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Training Volatility - Mastering IoT Memory Analysis

Ref: QMG457
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 the fundamentals of Volatility for analyzing IoT device memory in professional training.
  • Develop practical skills in extracting volatile data for corporate security.
  • Configure Volatility on simulated IoT environments with certification exercises.
  • Implement Volatility plugins adapted to sensors and IoT protocols like MQTT.
  • Analyze memory dumps to detect threats on LoRa networks and sensors.
  • Design actionable forensic reports in professional IoT contexts.
  • Optimize Volatility workflows for corporate skills certification.

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 1Introduction to Volatility: installation and first IoT memory plugins (Python tools, RAM dumps, simulated exercises)

Discover Volatility through guided installation on Linux dedicated to IoT devices, explore basic commands to profile volatile memory of connected sensors, practice extracting RAM images from embedded firmware, analyze suspicious processes with the pslist plugin adapted to common ARM architectures in IoT, perform practical exercises on real MQTT malware cases, produce your first simple reports, consolidate your skills with an interactive quiz to validate beginner competencies.

Module 2Process Analysis with Volatility: threat detection on IoT sensors (plugins psscan, threads, LoRa networking)

Dive into advanced process analysis with Volatility, scan memory spaces to identify malicious injections on IoT sensors, examine threads and suspicious network connections via netscan plugins for LoRa protocols, simulate real attacks on virtual devices, extract artifacts like cryptographic keys and command histories, apply custom filters to target MIPS/ARM architectures, generate forensic event timelines, end with a practical workshop on an MQTT-infected dump, strengthening your professional certification skills.

Module 3Artifact Extraction with Volatility: files and IoT registry (plugins filescan, hivescan, embedded sensor cases)

Master artifact extraction with Volatility on IoT systems, use filescan to recover deleted files in sensor RAM, analyze registry hives for malicious LoRa configurations, practice on real dumps from compromised devices, retrieve browser histories and hidden logs, integrate custom Python scripts to automate MQTT searches, compare your findings to known IoT cybersecurity IOCs, produce formatted judicial evidence, validate through group peer-review for corporate skills advancement.

Module 4Advanced Volatility Scenarios: timelines and IoT reports (tool integration, final certification projects)

Synthesize your skills with Volatility timelines on complex IoT attacks, integrate Maltego and Wireshark to correlate LoRa/MQTT memory data, develop a complete forensic investigation workflow for sensors, analyze persistent rootkits in embedded RAM, customize plugins for specific protocols, present a final project on a real corporate case, receive expert feedback and skills certification, access post-training resources for immediate professional deployment.

Evaluation method

  • Daily interactive quizzes on Volatility IoT commands.
  • Practical case studies with real memory dumps.
  • Final certification project: complete IoT forensic report.
  • Continuous evaluation by expert trainer.

Learning method

  • 100% hands-on on simulated IoT Volatility environments.
  • Real cases of sensor malwares, MQTT, and LoRa.
  • Small groups for personalized support.
  • Unlimited post-training digital resources.
  • Qualiopi certification validating professional skills.

Methods, materials and delivery

The Training Volatility - Mastering IoT Memory Analysis 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 Volatility - Mastering IoT Memory Analysis 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 Volatility - Mastering IoT Memory Analysis 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

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TomFormation AWS — Cloud Practitioner
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« la formation dev etait intense mais grave bien. merci Anthony Khelil »

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AmbreDWWM - Développement Web & Mobile React
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« 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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