Why Security Professionals
Trust AutoCyber AI
Every AutoCyber AI solution is built from the ground up for organizations where security, privacy, and trust are non-negotiable.
"Built for trust. Designed for control."
These security measures apply to all AutoCyber AI products: WASA AI, NAD AI, SecureEasy AI, and any future solutions we develop.
Local-First Architecture
All data processing happens on your infrastructure. No mandatory cloud dependencies for core operations. Sensitive information, scan results, and learned patterns never leave your environment by default.
Local-first architecture reduces exposure, simplifies compliance, and ensures your security posture is enforced by design - not policy.
No Data Resale - Ever
Your data is yours.
AutoCyber AI does not sell, share, or monetise customer data
No third-party analytics or advertising integrations
No hidden monetisation models
Data remains portable and exportable - no vendor lock-in
Transparency by Design
No Hidden Telemetry
Transparency by design. No silent data collection, background uploads, or undocumented tracking. All telemetry is strictly opt-in. Customers retain full visibility and control over what is shared. Every outbound connection and data transmission can be audited.
Optional Air-Gapped Deployments
Maximum isolation for critical environments.
AutoCyber AI solutions can be deployed in fully air-gapped networks with zero external connectivity. Local LLM inference, scanning, reporting, and analysis operate entirely offline. No update checks, licence validation, or telemetry are required in air-gapped mode.
This enables secure use in classified, regulated, or high-assurance environments.
Air-Gapped Mode Features
Secure Defaults
Security is the default, not an afterthought.
Encrypted Storage
Secrets and credentials are stored locally and encrypted at rest
Sandboxed Execution
Tools and operations are sandboxed within isolated virtualised environments
Explicit Authorization
Sensitive operations never execute without explicit user consent
Protected Credentials
API keys and credentials are never exposed to untrusted processes
Framework Alignment
Built-in enforcement aligned with NIST, OWASP, and MITRE frameworks
Safe by Design
Every feature is built with security as the primary consideration
OWASP Compliance
Our solutions are designed with awareness of and mitigations for the OWASP Top 10 for LLM Applications and the OWASP MCP Top 10 - the most critical security vulnerabilities in AI systems.
OWASP Top 10 for LLM Applications (2025)
The most critical security vulnerabilities in Large Language Model applications. AutoCyber AI products are designed with built-in mitigations for each of these risks.
Manipulating LLMs via crafted inputs leading to unauthorized access, data breaches, and compromised decision-making.
Our Mitigation: Input validation, prompt sanitization, context isolation, and output filtering
Neglecting to validate LLM outputs may lead to downstream security exploits, including code execution.
Our Mitigation: Output encoding, sandbox execution, and strict type validation
Tampered training data can impair models leading to responses that compromise security, accuracy, or ethical behavior.
Our Mitigation: Data provenance tracking, integrity verification, and anomaly detection
Overloading LLMs with resource-heavy operations can cause service disruptions and increased costs.
Our Mitigation: Rate limiting, resource quotas, and input size constraints
Depending on compromised components, services or datasets undermines system integrity.
Our Mitigation: Dependency scanning, SBOM generation, and verified sources
Failure to protect against disclosure of sensitive information in LLM outputs.
Our Mitigation: Data classification, output filtering, and access controls
LLM plugins processing untrusted inputs with insufficient access control risk severe exploits.
Our Mitigation: Plugin sandboxing, least privilege, and input validation
Granting LLMs unchecked autonomy to take action can lead to unintended consequences.
Our Mitigation: Human-in-the-loop controls, action boundaries, and approval workflows
Failing to critically assess LLM outputs can lead to compromised decision making.
Our Mitigation: Confidence scoring, uncertainty indicators, and human review
Unauthorized access to proprietary models risks theft and dissemination of sensitive information.
Our Mitigation: Access controls, watermarking, and deployment hardening
Sources: OWASP LLM Top 10 | OWASP MCP Top 10
Full Traceability for Every Action
Auditability & Transparency
Full traceability for every action. Every scan, tool execution, and AI-assisted decision is logged. Structured audit trails support internal reviews and external compliance audits.
Decision reasoning and execution context are available for inspection - no opaque black boxes.
Our Security & Trust Commitment
No Vendor Lock-In
Customers always retain ownership and export rights
Open Security Architecture
Clear trust boundaries and documented deployment models
Continuous Security Posture
Regular internal reviews, third-party assessments, and responsible disclosure
Ethical AI
Responsible usage guidelines and governance controls embedded into every product
These Principles Apply Across All Products
Every AutoCyber AI solution inherits these security foundations.
WASA AI
AvailableNAD AI
AvailableSecureEasy AI
Coming SoonChoosing AutoCyber AI means choosing a platform built to respect your security boundaries, your data ownership, and your operational trust requirements.