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Tuesday, November 3, 2026

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Fajasy on X

If the AI model Nubeva Technologies $NBVAF (TSXV: $NBVA) is training to read malware works, it could also take over the one step in its ransomware recovery software that engineers still do by hand. Nubeva’s Ransomware Reversal software, or NuRR, copies the encryption keys during an attack, but someone still has to figure out how ransomware uses them before Nubeva can build a decryptor (a program that reverses the encryption). AI agents have run NuRR’s routine support (bug fixes, support tickets, and product maintenance) for some time, CEO Randy Chou said, but Nubeva’s engineers still handle each live ransomware case by hand. Nubeva’s first granted patent finds the encryption method by running the ransomware in a sandbox (an isolated test computer) and matching the result to a library of standard methods. But the sandbox method breaks down in two cases Chou described, since homemade encryption (encryption ransomware authors write themselves) won’t match any standard method, and malware that detects the sandbox does nothing. A model that reads the malware’s compiled code could get around both problems, since (1) homemade encryption still shows up in the code as steps a model can follow, and (2) the malware’s checks for a real computer only run when the malware runs, so reading the code never triggers the checks. With NuRR supplying the keys and the model working out the encryption method, Nubeva would have both inputs a decryptor needs without an engineer taking the ransomware apart by hand. Frontier models, the most advanced AI models from labs like OpenAI and Anthropic, can already work out what some binaries (compiled programs) do just by reading their code. Anthropic said in April 2026 that its Claude Mythos Preview model can take “a closed-source, stripped binary,” meaning one with its function and variable names removed, and reconstruct “(plausible) source code for what it does.” Obfuscation (scrambling code to hide its purpose) is harder for a model to get past, since compressed malware keeps its real code hidden until it runs. Chou blamed obfuscation for the ~70% of malware binaries frontier models can’t figure out, so Nubeva’s model still has to prove it can do better. Chou didn’t connect the model to NuRR in his October 5, 2026 interview, but working out the encryption method is the same step Nubeva’s FY2026 annual filings say its AI decryptor builder will automate. Therefore, if the model works on live ransomware, NuRR could take on more cases at once, easing the capacity problem that cost Nubeva its biggest customer in 2023 (risk advisory firm Kroll).
@calvinblissett

Calvin Blissett on X

$CCLD crazy important earnings. Questions and things to monitor: new AI products, cybersecurity any and all information (loss of sales momentum, loss of current clients, still covered by insurance, lawsuits), why no acquisitions, are they still focused on acquisitions or spending more time developing AI products, is the person leading the AI strategy fit to lead it? At what point are buybacks considered despite the phenomenal ROI from acquisition.
@StableBread 2 clicks

Fajasy on X

I tried to work out who’s behind the AI data labeling companies that approached Nubeva Technologies $NBVAF (TSXV: $NBVA). CEO Randy Chou didn’t name the data labeling companies (firms that turn experts’ knowledge into training data for AI labs) or the customers behind them. “If a data labeling company’s coming to us, somebody behind them is asking,” Chou said, adding that the customer typically isn’t limited to cybersecurity companies. OpenAI is one potential candidate, since my previous write-up concluded that the frontier model Nubeva got access to in September was most likely OpenAI’s, through its Daybreak program for vetted defenders. OpenAI launched GPT-6 Astra on September 3, 2026, the day Nubeva announced its access. It’s the first model OpenAI rated Critical for cybersecurity capability. But access to OpenAI’s model wouldn’t prove OpenAI is also behind the data labeling companies, since any lab building cyber models could want labeled malware. Among data labeling companies, three of the largest are publicly recruiting or selling binary analysis expertise, the skill of figuring out what malware programs do: → Scale AI: Its product manager posting calls the cybersecurity portfolio “a product line that does not exist yet” and says the hire will recruit “malware analysts.” → Turing: Sells CyberBench, security tasks for training and testing frontier models, with malware analysis and reverse engineering among its ten categories. TechCrunch called Turing “a key coding provider for OpenAI” in March 2025. → Mercor: Recruits security experts, preferring reverse engineering or binary analysis backgrounds, and counts OpenAI, Anthropic, and Meta $META as customers. OpenAI cut ties with Scale in June 2025, after Meta bought 49% of Scale and hired its founder, Alexandr Wang. So if OpenAI is behind the approach, Turing and Mercor are the likeliest data labeling companies, since both sell to OpenAI and already sell or buy binary analysis expertise. Either way, these data labeling companies are worth $2.2-29B, so even Turing, the smallest, could pay the top of my $12-19M sale range for Nubeva for less than 1% of its last valuation.

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