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Training Threat Modeling STRIDE 2026 - Securing MLOps Pipelines

Ref: CAF525
10 people max.
5500€ 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
5 journées
distanciel

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Learning objectives

  • Master the STRIDE methodology to analyze threats on MLOps pipelines
  • Develop professional skills in threat modeling applied to AI
  • Design secure models against spoofing and tampering in enterprise settings
  • Implement STRIDE strategies to optimize ML deployment resilience
  • Deploy certified risk assessment tools in professional training
  • Optimize MLOps processes to anticipate advanced cyberattacks

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.

Fouzi Benzidane
Fouzi Benzidane

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1STRIDE Threat Modeling Fundamentals: Theoretical Framework and Tools (TensorFlow Integration)

Discover the pillars of STRIDE with Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege, applied to MLOps workflows. Use Python and TensorFlow to model real scenarios, analyze enterprise case studies affected by ML breaches, complete practical DFD diagram exercises, produce your first personalized threat report, integrate professional checklists for rapid assessment.

Module 2Advanced STRIDE Threat Modeling Analysis: Spoofing and Tampering in PyTorch

Dive into spoofing attacks on PyTorch models, simulate tampering via data poisoning on ML datasets, apply STRIDE to mitigate these risks in MLOps CI/CD pipelines. Practice with hands-on Jupyter labs, evaluate quantified impact on model performance, generate automated countermeasures, test in simulated Kubernetes environments, deliver a security plan for a concrete enterprise project.

Module 3STRIDE Threat Modeling: Repudiation and Information Disclosure in MLOps

Explore repudiation and information disclosure via faulty logging in MLOps, use STRIDE to audit TensorFlow/PyTorch deployments, integrate OWASP ML Top 10. Conduct collaborative workshops on Grafana to visualize leaks, develop anomaly detection scripts, analyze real breaches like SolarWinds adapted to ML, produce secure governance policies, optimize for GDPR compliance in AI.

Module 4Denial of Service and Elevation STRIDE: MLOps Resilience (Monitoring Tools)

Master DoS and elevation of privilege on ML APIs, apply STRIDE to serverless MLOps architectures, test with chaos engineering on PyTorch Serving. Configure Prometheus for proactive alerts, simulate DDoS attacks on model serving, implement advanced rate limiting and RBAC, evaluate security ROI via metrics, generate a deliverable dashboard for continuous production monitoring.

Module 5STRIDE Threat Modeling Synthesis: Certifying Secure MLOps Project

Integrate full STRIDE on an end-to-end MLOps project with TensorFlow and PyTorch, create a holistic threat model for a real client case, present multilayer defenses. Validate via peer review and automated audit, deploy in secure staging, obtain skills certification, plan post-training roadmap, receive toolkit and reusable enterprise templates.

Evaluation method

  • Daily interactive quizzes on STRIDE and MLOps cases
  • Final certifying threat model project with deliverable report
  • 360° evaluation by Qualiopi trainers and peers

Learning method

  • 70% practical labs on real TensorFlow/PyTorch
  • ML breach case studies with metrics and lessons learned
  • Agile STRIDE methods adapted for enterprise MLOps
  • Unlimited post-training resources support for 6 months

Methods, materials and delivery

The Training Threat Modeling STRIDE 2026 - Securing MLOps Pipelines 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 Threat Modeling STRIDE 2026 - Securing MLOps Pipelines 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 Threat Modeling STRIDE 2026 - Securing MLOps Pipelines 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
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« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
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« 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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