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Anthropic's Claude AI identifies NIST P-256 RNG vulnerability

Anthropic's Claude AI identified a vulnerability in the NIST P-256 random number generator, tracing its seeds to a 1997 timestamp and the `lrand48` function. Security researcher Valsorda confirmed these findings, suggesting that while no immediate rotation is necessary, users should verify their own random number generators. The second item discusses common pitfalls encountered when attempting to run AI models locally, highlighting hardware and software configuration issues. AI

IMPACT Highlights AI's capability in code auditing and vulnerability detection, prompting broader checks on random number generation.

RANK_REASON AI model identifies a specific technical vulnerability and a security researcher verifies it.

Read on Mastodon — fosstodon.org →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Anthropic's Claude AI identifies NIST P-256 RNG vulnerability

How we ranked this

Signal score
8 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Research
AI model identifies a specific technical vulnerability and a security researcher verifies it.
Source corroboration
2 independent sources
Multiple independent publishers reporting the same story raises confidence that it's real and newsworthy.
Topics
safety, other
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AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

Full methodology in our editorial standards.

COVERAGE [2]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    Anthropic says Claude found the NIST P-256 seeds came from lrand48 seeded with a 1997 timestamp. Valsorda verified it. Nothing to rotate; check your own RNGs. #

    Anthropic says Claude found the NIST P-256 seeds came from lrand48 seeded with a 1997 timestamp. Valsorda verified it. Nothing to rotate; check your own RNGs. # ai # security # cryptography # news # software # coding # development # engineering # inclusive # community Claude Trac…

  2. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    I keep seeing the same two failures when people try to run a model locally. The first is buying or... # ai # llm # machinelearning # hardware # software # codin

    I keep seeing the same two failures when people try to run a model locally. The first is buying or... # ai # llm # machinelearning # hardware # software # coding # development # engineering # inclusive # community Two questions before you run a local LLM: does it fit, and how fas…