Notes on data, AI, IT
and security
No marketing fog. The way I think about real problems with founders and managers.
A fifteen-person competence centre or an external architect: how a mid-sized plant covers the skills gap between production, IT and security
Large utilities are advised to build competence centres of 10 to 15 specialists at the junction of power engineering, IT and security. A plant of three hundred people cannot afford one and cannot hire one, yet it has the same critical infrastructure object, the same transition plan and the same model in the loop. What must stay inside, what can come from outside, and how to distribute signatures so that responsibility does not fall between four contractors.
Trusted hardware by 2030 and a machine on Windows XP: aligning a mandated transition with a line that runs until 2035
By 1 January 2030 significant critical infrastructure objects in Russia must predominantly run on trusted hardware and software platforms. Meanwhile the plant has a line on foreign controllers that will work for another ten years and cannot be stopped for a swap. What the decree actually requires, which nodes fall under it, where the no-equivalent exemption works, and how to turn compensating controls from an excuse into a justification.
Accident investigation needs a digital trace: what to capture before it happens
Since 1 January 2026 accidents and incidents in Russia's power sector are investigated under new rules, yet a security specialist is still not a mandatory member of the commission and a cyber attack is not listed as a cause. For a plant this means one thing: if configurations, firmware, logs and the model's state were not preserved at the moment of the accident, the investigation will close on the operator and the cause will stay in the loop. What to capture in advance, where to keep it and who signs.
FSTEC order 117 and AI in the loop: the regulator's first AI security checklist, translated into architecture
In April 2026 Russia's technical security regulator described AI protection in measures rather than terms for the first time: an isolated training environment, trusted data sets, model integrity, a log of every prompt and response, input and output filters, a ban on handing protected data to external services. Formally for state systems, in practice the first official checklist for any AI loop. Eight requirements translated into architecture and a one-quarter plan.
The air gap was an illusion before AI: what changes when models and agents live inside the loop
A piece on cyber resilience in the power sector dismantled the illusion of full isolation, split requirements into mission critical and business critical, flagged a gap in accident investigation and a shortage of cross-disciplinary staff. I agree with almost all of it and want to continue it: in 2026 the isolated loop has a new participant that makes decisions from data rather than code. That changes every one of his points.
Russia's 187-FZ nine years on: what changed since 2017 and what to do in 2026
In 2017 the critical infrastructure law was a frame, and a mid-sized plant could decide it did not apply. By 2026 self-assessment is closed by sector-wide object lists, trusted hardware is a plan with dates, foreign security tools are banned, and the regulator asks for running processes instead of binders. Four shifts, and the 2017 checklist rewritten for today.
Observability for a swarm of AI agents: what they are doing, who allowed it, and how to stop them
OpenAI is building a dedicated mechanism to watch and control large numbers of concurrently running agents. Why agent observability differs from classic metrics, logs and traces, why it sits closer to security than to operations, and what to put in place while you still only have a handful of agents.
Legacy on the factory floor: securing Windows XP and 7 systems you cannot patch
Industrial equipment lives 15 to 30 years, and the control PCs under it run on Windows XP and 7 that lost support long ago. A routine patch can void the vendor warranty or crash the process. What to do when you cannot update: move the defense from the host to isolation and compensating controls.
AI on the factory floor and a new class of attack: how to protect an industrial model
Factories put neural nets on predictive maintenance and process optimization. A new class of attack - poisoning the training data and quietly spoofing telemetry - pushes the AI into decisions that wreck equipment. Where the real line of defense actually runs.
When AI exposes the debt sitting in your codebase
The first numbers from Anthropic's Glasswing project are not a story about a smart model. They are a story about how much old vulnerability lives in code we use every day.
Shadow AI: how the new shadow IT is becoming a security problem
Employees are using AI tools without IT department oversight. The pattern is familiar - but the risks are different from classic shadow IT.
Data, IT, and security cannot be separated
Why splitting these three areas across different teams turns any technology project into a quiet source of hidden risk.