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About the Project

Inspiration

Artificial Intelligence is rapidly becoming part of enterprise software, healthcare, finance, legal services, customer support, and internal business operations. While organizations are adopting AI faster than ever, one critical challenge remains largely unsolved:

How do you prove that your AI is operating securely?

Most teams can monitor servers, networks, and applications, but they have very little visibility into AI interactions. If an employee accidentally shares confidential information with an AI model, a prompt injection attack manipulates an agent, or sensitive customer data is exposed, organizations often discover the issue only after the damage has already occurred.

Security teams don't just need to know what happened—they need evidence that can withstand security reviews, compliance audits, and enterprise customer due diligence.

That inspired us to build Foxy Audit.

Our goal was to create a platform that helps organizations secure AI systems, preserve privacy, and generate trustworthy evidence that their AI behaved safely.

What We Built

Foxy Audit is an AI Runtime Security & Audit Platform designed for teams building AI-powered applications.

It continuously analyzes AI interactions and helps organizations:

Detect prompt injection and jailbreak attempts.
Identify sensitive information such as PII, API keys, passwords, and confidential data before it reaches an AI model.
Enforce customizable AI security policies.
Generate tamper-evident cryptographic audit evidence.
Produce compliance-ready reports for security teams and auditors.
Verify the integrity of AI interactions without exposing customer data.

One of our core principles is privacy-first security.

Instead of sending customer prompts to our cloud for analysis, Foxy Audit performs security analysis locally whenever possible and only generates the cryptographic evidence required for verification. This minimizes unnecessary data exposure while still providing organizations with verifiable security records.

How We Built It

Foxy Audit was designed as a full-stack AI security platform.

The backend was built using FastAPI with PostgreSQL for data management, while the frontend was developed with React.

Our runtime security engine analyzes AI prompts and responses to identify prompt injection attempts, sensitive data exposure, and policy violations.

Every security event is transformed into a cryptographically linked audit record using chained hashing techniques, creating a tamper-evident audit trail that can later be independently verified.

On top of this security layer, we implemented:

Automated compliance report generation
Organization-level policy management
Audit dashboards
Analytics and reporting
Verification endpoints
Authentication and access control
Evidence management

The result is a platform that not only detects security risks but also produces evidence that organizations can present during enterprise security reviews and compliance audits.

Challenges We Faced

The biggest challenge was balancing three competing goals:

Strong security
User privacy
Practical usability

Many existing AI security solutions require organizations to send prompts to external services for analysis. While convenient, this creates another potential point of data exposure.

We wanted to provide meaningful runtime security analysis without requiring organizations to surrender control of their sensitive information.

Another challenge was defining what an AI audit should actually look like. Traditional logs record events, but they don't provide guarantees that those records haven't been modified after an incident.

Designing a system that combines runtime threat detection with tamper-evident evidence while remaining easy for developers to integrate required significant architectural iteration.

What We Learned

Building Foxy Audit taught us that AI security is not just about preventing attacks.

Different stakeholders need different outcomes:

Developers need simple integration.
Security teams need visibility.
Enterprise customers need confidence.
Auditors need evidence.
Compliance teams need reports.

A successful AI security platform has to satisfy all of these requirements simultaneously.

We also learned that trust is becoming one of the most important aspects of enterprise AI adoption. Organizations increasingly need ways to demonstrate—not just claim—that their AI systems operate securely.

Why It Matters

As AI becomes part of critical business workflows, organizations need more than monitoring tools.

They need systems that can continuously identify risks, preserve privacy, and generate trustworthy evidence for customers, auditors, and regulators.

Foxy Audit combines AI runtime security, privacy-preserving analysis, tamper-evident audit evidence, and automated compliance reporting into a developer-friendly platform that helps organizations build AI systems they can confidently deploy, secure, and verify.