Recent Writings — Loren Kohnfelder

TIL the origins of the concept of software waterfall development: it was first used to advise against the practice. There are a number of analogous examples of terminology for criticism being adopted by fans, either unaware or unswayed by the critic’s words.

The point of this fascinating story: now that we can vibe code there are all kinds of creative uses; and because these applications do not need the rigor that commercial software requires, prototyping “alpha” quality is no problem.

• The real AI; Is AI profitable?; Very Important Words the Tech Industry Ruined
• System modeling
• Guardrails?
• Anthropic sandboxing
• What’s a Virus?
• Threat model or triage guideline?
• Big Tech priorities

The real AI Seth Godin, based on Woz’s definition of “AI” (spoiler: Actual Intelligence).

• Anthropic Mythos: security superpowers?
• Threat model scope matters
• Anyone ready for quantum break in 2029?
• Trains with 5G windows and noise-cancelling cabins: only in Japan
• The NAND gate of continuous mathematics: all elementary functions from one operator

Anthropic holding back Mythos because they claim it has extraordinary powers to discover security flaws (whether the claims hold up or not) was a master marketing/PR move. It instantly made a big splash, generated great demand, and as a side effect it at least made the software security community wonder, “what if it’s true?” Naturally, there are all kinds of opinions, rebuttals, and reactions.

“AI” on my view is already and will certainly be a massive disruption to software in the coming years. Furthermore, we have an unprecedented wave coming that’s only just now beginning to break. Yet the biggest unknown, as I see it, is how the software community will respond, and that will be more due to social factors than purely technical. This is very much as it should be, however our very human frailties and limitations will inevitably drive how this unfolds.

• Google security methodology compendium
• Threat modeling
• Are attacks the only threat?
• Why is threat modeling ignored?
• Miscellaneous
• e16n next Stage 4

Google is sharing a lot of their impressive security methodology in a recent collection of articles: How Google Does It: An inside look at cybersecurity. Of special interest to me: Threat modeling, from basics to AI.

• On “the end of security bugs”
• STRIPPED
• Incident response threat modeling?
• Using CSS and PDF as emulators running code

Claude Code Security has people predicting the end of security bugs as we know them I can’t imagine anything in the forseeable future doing that because all software has bugs, and vulnerabilities are by definition a subset of all the bugs (in a properly designed system). Bug-free code seems computationally infeasible for large systems, if only for the amount of testing required to confirm there are no bugs. What am I missing, or is it AI hype?

• on “Bitlocker, the FBI, and Risk”
• threat models to address hacklore
• software bloat
• software update release quality

How much AI use is acceptable for writing? It’s a hard question because it depends greatly on context, the reader’s expectations, and the fact that it’s difficult to usefully measure “how much”. How we address this matters for several reasons, including but not limited to: creator’s responsibility and originality, honest disclosure about research effort and sources, respecting the broad spectrum of opinion about ethical use of AI.

Writing in response to Adam Shostack’s excellent post “Bitlocker, the FBI, and Risk”. He nicely highlights the fundamental risk trade-off in data protection, and so long as we (often very rightly) prioritize availability we need measures that may compromise confidentiality. Also I especially liked the touch of a risk analysis not using numbers and explicitly pointing that out.