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Training Red Teaming LLM - Securing AI Models Against Attacks

Ref: OZX383
10 people max.
4400€ HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
4 journées
distanciel

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Learning objectives

  • Master advanced LLM red teaming techniques in a certified professional training
  • Develop skills to identify hidden vulnerabilities in enterprise AI models
  • Design realistic attack scenarios tailored to professional LLM deployments
  • Implement open-source tools to test the robustness of large language models
  • Optimize post-red teaming mitigation strategies for enhanced AI security
  • Evaluate the impact of attacks on LLM performance and GDPR compliance
  • Acquire a certification proving expertise in red teaming to boost career

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

Don't let this gap widen

Why this program matters

  • Without this upskilling, your team accumulates a technological gap that translates directly into productivity loss.

  • Organizations that don't train their talents on key topics see their competitiveness drop.

  • Every quarter without training is a gap widening with competitors who invest.

  • The cost of inaction quickly exceeds that of well-targeted training.

Allan Busi
Allan Busi

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1LLM Red Teaming Fundamentals: Methodologies and Ethical Framework (OWASP Tools, MITRE Frameworks)

Discover the principles of red teaming applied to LLMs through interactive workshops on OWASP attack taxonomies for AI, explore MITRE-Engage frameworks adapted to language models, analyze real-world historical jailbreak cases from OpenAI and Anthropic, practice developing ethical charters for enterprise simulations, produce a preliminary threat report, integrate tools like Garak for initial vulnerability scanning, while fostering participant exchanges for a collaborative and professional approach.

Module 2Advanced LLM Red Teaming Attacks: Jailbreaks and Injections (Adversarial Prompts, GCG, PAIR)

Dive into sophisticated attack techniques with hands-on exercises on universal jailbreaks using gradient-based methods like GCG, test adversarial prompt injections on GPT-4 and Llama2, simulate PAIR scenarios to extract sensitive data, use Python libraries like TextAttack and Adversarial Robustness Toolbox, evaluate effectiveness via attack success metrics, analyze logs to identify architectural weaknesses in LLMs, generate detailed reports with penetration rate visualizations, prepare proactive defenses based on field feedback.

Module 3LLM Red Teaming Defenses and Mitigation: Hardening and Monitoring (RLHF, Guardrails, Fine-Tuning)

Learn to counter attacks through workshops on reinforced RLHF and alignment techniques, implement guardrails with NeMo Guardrails and LlamaGuard, practice defensive fine-tuning on adversarial datasets like AdvBench, deploy real-time monitoring with LangChain and Prometheus, test post-mitigation robustness via iterative red teaming, quantify improvements with SafetyBench benchmarks, produce enterprise playbooks for recurring audits, integrate GDPR compliance and NIST AI RMF for large-scale secure deployments.

Module 4Advanced LLM Red Teaming Simulations: Real Cases and Certification (CTF, Executive Reports)

Participate in a full Capture The Flag on vulnerable LLMs like Mistral and Falcon, simulate chained attacks on enterprise RAG pipelines, analyze real incidents like those from Bing Chat, develop executive reports with quantified security ROI, review strategies via peer-review, validate skills through QCM and final certifying project, receive personalized feedback for post-training action plans, export reusable templates for internal teams, consolidate red teaming expertise for secure AI leadership.

Evaluation method

  • Interactive quizzes and daily challenges to validate technical skills
  • Red teaming simulations evaluated by experts on realistic criteria
  • Final project with detailed report and oral defense for certification

Learning method

  • 70% hands-on approach with open-source tools and live LLMs
  • Case studies from leading companies in secure AI
  • Individual mentoring in small groups of max 10
  • Post-training resources: replays, source codes, alumni community

Methods, materials and delivery

The Training Red Teaming LLM - Securing AI Models Against Attacks program is delivered onsite or remote (blended-learning, e-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.

The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.

Equipment required

For the smooth delivery of the Training Red Teaming LLM - Securing AI Models Against Attacks program, the following equipment is required:

  • Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
  • Training environments installed on workstations or accessible online
  • Course materials, hands-on exercises and complementary resources
  • Post-training access to materials and educational resources

For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.

* contact us for remote delivery feasibility** ratio varies depending on the program

Skills assessment methods

Assessment of skills acquired during the Training Red Teaming LLM - Securing AI Models Against Attacks program is performed through:

  • During training: case studies, hands-on labs and professional scenarios
  • End of training: self-assessment questionnaire and skills evaluation by the trainer
  • After training: completion certificate detailing acquired skills

Program accessibility

Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.

Enrollment terms and lead times

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
Our method

Training quality, guaranteed at every step

Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.

Step 1

Rigorous trainer selection

Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.

  • Triple validation: technical, pedagogical, sectoral.
  • Minimum rating 4.8/5 over the last 12 sessions.
Step 2

You meet the trainer beforehand

30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.

  • Live briefing on goals and team context.
  • Veto right — we swap the trainer for free if needed.
Step 3

Content tailored to your context

No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.

  • Hands-on cases drawn from your stack and projects.
  • Program co-written then validated by your team.
Step 4

Continuous quality follow-up

Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.

  • NPS, knowledge quizzes and skills self-assessment.
  • Satisfaction guarantee: fully satisfied or free rework.

A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

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