AI-powered features introduce new security risks. Wolfcore tests the prompts, APIs, model behaviour, and data pathways attackers target — before they are exploited.
AI Security and AI Penetration Testing
Modern applications are rapidly integrating LLMs into customer-facing and internal systems. — chatbots, recommendation engines, automated assistants, document processors, fraud detection, and more.
Most breaches involving AI systems do not come from the model itself — they come from how the model is integrated into applications, APIs, and business logic.
But AI features bring new vulnerabilities:
- Data Leakage
- Prompt injection
- Model manipulation
- Insecure LLM integrations
- Overscoped API access
- Unsafe tool execution
Wolfcore performs full AI application penetration testing to uncover these weaknesses and help your team secure your LLM-enabled systems.
What We Test
Prompt Injection Vulnerabilities
- Direct prompt injection
- Indirect prompt injection (HTML, emails, PDFs, user-submitted text)
- Output manipulation
- Model bypass
- Jailbreak attempts
- Safety layer bypass techniques
LLM App Architecture
- AI-API boundaries
- Data exposure
- Unsafe function calling
- Tool execution security
- Retrieval-Augmented Generation (RAG) risks
- Embedding store leakage
API & Backend Security
- Overscoped API keys
- Missing access controls
- Backend actions triggered by model output
- Validation weaknesses
- Insecure integrations (Zapier, webhooks, automations)
Data Leakage & Privacy
- Sensitive data exposure in responses
- Prompt memory retention issues
- PII handling failures
- Shadow datasets
- Training data bleed
AI Supply Chain Security
- Model source verification
- Use of third-party models
- Dependency poisoning
- Untrusted plugins
- Model update safety
Business Logic Testing
- Can the model reveal internal instructions?
- Can a user escalate actions via AI?
- Can they impersonate staff via chatbots?
- Can the AI generate harmful outputs affecting customers?
Deliverables
Every AI pentest engagement includes
- Full report (PDF)
- Technical findings with evidence
- Risk scoring (CVSS + AI-specific severity)
- Remediation steps for developers
- Optional workshop with your team
- Retest included
This service is ideal for
- SaaS platforms using chatbots or AI assistants
- Products integrating OpenAI / Azure OpenAI / Claude / Gemini
- Internal AI tools handling sensitive data
- Startups preparing for enterprise or regulated customers
Why Wolfcore
AI pentesting that mirrors real attacks — not a checkbox exercise.
We test the full AI feature: prompts, APIs, tools, data pathways, and the business logic around them — the same places attackers target and we test AI systems as part of the application, not as isolated models.
Real-world AI red-teaming techniques
We attempt the same manipulations used in the wild: prompt injection paths, indirect injection, output steering, and tool abuse.
We test what scanners can’t
No “green tick” report. We validate exploitability across model behaviour, app logic, permissions, and unsafe tool/function execution.
Security across your AI stack
From RAG and embeddings to overscoped keys and backend actions triggered by model output — we follow the chain end-to-end.
Clear outcomes your team can ship
Repro steps, evidence, severity, and developer-ready fixes — so issues actually get resolved, not just documented.
Want a practical view of your AI attack surface?
Book a short consultation and we’ll outline what we’d test in your exact implementation.
Ready to secure your AI systems?
Book a consultation with Wolfcore.
AI and LLM penetration testing
AI features introduce new attack surface — prompt injection, data leakage, insecure tool use and model abuse. Wolfcore tests your AI and LLM-powered applications the way attackers will, so you can ship AI features safely.
FAQ
What is AI penetration testing?
AI penetration testing assesses AI and LLM-powered systems for security flaws such as prompt injection, data leakage, insecure tool or plugin use and model abuse.
What is prompt injection?
Prompt injection is when an attacker crafts input that manipulates an AI model into ignoring its instructions, leaking data or performing unintended actions.
Can you test our LLM chatbot or AI feature?
Yes. Wolfcore tests chatbots, copilots, RAG systems and other LLM-powered features against real-world AI attack techniques.
How is AI pentesting different from normal testing?
It adds AI-specific attacks on top of standard penetration testing, targeting the model, its prompts, data sources and connected tools.