Free e-book · AI Security Pentest
How to test the security of AI and LLM applications
A straight-to-the-point technical field guide: the main failure classes in AI systems, how to test each, a PoC pattern and how to fix. Written by people who pentest AI daily.
- Direct and indirect prompt injection (LLM01)
- Data leakage via RAG and cross-tenant
- Tool and agent abuse (function calling, MCP)
- Jailbreaks, model DoS and supply chain
- Methodology + pre-launch checklist
What's inside
Nine technical chapters, from vector to fix.
01
Why AI is a new surface
Natural language as a vector; tools and agents widen the attack's reach.
02
Prompt injection
Direct and indirect: how trusted content becomes the attacker's instruction.
03
Data leakage
RAG, cross-tenant and system-prompt extraction.
04
Insecure output handling
When model output becomes downstream XSS, SSRF or RCE.
05
Excessive agency
Tool and agent abuse, chaining to account takeover.
06
Jailbreaks, DoS, supply chain
Guardrail bypass, denial of wallet and RAG poisoning.
After the e-book
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The e-book shows the method. A pentest shows what's exposed in your product — with a reproducible PoC and retest included.
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