Self-Paced Professional

HACKINGP O I N T

Single Seat

Bridging the gap between traditional AppSec and the fast-moving world of large- language models, this course links traditional application-security thinking to the fast-evolving world of large-language models. In guided, sandboxed labs you will play the attacker, discovering how prompt injections, insecure output handling, and data-poisoning really unfold. We then introduce defensive prompt-engineering patterns, architectural guardrails, and monitoring strategies that shrink the attack surface. By the end, you will be able to evaluate LLM designs, articulate their risks, and recommend practical guardrail patterns and defenses to development teams.

Recommended For Ideal for security practitioners who are new to LLMs and need a structured, hands-

on introduction to the unique risks and defenses in generative-AI systems. Learners are required to have some level of familiarity with web-app pen testing techniques.

• Security Professionals.

• Back-End / Front-End Developers.

• System Architects.

• Product Managers.

• Anyone directly involved in the integration and application of LLM technologies.

Key Features • Attacker simulation – think and behave like a sophisticated adversary targeting

LLM deployments.

• Vulnerability discovery & exploitation - see how prompt injections, insecure output handling, and data poisoning are found and abused.

• Bug hunting in integrations - spot insecure plugins, design, and supply-chain links unique to LLM workflows.

• Hands-on labs - reproduce misconfigurations, over-reliance scenarios, and third-party exposure, covering the OWASP top 10 for LLM.

• Secure-by-design architecture - learn how to design LLM apps with minimal attack surface, plus logging, monitoring, and guardrails for continuous protection.

• Operational guardrails & monitoring – translate lab knowledge into practical logging, alerting, and policy guardrails that keep LLM services protected in production.

Mastering LLM Integration Security: Offensive and Defensive Tactics BY

Instructor-led 2 DaysProfessional

Self-Paced Professional

HACKINGP O I N T

Single Seat

Outcomes & Impact • Develop a clear mental model of LLM attack surfaces and articulate risks to

prompt engineers, risk teams, and leadership.

• Take away actionable knowledge for reviewing prompts, plugins, and LLM architectures during threat-modelling and code reviews.

• Become the organizational point-person who can translate generative-AI ambitions into secure, well-governed deployments.

Prerequisites Basic programming or computer-science background plus some prior exposure to AI or ML ideas.

Familiarity with fundamental cyber security practices gained through study or job experience.

Purchase & Redemption Options Mastering LLM Integration Security: Offensive and Defensive Tactics is available via:

• Flex Credits.

• Check Point COOP funds.

• Credit Card.

Get Started Today Click here to enroll in NotSoSecure Mastering LLM Integration Security: Offensive and Defensive Tactics.

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