AI multiplied code output, not security understanding
AI coding tools scale whatever patterns exist - including insecure ones - increasing attack surface faster than signal.
Security at engineering speed
Neo is an AI security copilot built for a world where software is continuously generated, changed, and shipped - applying reasoning, memory, and real execution across the delivery lifecycle.
Trusted by 100k+ security professionals
AI fundamentally changed how software is built.
Security architecture didn't change with it.
Generative AI is accelerating software delivery. Gartner predicts that 75% of enterprise software engineers will use AI code assistants by 2028; up from just 10% in 2023. That speed increase compounds security workload - even when security tooling stays the same.
Applications are now logic-heavy and constantly changing
Authorization and business logic break, and PR reviews + threat models can't keep up with continuous delivery
Scan-and-report tools hit an architectural ceiling
They detect patterns, not behavior, and cannot reason about intent, exploitability, or context.
Security lifecycle, end to end
Neo connects inventory, modeling, testing, triage, and remediation into one continuous workflow—so teams ship faster with confidence.
Design & Threat Modeling
1/5
Design & Threat Modeling
Continuously model risk as systems and features evolve.
How Neo Helps
- Observes services, APIs, auth flows, and trust boundaries as they’re designed
- Reasons about how new features change the attack surface
- Preserves architectural decisions, accepted risks, and prior threats as memory
Outcome Signal
Threat modeling shifts from a one-time meeting to a living security feedback loop.
Code & PR Security Review
Security review at pull-request speed, without slowing developers.
What Neo does here
- Reviews PRs and feature changes with full codebase and architectural context
- Identifies security-relevant changes, not just vulnerable patterns
- Produces actionable fix guidance and escalates only what matters
Outcome Signal
Security feedback moves from days to minutes, without becoming a bottleneck.
Runtime Validation
Prove what’s actually exploitable in real environments.
What Neo does here
- Executes attacker-realistic testing against running applications
- Reasons about auth, authorization, and business logic
- Validates exploitability with concrete evidence, not theory
Outcome Signal
Teams focus on real, reachable risk instead of chasing false positives.
Exposure Analysis
Understand what’s exposed as infrastructure and deployments change.
What Neo does here
- Discovers assets, services, and exposure paths dynamically
- Correlates reachability, ownership, and criticality
- Retains memory of drift, mitigations, and known constraints
Outcome Signal
Infrastructure risk is discussed in terms of exposure and impact, not static inventories.
Remediation Tracking
Turn findings into executable remediation work.
What Neo does here
- Deduplicates and correlates findings across tools and workflows
- Prioritizes based on exploitability and exposure
- Tracks remediation outcomes and retests automatically
Outcome Signal
Backlogs shrink because teams work on what actually reduces risk.
Design & Threat Modeling
Continuously model risk as systems and features evolve.
How Neo Helps
- Observes services, APIs, auth flows, and trust boundaries as they’re designed
- Reasons about how new features change the attack surface
- Preserves architectural decisions, accepted risks, and prior threats as memory
Outcome Signal
Threat modeling shifts from a one-time meeting to a living security feedback loop.
Autonomous execution
Neo adapts as systems change. The model and test techniques update, and the work continues; without restarting from scratch.
Security reasoning grounded in system behavior
Neo models how applications authenticate, authorize, and behave from real inputs (API docs, creds, responses), then tests hypotheses like a security engineer would.
Persistent memory across runs
Architecture decisions, prior findings, validation results, accepted risk, and outcomes persist across workflows, so new work builds on what’s already known instead of repeating discovery, setup, and reasoning.
Research-informed security testing
Neo incorporates current security research and emerging attack techniques into its testing and analysis, so teams evaluate systems against real, contemporary threats rather than relying on static assumptions or outdated test cases.
Output quality
Actual security checks—sandboxed execution with evidence you can verify, plus execution context, repro paths, and fix guidance—not speculative output.
Engineered With Guardrails From Day One
Neo runs against the same sensitive assets you're protecting—source code, configs, and security findings—so it's engineered with privacy and defense-in-depth as a top priority. Users get granular guardrails over what Neo can access and execute, plus audit-grade visibility into every action. This is the "hard part" of production security AI that DIY stacks rarely get right.
Privacy-first by design
Neo does not train or fine-tune on your data, and we use LLM providers under zero-retention / no-training agreements. Tenant data is isolated, with configurable retention and auto-deletion controls.
Least-privilege access
Agents only use the secrets and endpoints you explicitly grant. Credentials are injected at runtime, scoped to the task, and are not written to disk or logged. Workflow boundaries prevent accidental cross-task data access.
Isolated execution with real guardrails
When Neo needs to run commands, test payloads, or fetch URLs, it executes in isolated sandboxes. Each task spins up a fresh environment, enforces strict controls around network/system access and resource usage, captures logs and artifacts as evidence, and destroys the environment after completion.
Governance that holds up in audit
Enterprise features include SAML/OIDC SSO, RBAC with custom permission policies, comprehensive audit trails, and network controls (e.g., private connectivity and IP allowlisting). Dedicated infrastructure and data residency options are available for enterprise deployments, with SOC 2 Type II and Data Privacy Framework alignment.
See Neo map your full API inventory.
Schedule a demo, today.
Request a demo
From Nuclei to Neo:
open-source velocity, enterprise-grade control
Nuclei and the ProjectDiscovery community deliver attacker-realistic coverage at open-source speed, finding and validating what's actually out there. Neo turns that momentum into governed AI security workflows, so results are consistent, repeatable, and auditable from design through production.
20+
Open Source Tools
12k+
Nuclei Templates
117k+
Github Stars
100k+
Global Community
Customer stories:
Secure APIs and ship faster
"The biggest win was speed to certainty: Neo surfaced real race-condition and payment-bypass scenarios with step-by-step reproduction, so we didn't have to spend days recreating timing-sensitive bugs manually."
Security Engineering Lead,
Application Security Team at a fast-casual dining chain with over 3,500 locations
“The standout value was confidence at scale: Neo validated cross-account authorization across roles with actionable PoCs and repro steps, so AppSec kept PR reviews and new-feature testing moving.”
Senior Security Engineering Manager,
Application Security Team at a leading Cryptocurrency Exchange Platform
Fits into your stack on day one; No rip-and-replace
Neo plugs into the tools you already run and turns scattered signals into workflows you can execute.
Cloud & Runtime
Source Control
Issue Tracking
