AI Code Security & Supply Chain
Last verified: June 2026· engagement
We audit AI-generated code for vulnerabilities, license violations, prompt-injection vectors, and data leakage, then set up policy and automated scanning in your CI.
- Outcome
- A security report + scanning infra in CI
- Timeline
- 3–5 weeks
- Pricing
- $20–50k audit, $5–12k/mo monitoring
- Buyer
- CISO, VP Eng
The problem
AI is writing code faster than anyone can review it. Hallucinated APIs, subtle vulnerabilities, secrets in prompts, and license violations are entering your repos daily. Traditional AppSec tooling misses the new failure modes — and your team is moving too fast for manual review alone.
What we do
- AI-aware static analysis in CI: hallucinated packages, missing tests, license violations, secret leakage.
- A prompt-data gateway that redacts PII / secrets before requests hit the model and audit-logs every prompt.
- MCP-server hardening: least-privilege credentials, read-only defaults, audit logs, human-in-the-loop on destructive tools.
- Mapping of new prompt-injection surfaces (agents that read external content and call tools) and mitigations.
How it fits together
What you get
Built on our open source
agentvfs — A workspace runtime and execution boundary for AI agents — guardrails on what an agent can touch.
Common questions about this engagement
Do you work under NDA?
Yes — we sign your mutual NDA before any data or repo access. For audits we prefer read-only access to start; for builds we work in a clean repo under your ownership.
Will we own what you ship?
Always. You own the code, the runbooks, the dashboards. We are explicitly set up to hand off and transition out, not to create dependency.
Vendor-agnostic — what does that mean in practice?
We integrate with what you already run — OpenAI, Anthropic, open-weight models on your cloud, your CI/CD, your observability stack. If a hosted vendor solves it, we will not reinvent it; if a self-hosted tool is the right answer, we will not pretend the hosted one is.
How is this different from a Big Four consulting deck?
We are the engineers doing the work, not analysts handing recommendations to a different team. The deliverable is working software in your repo, not a slide deck.
Can you work with our in-house AI team instead of replacing them?
Yes — most of our engagements pair with an internal owner and ramp them up to run the system after we leave. Many of our best engagements start with "we hired an AI team, help us get them productive."
Guides for this work
How to choose an MCP server development company
The MCP SDK is a weekend's work; the job you're actually hiring for is least-privilege auth, scoping, audit logging, and production hardening on servers that reach straight into your internal systems.
Agentic codingIs your codebase ready for AI agents?
Agents don't fail randomly on a repo — they fail predictably on the same things that slow down human engineers: fuzzy boundaries, missing tests, undocumented conventions. Readiness is just those weaknesses paid down deliberately.
Let’s scope it on a call
Thirty minutes with an engineer. We’ll tell you straight whether this is the right first move for your team.