OTCogniShield Masterclass — Episode 05
From network observations to reviewable evidence

Runtime: 12 minutes 36 seconds, including the six-second Thank you card.

Format: H.264, 1280 x 720, 24 fps, AAC narration, fast-start playback.
Presenter: approved static Sam portrait; no lip synchronisation.
Narration: same synthetic British male series voice, Kokoro bm_fable.

The episode connects observations to a specific question, scope, original observation dates, processing and review dates, evidence sources, owners, uncertainty, coverage and remaining gaps. It follows an illustrative observation into an evidence register and bounded questionnaire response.

Includes an IEC 62443-3-2 risk-assessment section covering the system under consideration, initial risk, zones and conduits, tolerable risk, detailed scenario assessment, consequences and likelihood, unmitigated risk, target security levels, countermeasures, residual risk, documented requirements and asset owner approval. It explains that a locally approved 4x4 matrix is an example method, not an exact matrix mandated by the standard.

NIS2 and NCSC CAF material supports preparation and review. Actual applicability, assessment scope, framework version and sector arrangements require confirmation. Evidence mappings do not establish compliance or complete a risk assessment.

The final narrated passage ends with Thank you. A six-second Thank you card follows. No narration/voice-engine label is burned into the picture. The MP4 title contains only the episode title.

Captions.en.vtt and Captions.en.srt: player captions.
Narration.txt: timed transcript.
Narration-British-Male.wav: unprocessed voice master.
Poster.png: opening frame.
Sources.txt: reference notes and scope of the teaching example.
source/: editable script, timings and renderer.
assets/: approved series images.
Kokoro-LICENSE.txt: retained voice-engine licence.

To regenerate narration, install the dependencies and supply the Kokoro model directory to source/generate_narration.py --model-dir PATH. The model and environment are not bundled. The script preserves the generated speech and natural pauses.
To regenerate the MP4, extract the folder as episode05. From its parent directory create output/, then run python3 episode05/source/render_episode.py. Rendering requires Python, Pillow, NumPy, FFmpeg and DejaVu fonts.

The MP4 can be uploaded independently. This production pack does not change the website or publish an episode page.
