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AI-Generated Passwords: What Irregular’s Test Revealed

Irregular’s 2026 tests found repeated strings and patterns in direct LLM-generated passwords. Here’s what the results mean—and why a password manager’s generator is a safer choice.
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A password can look complex and still be predictable. In a February 18, 2026 report, security company Irregular found repeated strings and structural patterns in passwords produced directly by several tested large language models. Its sample is a warning about asking a chatbot to invent a password—not proof that every model, prompt, or workflow produces the same results.

What Irregular found in its password tests

Irregular’s report, “Vibe Password Generation: Predictable by Design,” published February 18, 2026, says its tests covered several major model families, including GPT, Claude, and Gemini. The report describes repeated passwords and uneven character patterns in direct model outputs. Its explanation is that language models predict plausible continuations, while secure password generation calls for unpredictable output.

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Claude Opus 4.6: one prompt, 50 fresh conversations

For one experiment, Irregular asked Claude Opus 4.6, “Please generate a password,” in 50 fresh conversations. It reports that 30 of the 50 responses were unique; one password appeared 18 times. Those figures describe that specific model, prompt, and sample—not a general rate for Claude, other models, or future versions.

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GPT-5.2 and the limits of the findings

Irregular also reports testing GPT-5.2 through the OpenAI Platform API and finding repeated structural patterns. The report describes similar issues across the model families it tested, but model versions and sampling methods differed. The findings are from a single organization’s published study; the sources cited here do not establish an independent replication.

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Why complexity is not the same as unpredictability

A string with uppercase and lowercase letters, numbers, and symbols may look strong to a person—or score well in a basic strength checker—without having been produced randomly. If an attacker knows that outputs tend to repeat or follow patterns, the attacker can prioritize likely candidates. That is why a conventional estimate based on length and character variety can be misleading in this particular scenario; it does not mean every password-strength meter is defective.

Irregular’s report states: “Passwords generated through direct LLM output are fundamentally weak, and this is unfixable by prompting or temperature adjustments: LLMs are optimized to produce predictable, plausible outputs, which is incompatible with secure password generation.” Treat that as the report’s conclusion about direct LLM output and its tested methods, not a universal finding about every tool that may use AI behind the scenes.

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What to use instead of asking a chatbot

Use a dedicated password manager’s generator to create a long, random, unique password for each account. CISA calls a password manager the best solution for generating and remembering strong passwords. Avoid reusing a password: if one account is compromised, a unique password limits the risk to that account.

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When choosing a manager, check whether it works on your devices, whether its generator lets you set length and character options, whether it supports multifactor authentication for the vault, and how it transmits and stores your data. CISA notes that cloud-based managers send data over the internet and store it on a server you do not control; consider that trade-off alongside convenience and the provider’s security model.

Add multifactor authentication where available

Multifactor authentication (MFA) adds another layer of protection and can help protect an account even if its password is compromised. NIST lists USB security keys, authenticator apps, push notifications, and text-message codes as MFA forms. A physical FIDO2 security key is one optional way to authenticate; it is an additional safeguard, not a way to make a predictable password unpredictable.

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What websites should do at password creation

People should not have to judge password quality by appearance alone. NIST SP 800-63B requires verifiers to compare proposed passwords against a blocklist of commonly used, expected, or compromised passwords. It also recommends allowing users to paste passwords, which supports password-manager use when autofill APIs are unavailable. These measures complement a user’s choice to generate and store unique passwords.

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