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Tools like Copilot, Cursor, and Claude Code allow developers to generate applications faster than ever before. Features that once took weeks to build can now appear in hours.
But security hasn’t kept up.
Applications are being created faster than security teams can review them. At the same time, AI systems introduce entirely new attack surfaces from prompt injection and data leakage to unsafe agent actions.
The security playbook built for traditional software isn’t enough anymore. Most risks are introduced at the architecture level long before code is tested.
Security programs built for traditional software are slow, expensive, and often ineffective.
As an AI-native application security company, we45 helps organizations secure modern applications, APIs, cloud environments, and AI systems faster, more effectively, and at a lower cost.
By combining AI-powered security technology with deep security expertise, we deliver faster feedback, broader security coverage, and early visibility into architectural risks before they reach production.
Because traditional application security was never built for AI-era software anyway.
Fixes sit unvalidated while new code keeps shipping
Fixes are validated as soon as changes are made
Findings are outdated before teams can act on them
Testing reflects the current state of the application
Issues are marked fixed without clear validation
Validation is backed by clear, testable evidence
Testing cycles fall behind release cycles
Testing stays aligned with how often code ships
Identify architectural risks early so design flaws don’t make it into production systems.
TMaaS engagements are powered by SecurityReview.ai, enabling scalable threat modeling and earlier risk discovery during system design.
Security designed for modern AI-powered applications and systems.
Built to uncover how your system actually behaves at the architecture level including trust boundaries, data flows, integrations, and AI system interactions where most critical risks originate.
Continuous security testing across modern applications, APIs, and cloud environments.
PTaaS engagements are powered by o2, enabling faster testing cycles, validation-driven retesting, and stronger evidence for security teams.
Threat modeling and security design reviews that scale with modern software development.
SecurityReview.ai helps you analyze architectures, identify design-level risks early, and validate how your system behaves before it’s built or deployed.
Hands-on security training designed for real engineering teams.
AppSecEngineer gives developers and security teams practical training across application security, cloud security, AI/LLM systems, and web3 so security issues don’t get written into your code in the first place.
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Organizations launching AI applications need to understand the risks across models, agents, and AI-powered workflows before they reach production.
Security testing designed for modern AI applications, APIs, and orchestration layers to identify vulnerabilities traditional pentests miss.
Engineering teams ship faster than security reviews can keep up. TMaaS powered by SecurityReview.ai enables scalable design-stage security.
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Teams adopting tools like Copilot, Cursor, or Claude Code need guardrails, architecture guidance, and security validation.
we45 contributes to the global security community through research, training, and hands-on security engineering.
Our team trains security professionals at major conferences including Black Hat and RSA Conference, and SecurityReview.ai was recently recognized with the SANS Difference Maker Award for advancing modern security practices.
Threat models delivered across modern software architectures
Threat models delivered across modern software architectures
Vulnerabilities discovered across applications, APIs, and cloud environments
trained through AppSecEngineer
AI-native application security focuses on protecting modern software environments that include AI models, AI agents, and AI-powered applications. It combines traditional application security practices with testing methods designed for AI systems and architectures.
AI pentesting evaluates risks specific to AI-powered systems such as prompt injection, model manipulation, data leakage, and agent misuse. Traditional pentesting focuses primarily on web applications and APIs
Threat modeling is most effective early in the development lifecycle, when architecture decisions are still being made. It helps teams identify potential attack paths and security risks before systems reach production.
Yes. we45 helps organizations secure AI-powered applications, AI agents, and modern cloud-native systems through AI-native pentesting, security architecture reviews, and threat modeling.
Security built for the age of AI-powered software.
Talk to an AI Security Expert
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