Services

AI security testing

Your AI system passed its security review. Has anyone tried to make it ignore its own instructions? Epiphyte tests AI systems the way attackers use them, with Monarch, the cybersecurity AI from UD Works.

Security advisory · 22 October 2026

PHP2Shell: patch and mitigate now

Unauthenticated remote code execution in PHP (CVE-2026-109618, CVE-2026-109619). CISA has listed both as exploited since 26 October. Free 6-page mitigation guide.

Get the guide

What we test

The OWASP Top 10 for LLM Applications 2025 lists ten ways LLM applications are attacked. Epiphyte tests against all ten. For each one, the question a test has to answer:

  1. Prompt injection. Can input from a user, a document or a web page make the model ignore its instructions?

  2. Sensitive information disclosure. Can the application be made to return data the user is not entitled to?

  3. Supply chain. Which models, datasets and plug-ins does it depend on, and who controls their updates?

  4. Data and model poisoning. Can training, fine-tuning or retrieval data be altered by an outsider?

  5. Improper output handling. Is model output passed to a shell, a database or a browser without validation?

  6. Excessive agency. Which tools and permissions does the model hold, and which actions need a human?

  7. System prompt leakage. Does the system prompt contain anything that would be harmful if read?

  8. Vector and embedding weaknesses. Can one tenant's embeddings be retrieved by another?

  9. Misinformation. How is a confident wrong answer detected before it reaches a customer?

  10. Unbounded consumption. What stops one user from running up cost or exhausting capacity?

The rules behind it

  • CSA, Singapore. The Guidelines on Securing AI Systems (15 October 2024) ask for AI that is secure by design and secure by default. The Companion Guide draws on MITRE ATLAS and the OWASP Top 10.

  • MAS, para 5.10. A financial institution tests third-party AI in its own use cases, with its own data, runs compensatory testing where the vendor's disclosures fall short, and keeps documentation of how it tested.

How we test

With Monarch, the cybersecurity AI from UD Works. Its compact local model runs on a single 16 vCPU VM with no GPU, so testing can run inside your environment. We test only the systems you authorise, within a scope agreed with you before testing starts.

Guide: testing AI agents and LLM apps in Singapore

Prices

  • AI system and agent red-team: S$10,000–20,000 per system, 5 days. No high finding, no fee.

  • Web, API and network penetration testing: from S$1,500 per asset, report in MAS TRM format, retest included.

  • Continuous VAPT: from S$20,000 per year, delivered as a service with an annual evidence pack.

Free AI agent red-team checklist

Talk to us

Tell us what needs testing or documenting and the date you're working to. We'll send a proposal with the price and dates.