Forenzy Cortex
Find your AI attack surface, test it like an adversary
Forenzy Cortex is an AI security platform that discovers the LLM applications, agents, APIs and models in use across your organization — including shadow AI — and tests them for the risks a standard security tool can't see: prompt injection, data leakage, insecure output handling and model abuse.
Cortex tests the model layer your web pentest cannot reach; pair with Forenzy Probe for application/API coverage and our AI/LLM penetration testing service for adversary-led review.
Your stack
How AI security testing fits alongside AppSec
- Goes beyond standard web/API pentests — probes prompt injection, data leakage and model abuse.
- Discovers shadow AI: unsanctioned bots, plugins and third-party model APIs across the org.
- Maps findings to the OWASP Top 10 for LLM Applications and EU AI Act robustness expectations.
- Forenzy Probe covers traditional runtime flaws; Cortex covers LLM-specific risk in the same release cycle.
- Complements hands-on AI/LLM penetration testing from the same Forenzy offensive team.
The problem
Every team is shipping AI. Few are testing it.
Each AI feature adds an attack surface your existing testing doesn't cover. Worse, much of it is shadow AI — tools and integrations adopted without security's knowledge — so the first step isn't testing the AI, it's finding it.
AI asset discovery
Surface the LLM apps, agents, APIs and models in use across your org, including shadow AI.
Prompt-injection testing
Probe for direct and indirect prompt injection, jailbreaks and guardrail bypasses.
Data-leakage detection
Test whether training data, secrets or context can be coaxed back out of the model.
OWASP LLM Top 10
Map every finding to the OWASP Top 10 for LLM applications.
Insecure-output handling
Catch where model output flows into code, queries or downstream systems unsafely.
Model supply-chain checks
Flag risky third-party models and datasets and gaps in model provenance.
AI / LLM attack surface overview
Security built for LLM apps, agents and APIs
Discover shadow AI, test for prompt injection and data leakage, and keep compliance evidence as models change.
Capabilities
Security built for LLM apps, agents and APIs
Discover shadow AI, test for prompt injection and data leakage, and keep compliance evidence as models change.
AI asset discovery
Surface the LLM apps, agents, APIs and models in use across your org, including shadow AI.
Prompt-injection testing
Probe for direct and indirect prompt injection, jailbreaks and guardrail bypasses.
Data-leakage detection
Test whether training data, secrets or context can be coaxed back out of the model.
OWASP LLM Top 10
Map every finding to the OWASP Top 10 for LLM applications.
Insecure-output handling
Catch where model output flows into code, queries or downstream systems unsafely.
Model supply-chain checks
Flag risky third-party models and datasets and gaps in model provenance.
EU AI Act readiness
Evidence the adversarial-robustness testing expected of higher-risk AI systems.
Continuous AI monitoring
Re-test as prompts, models and integrations change, not just once at launch.
Why Forenzy
We do not just use AI. We break it.
The same Forenzy team runs hands-on LLM penetration tests, so Cortex tests AI the way a motivated adversary actually would — not with a checklist of generic prompts.
Use cases
Where teams deploy it first
LLM app pre-launch review
Test assistants and agents for prompt injection, data leakage and insecure output handling before GA.
Shadow AI discovery
Inventory unsanctioned ChatGPT plugins, internal bots and third-party model APIs.
EU AI Act evidence
Document adversarial robustness testing for higher-risk AI systems.
Proof in practice
Customer outcomes
Professional services
Internal copilot blocked before PII leakage reached production
Challenge: A department-built LLM assistant could be prompted to return customer context from its RAG store.
Outcome: Cortex testing surfaced the flaw pre-launch; guardrails and retrieval filters were added before rollout.
Cortex-style testing uncovers prompt-injection paths in production assistants before launch — including flows that expose sensitive context or bypass authorization.
FAQ
Common questions
What is AI/LLM security testing?
Security assessment built for AI systems — testing for prompt injection, data leakage, jailbreaks and model abuse that traditional application testing does not cover.
Why can't a normal pentest cover my AI app?
A standard pentest checks the web and API layer; it does not probe the model itself for prompt injection, training-data leakage or unsafe output handling.
Does Forenzy Cortex help with the EU AI Act?
Yes — Cortex provides evidence of the adversarial-robustness testing expected of higher-risk AI systems under the EU AI Act.
What is shadow AI and can Cortex find it?
Shadow AI is LLM tools, agents or integrations adopted without security approval. Cortex discovers sanctioned and unsanctioned AI assets across your environment before testing them for LLM-specific risks.
Should we use Cortex or an AI penetration test?
Use both for defense in depth: Cortex supports continuous discovery and testing as models change; Forenzy AI/LLM penetration testing adds expert adversary-led depth for high-risk launches and audits.
