Exclusive Report · 2026

The State of
AI Engineering Security

A deep look at what AI coding assistants are shipping into production — and the ASPM playbook that catches it. 38 pages of benchmarks, case studies, and remediation patterns.

WHAT IS INSIDE

38 pages of benchmarks, case studies, and remediation patterns.

AI-coding benchmarks

A 1,200-PR side-by-side of what Cursor, Claude Code, Copilot, and Devin ship into real repos — and how often those PRs introduce a CWE-285, CWE-89, or CWE-22.

ASPM playbook

The four-layer review pattern that catches what AI-generated code misses: graph-aware SAST, reachability analysis, replay-verified findings, and a human-reviewable audit trail.

Three case studies

How three engineering teams cut their AI-coded vulnerability backlog by 78%, 84%, and 91% in one quarter — including the rollout plan they used and the metrics they watched.

EU compliance map

A practitioner-grade mapping from AI-coding risks to NIS2 Art. 21, DORA Art. 28, the EU AI Act, and the Cyber Resilience Act — with the evidence each regulator expects.

WHO IT IS FOR

Built for the people who own AI-coded production risk.

CISOs and Heads of Security

A board-ready view of what AI coding assistants are shipping into your codebase and the playbook to bring it under control in 90 days.

Application-security teams

The benchmarks, reachability patterns, and remediation templates that compress your review backlog without dropping the findings that matter.

Platform and DevEx leaders

How to keep AI-coding velocity high while the audit trail stays auditable — including the IDE- and CI-level guardrails the case-study teams standardised on.

Compliance and GRC

The NIS2 / DORA / EU AI Act / CRA mapping your regulator will ask about, with the evidence artefacts each framework expects.

GET THE REPORT

Read it before your next AI-generated PR ships.

Free 38-page PDF. No signup wall, no email-gate before the table of contents.

Qualification

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SAMPLE HANDOVER · ILLUSTRATIVE

Sample evidence handover

A trimmed view of what your team receives at the end of an AI Swarm Pentest engagement. Real engagements include full technical evidence, executive narrative, and a remediation plan.

VALIDATED FINDING Evidence attached

Server-Side Request Forgery in webhooks/receiver

demo-project/sample-app · src/webhooks/receiver.py:42

SeverityHigh CVSS 3.18.6 Priority79 Confirmedvia replay

Untrusted caller-supplied URLs reach an internal egress without an allowlist. Replayed in a sandbox against a fresh authorised target — the same control was validated to fail twice.

REVIEWER-READY REMEDIATION Merge-ready PR

Validate the target URL against an allowlist of permitted hostnames. Reject private/internal IP ranges. Enforce HTTPS only.

plexicus/remediation/webhooks-ssrf 3 changed · 0 new files
42resp = requests.get(target_url)
42+if not is_allowed_host(target_url):
43+  raise WebhookRejected(target_url)
44+resp = requests.get(target_url, timeout=5)
Every engagement hands over:
  • Executive briefing
  • Validated findings list
  • Merge-ready PRs
  • Compliance mapping (NIS2 · DORA · CRA)