AI-Native Security

Our AI learns what your product should do. Then finds everything it shouldn't.

Every request looks valid. Every response checks out. But your business rules are being violated - and no scanner will ever catch it.

⚠

AI agents and attackers already reason about your business logic. MCPs, autonomous agents, and sophisticated threat actors reason about your business rules and exploit them - not just the inputs and known CVEs that scanners catch. Your product's security is now exposed to the full capabilities of modern AI. Who's checking for the logic flaws that don't have signatures?

The Problem

Scanners match patterns.
Modern attacks exploit logic.

AI agents, MCPs, and autonomous tools explore your APIs, map your workflows, and chain actions at machine speed. Your product's security is now exposed to the full capabilities of modern AI. The flaws they find aren't in any vulnerability database, pattern-matching tools and CVE scanners miss them entirely.

Traditional Security Tools

Pattern matching on autopilot

Conventional scanners check for known signatures without understanding your application's purpose or intended behavior.

Checks against static CVE databases
No understanding of business context
Tests endpoints in isolation
Can't reason about feature interactions
Misses semantic and workflow violations

Anomity AI

Learns. Reasons. Reveals.

Our AI builds a semantic model of your product, then thinks adversarially to find vulnerabilities humans would miss.

Understands what your product should do
Maps workflows, features, and permissions
Tests feature interactions and edge cases
Chains behaviors like a real adversary
Finds violations of business intent

What We Find

Business logic flaws that scanners miss

Our AI builds a semantic model of your product's business logic - exploring from the outside, mapping APIs, workflows, permissions, and business rules. It understands your product's intended behavior, then systematically uncovers flaws where every request looks valid, but the behavior violates your product's rules.

Feature Interaction

Gift card converted to cash

Three unrelated features: gift cards, refunds, and wallet withdrawals. Our AI bought a $500 item with a gift card, requested a refund "to wallet" instead of back to gift card, then withdrew to a bank account. Gift card → cash. Repeat infinitely.

Money laundering, revenue loss

Why scanners miss this

Each action is valid: purchase, refund option, withdrawal. Scanner tests endpoints in isolation. Our AI understood the business intent: gift cards shouldn't be convertible to cash. It mapped feature interactions and found the emergent money flow.

State Persistence

Terminated user still has access

User A shares a document with User B as "Editor." User A then removes User B from the organization entirely. Our AI checked: User B's edit token for that document was never revoked. Write access persists — months after termination.

Data breach, insider threat

Why scanners miss this

Current permission check passes — token is valid, role is cached. Scanner sees authorized request. Our AI understood the expected lifecycle: org removal should cascade to all shared resources. It tested what happens when access should be revoked.

Rule Combination

45% discount past the 25% cap

Three discount types: referral (10%), first-order (15%), promo codes (20%). Business rule: max 25% combined. Our AI applied them in sequence, then updated profile mid-checkout to re-trigger first-order. Final discount: 45%. Cap only checked at initial calculation.

Revenue loss at scale

Why scanners miss this

Each discount applies correctly. Scanner tests each in isolation. Our AI understood the business constraint: 25% max total. It tested every permutation and ordering, finding that mid-checkout changes bypass the cap validation.

Separation of Duties

Same person, different role hat

Your expense system requires manager approval. Users can't approve their own submissions. Our AI noticed users can hold multiple roles. It submitted an expense as "Sales Rep," switched to its "Regional Manager" role, and approved the same expense. Check passed: different role IDs.

Fraud, SOX compliance violation

Why scanners miss this

Submit: authorized. Role switch: valid feature. Approve: manager has authority. Scanner sees correct authorization at each step. Our AI understood the business intent: the same person can't approve their own expenses, regardless of which role they're wearing.

Permission Inheritance

Viewer escalated to data owner

User A creates a project, adds User B as viewer. User B creates a sub-task within that project — which the UI allows. Our AI discovered: sub-task creator automatically becomes "owner" of that object, with permission to invite others and export data.

Data exfiltration, access escalation

Why scanners miss this

Create sub-task: authorized for viewers. Creator becomes owner: per-object behavior. Scanner sees valid permission model. Our AI understood the intended hierarchy: project "viewer" shouldn't gain ownership rights. It mapped how permissions inherit — and inflate.

Delegation Chain

"View only" became "full export"

Admin delegates limited "view reports" to User B. User B delegates to User C — and adds "export" capability that B doesn't even have. Your system allows delegators to expand permissions they were given. Our AI chained four delegations: view → full data export.

Data breach, privilege escalation

Why scanners miss this

Each delegation is authorized by someone with the permission. Scanner sees valid delegation at each step. Our AI understood the business intent: delegated permissions shouldn't be re-delegatable or expandable. It mapped the full delegation graph.

How It Works

Continuous agentic business logic security - from the outside

Our AI learns your product

Anomity explores your application from the outside, building a semantic model of APIs, workflows, permissions, and business rules - no integration or internal access needed.

Our AI finds what shouldn't happen

Using the semantic model, our AI reasons about intended behavior, then systematically tests workflow bypasses, feature interactions, permission boundaries, and state edge cases.

You get findings + remediation

Receive detailed vulnerability reports with reproduction steps and remediation guides via email and dashboard, on every change.

The Team

Built by veterans

We've spent 15+ years in the trenches - shipping production systems, publishing academic research, and keeping infrastructure secure at scale.

Engineering

Built and scaled enterprise-level production products. We know how real applications work - and how they break under pressure.

Research

With computer science PhDs in the team, we bring academic rigor to real-world problems.

Fortune 500 Security

Experienced in finding and disclosing vulnerabilities in enterprise systems. We've seen how the biggest companies fail - and how to prevent it.

DevSecOps

Operated infrastructure at scale. We understand the real-world constraints security solutions must work within.

15+ years building production systems · Combined expertise in engineering, research, and operations.

Apply for Access

Deploy AI-native security to beat agentic adversaries

Currently in private beta. We're partnering with forward-thinking security teams to adapt security to the AI era. Fill out the form below to apply for access.

We'll reach out within 48 hours to discuss your security needs.

Our AI learns what your product should do. Then finds everything it shouldn't.

Scanners match patterns.Modern attacks exploit logic.

Pattern matching on autopilot

Learns. Reasons. Reveals.

Business logic flaws that scanners miss

Gift card converted to cash

Terminated user still has access

45% discount past the 25% cap

Same person, different role hat

Viewer escalated to data owner

"View only" became "full export"

Continuous agentic business logic security - from the outside

Our AI learns your product

Our AI finds what shouldn't happen

You get findings + remediation

Built by veterans

Engineering

Research

Fortune 500 Security

DevSecOps

Deploy AI-native security to beat agentic adversaries

Scanners match patterns.
Modern attacks exploit logic.