dependency versions, and copy-pasted patterns from training data that were never security-reviewed in the first place. We add guardrails specifically tuned to these patterns, on top of standard SAST rules that were never designed with AI-assisted authorship in mind.
03
LLM-assisted triage, and the supply chain beyond your code
A raw SAST scan produces a high volume of findings, many of them false positives specific to your codebase's patterns. LLM-assisted triage reviews each finding in the context of your actual code before it reaches an engineer, cutting the noise substantially. On the supply chain side, we generate a Software Bill of Materials for every build, scan dependencies for known vulnerabilities, and sign container images so a tampered image can be detected before it deploys.
- LLM-assisted triage filters SAST findings before human review
- SBOM generated per build, with dependency vulnerability scanning
- Signed images (cosign) with SLSA-aligned provenance
04
Where the included hours go
Pipeline setup and remediation draw on the CyberSecurity hours in your plan: 1–8 hours a month on VPS, 5–10 on dedicated servers depending on the plan, 10 on GPU servers, from Advanced upward on cPanel. You request the setup, or a review of an existing pipeline, from the client panel, propose a timeframe, and we deliver against it. Hours do not roll over into the following month, so we plan larger pipeline work around your release schedule; anything beyond the monthly quota is still accepted, billed separately.
How we work
Request from the panel
Open a request under Services describing your repositories, CI pipeline and whether AI coding assistants are in use.
Wire in the scanning gates
We add SAST/DAST, secret scanning and SBOM generation as pre-commit and CI gates, confirming the included hours used.
Triage and tune
We tune LLM-assisted triage against false positives specific to your codebase, so the gate blocks real issues, not noise.
Document and hand over
You get the pipeline configuration, an SBOM per build, and documentation for extending the gates as the codebase grows.
Use cases
SaaS vendor with a large dependency tree
A SaaS company with dozens of npm and pip dependencies gets automated SBOM generation and dependency scanning wired into CI, catching a newly disclosed CVE in a transitive dependency within the pipeline.
Agency shipping client projects on a deadline
A development agency gets secret scanning at the pre-commit stage across all client repositories, stopping a credential leak before it ever reaches a public or shared repo.
Technology stack
- Semgrep
- gitleaks
- Syft
- Grype
- cosign
- checkov
- SLSA
- OWASP ZAP
Every subscription includes monthly DevOps, CyberSecurity and Programming hours: 1 h from the cPanel Advanced plan up, 1–8 h on VPS, 5–10 h on dedicated servers depending on the plan, and 10 h on GPU servers. Hours are requested from your client panel, don't roll over to the next month, and anything above the quota is accepted and billed separately.
Frequently asked questions
Is this the same as securing an application that uses an LLM?
No — that's LLM & AI Application Security, a separate service covering apps that call an LLM at runtime (prompt injection, data leakage). AI Code Security & Supply Chain is about the code itself, including code written with AI coding assistants like Copilot, and everything that code depends on.
What specifically goes wrong with AI-generated code?
Studies of AI-assisted coding tools have found elevated rates of insecure defaults suggested confidently, outdated or vulnerable dependency versions pulled in without review, and patterns copied from training data that were never security-reviewed. Standard SAST rules weren't designed with this authorship pattern in mind, which is why dedicated guardrails matter.
What is an SBOM and why does it matter?
A Software Bill of Materials lists every component and dependency in a given build. It matters because when a new CVE is disclosed for a specific library version, an SBOM lets you immediately check which of your deployments are affected, instead of manually auditing every project.
Does secret scanning stop a credential that's already been committed?
Pre-commit scanning stops it before the commit happens, which is the strongest protection. We also scan existing commit history to catch credentials already committed in the past, and flag them for rotation — since removing a file doesn't remove it from git history.
How does LLM-assisted triage avoid becoming its own black box?
Triage results include the reasoning for why a finding was marked as a false positive or genuine issue, so an engineer can review the logic rather than trusting an opaque verdict. Findings marked genuine always go to a human before any gate blocks a deployment.
Can this be added to an existing CI/CD pipeline, or does it require rebuilding it?
It's designed to be added as gates within your existing pipeline — GitHub Actions or GitLab CI — rather than requiring a rebuild. We scope the integration to your current setup during the request stage.
Want AI-aware code and supply-chain scanning in your pipeline?
Tell us about your repositories and CI setup and we'll wire in the gates using your included CyberSecurity hours.