Find out in minutes. Point MILLENNIUMS.AI at your app — no dashboards to learn, no attack scripts to write — and see exactly what happens, from first probe to a one-click fix pull request.
Every reason teams run a pentest, turned from a slow, expensive project into something that happens on every release.
Logic flaws, chained exploits, and broken authorization — the bugs a generic scanner walks past. Autonomous adversarial testing, with certified CREST/OSCP human review on demand, finds them and proves each with a working exploit. Catching one early beats explaining a breach.
PCI DSS, SOC 2, ISO 27001, and HIPAA all require regular pentesting. One scan produces an audit-ready Compliance Report mapped to your controls — evidence in minutes instead of a five-figure engagement and a six-week wait.
B2B buyers want a fresh, third-party pentest report — an "attestation of clean health" — before they sign. Hand them one on demand, and protect the brand from the single breach that can erase customer trust overnight.
A flaw caught in a pull request costs a fraction of one patched in production after an incident. Scan every release, take the one-click fix PR, and keep the pentest records cyber-insurers ask for to grant coverage or lower your premium.
Security that runs on every change, not once a year — so a new feature can't quietly reopen an old hole. Every finding comes with reproducible, plain-English detail that teaches your developers to ship more secure code next time.
A staging URL, a repo, or an API endpoint. Register it once and scan on demand, or let it run on every pull request and once a week.
Autonomous agents probe the AI attack surface — prompt injection, tool and agent abuse, data leakage, RAG flaws, runaway cost — in an isolated sandbox that's destroyed when the scan ends. Nothing to run, nothing to watch.
Not a CVSS guess — an attack that actually fired, with the exact steps to reproduce it. Unproven leads are held in a separate review bucket, so you only triage what's real.
Each finding comes with a plain fix and, when you want it, a draft PR your engineers review before it lands. Nothing merges on its own.
A scoped scan runs on each AI-surface pull request and blocks the merge on a proven, net-new vulnerability. Recurring findings are de-duplicated, so the pipeline stays quiet until something real appears.
Every completed scan writes a full penetration test report — the document a pentest firm hands you — with each finding mapped to the standard you answer to: OWASP LLM Top 10, SOC 2, ISO 27001, ISO 42001, NIST AI RMF, PCI DSS 4.0 Req 11.4. Plus a redacted attestation letter you can send a customer without an NDA, and the same report as JSON for Vanta, Drata or Secureframe.
The engine tests every category on the industry-standard AI-security checklist. The full matrix is published live on the Trust Center. See it →
Your AI app is only as trustworthy as what it's built on, and most of that comes from outside your codebase: third-party foundation models, fine-tuned weights, training and RAG datasets, plugins, and the ML/LLM libraries in your stack. A poisoned model, a backdoored dataset, or a vulnerable ML dependency can compromise you before you write a line of code. This is OWASP LLM03:2025 Supply Chain.
Risk from the AI components you depend on — untrusted model sources, over-trusted plugins, and known-vulnerable ML/LLM dependencies.
The scan inspects where models and data come from, how plugins are wired, and the dependency tree — then triages CVEs by real exploitability (CISA KEV / EPSS) and reachability, so you see what matters.
Supply-chain compromise bypasses your app-level controls — it's on the OWASP LLM Top 10 for exactly that reason. Different from Shadow-AI discovery, which inventories where AI is used.
Tools: osv-scanner for dependency CVEs + EPSS / CISA-KEV / reachability triage; findings map to OWASP LLM03 and MITRE ATLAS AI Supply Chain Compromise (AML.T0010).
Beyond the app, the same engine checks your cloud posture for the exposures attackers hunt for: public buckets, over-broad IAM, ports open to the world, unencrypted data, and blind spots in your audit trail. Each finding is CVSS-scored with a plain fix.
Example findings. Connect a read-only role and we assume it, enumerate read-only, and check your posture — CVSS-scored, mapped to your compliance frameworks. No keys, no write access.
Define a scope, prove you own it, sign the rules — then the engine works the four steps of a real network pentest. Every action is bucketed into a three-tier safety model, so automated offensive testing stays safe to run.
Gather data and map the digital footprint — mostly passive.
Find open ports and active services, then confirm what's exposed.
Test weak points to gain access — human-approved per target.
Document flaws with proof, and hand over the fix.
Live: external + internal-network connector, confirm-only and credentialed, plus rate-capped Tier-2 sweeps — all gated by proven ownership + a signed RoE, with an always-visible Emergency Stop. Tier-3 exploitation ships as a human-gated, non-destructive framework, disabled by default.
Pick a monthly plan, add scans as you grow, or run it in your own cloud — no per-seat tax, no annual lock-in. Full pricing details →
A free scan. You'll have a real, provable finding in minutes.