Spoofing · Tampering · Repudiation · Information disclosure · Denial-of-service · Elevation of privilege. We decompose your system into trust boundaries and enumerate threats by category.
Most software shipped to the cloud is written with AI and never validated. Real security reviews cost $10k–$100k, so founders and indie builders ship to prod and hope nothing breaks.
Point VELO at your GitHub repo. You get a full vulnerability report and a remediation plan — then hand it to Claude Code (or any coding agent) and say “read this and apply the fixes.”
Get a deterministic security-scan quote in seconds — and pay only when you’re ready.
Paste any public GitHub repo. We size it, pick a panel of 6–11 specialist agents covering Azure, AWS, GCP, Kubernetes, IaC, AppSec, AuthN/Z, API surface, AI/LLM defense, prompt injection, and compliance — and quote you a single price. Same project today and tomorrow → identical quote.
Curious what you get? Browse an example report ↗
Expert frameworks, run deterministically
Every scan applies the same battle-tested methodologies a senior security architect would — codified as deterministic agent pipelines so the analysis is rigorous, reproducible, and auditable.
Findings are mapped to ATT&CK tactics (Initial Access, Execution, Persistence, Privilege Escalation, Defense Evasion, Lateral Movement, Exfiltration) so your team can prioritize against real-world attacker behavior, not theoretical CVSS.
Web Top 10, API Top 10, and ASVS Level 2 controls applied to your auth flows, session handling, input validation, access control, cryptographic storage, SSRF surface, and dependency hygiene.
Prompt injection, insecure output handling, training-data poisoning, model denial-of-service, supply-chain risks for models & embeddings, sensitive-info disclosure, agentic tool-abuse, excessive autonomy. Triggered automatically when we detect LLM SDKs.
CIS controls for Azure, AWS, GCP, Kubernetes, and Docker applied to your IaC: storage account public access, over-permissive IAM, unencrypted volumes, exposed metadata endpoints, container privilege escalation.
Secure Software Development Framework practices for SDLC, and PASTA (Process for Attack Simulation & Threat Analysis) for risk-aligned modeling — so findings map back to business impact, not just code smell.
Privacy-first by design
We built VELO assuming you wouldn’t trust us with your code — so we made sure you don’t have to.
We don’t store your code
Source is fetched, analyzed in an ephemeral sandbox, and discarded immediately after the scan completes. Nothing is written to disk, no embeddings are kept, no copy persists in any database.
Data sanitization before the model sees anything
A deterministic pre-processor strips secrets, API keys, tokens, .env values, IP addresses, internal hostnames, employee emails, and customer PII before any payload reaches an LLM or agent. We test the sanitizer with adversarial canaries on every release.
Reports auto-delete after 90 days
Your generated report is yours. We retain it for 90 days so you can revisit it, then it’s cryptographically shredded from our storage. Export it anytime — once it’s gone from our side, it’s gone.
Never trained on, never sold
Your code and reports are never used to train models, fine-tune agents, or sold to any third party. No advertising, no data brokers, no “anonymized” datasets shipped to partners.
Zero environment exposure
We don’t need — and we don’t accept — production credentials, cloud account access, network topology, or anything that could enumerate your live environment. We work from the artifact, not the runtime.
Auditable, deterministic, reproducible
The same input produces the same scan. Every finding traces back to a specific rule, a specific file, and a specific framework citation — so you can verify what we said, and regulators or customers can too.
Full details: Privacy Policy · Terms
The Dark Ages of Cybersecurity have begun
Anthropic’s foundational research on alignment and model behavior — the body of work some call the Claude Mythos — was unambiguous about one thing: as foundation models become more capable, they amplify both attackers and defenders. We are entering a period of rapid, asymmetric capability growth where the gap between offense and defense is widening — fast.
- $20A junior attacker with a $20 API key can now generate working exploits, deepfake credentials, and adaptive social-engineering campaigns at industrial scale.
- 5–7×LLM-generated phishing converts at 5–7× the rate of human-written campaigns, with personalization at scales previously impossible.
- NewPrompt injection, model theft, training-data poisoning, and agentic tool-abuse are entirely new classes of attack — with no traditional defense playbook and no CVE feed to subscribe to.
- ⏱The window between capability published and capability weaponized has compressed from years to weeks. Patch cycles haven’t.
Companies that prepare now — by modeling AI-specific threats, hardening their LLM gateways, and shifting security left into design and code review — will weather the transition. Companies that wait for incidents will fund the war on themselves.
VELO exists so the right side of that line is reachable for anyone.
Simple, fair pricing
Pay-as-you-go starts at $49 per scan for small repos, scales to ~$67–$87 for mid-size projects, and ~$150–$400+ for large multi-cloud or AI-heavy codebases. Subscribe for an automatic monthly credit and a discount on every scan.
- Standard scan pricing — from $49 per scan
- No subscription required
- Credits valid 90 days from deposit
- Failed scans auto-refund to wallet
- 20% off every scan
- $99.00 auto-credited each month
- Credits valid 90 days from deposit
- Failed scans auto-refund to wallet
- 28% off every scan
- $198.00 auto-credited each month
- Credits valid 90 days from deposit
- Failed scans auto-refund to wallet