Agent5Seven topics. One clear view.
Agent5

The latest AI news at a glance: seven topics, and a short, plain-English read on the stories. Free, no account.

Product
HomeHow it worksFAQAboutHow we fact-checkBlog
News
All newsModels & ReleasesFunding & DealsBenchmarksAgents & ProductsHardware & ComputePolicy & DramaRobotics
More
AdvertisePressPrivacyTerms
© 2026 Agent5
Agent5
Blog
Agent5
Blog
  1. Home›
  2. News›
  3. Benchmarks›
  4. Claude solves 25-year NSA cryptography mystery
Models & Releases23Funding & Deals10Benchmarks19Agents & Products64Hardware & Compute13Policy & Drama32Robotics12
Benchmarks

Claude solves 25-year NSA cryptography mystery

The Decoder: Anthropics' Claude cracks a 25-year-old NSA cryptography mystery in under 30 minutes

Anthropic's AI model Claude has solved a 25-year-old cryptography puzzle. The mysterious seeds behind NIST's standard curves for digital signatures were provided by the NSA without explanation, raising long-standing suspicion about built-in backdoors. Claude figured out in under 30 minutes that the seeds came from "lrand48," a simple C random number generator, making deliberate backdoors far less likely. The article Anthropics' Claude cracks a 25-year-old NSA cryptography mystery i

Get smart on it

An AI system solved a longstanding cryptography puzzle by identifying how the NSA generated seed values for a widely-used digital signature standard from 2000. The seeds' origins had been unknown for 25 years, raising concerns about potential security backdoors, and the mystery had attracted bounty offers and investigation efforts. The AI determined the seeds came from a simple random number generator initialized with a timestamp from the late 1990s, and its findings suggest deliberate backdoors were less likely. The organization behind the AI donated the bounty to an internet security research group.

Relevant courses

Want to go deeper than the news? Explore live, cohort-based AI courses taught by practitioners.

Browse AI courses on Maven →
Sources
The Decoder ↗
The biggest AI stories, once a day

One short email a day with the stories that matter. Free. Unsubscribe with one click.

Related news
BenchmarksOpen story →

Deepseek V4.1 Flash 1017 beats larger rivals in agentic tasks while once again massively cutting per-task costs

Deepseek has released V4.1-Flash-1017 as an open-weight model that posts better benchmarks, finishes tasks faster, and produces shorter outputs than its predecessor. The company is also opening up its internal search engine through new Search and Fetch APIs at $0.75 per 1,000 calls. API users in tools like Claude Code and Codex get free access for now. The article Deepseek V4.1 Flash 1017 beats larger rivals in agentic tasks while once again massively cutting per-task costs appeared fir

BenchmarksOpen story →

Elorian’s first AI model wants to reason with images, not just about them

According to Elorian's evaluations, Glimpse outperforms even GPT-6 Astra on scientific chart reasoning and short-form video captioning, with competitive results on other visual reasoning tasks.

BenchmarksOpen story →

Google's Gemini 4 Argon is closer to the AI frontier than any Google model in months

Google Deepmind's Gemini 4 Argon scored 97.5 percent on the ARC-AGI-3 benchmark, making Google the second lab after OpenAI to cross the 95 percent mark. But the results swing wildly depending on the test setup: in the standard harness, the score drops to just 49.8 percent. Argon also trails rivals in math and software engineering. The article Google's Gemini 4 Argon is closer to the AI frontier than any Google model in months appeared first on The Decoder.

BenchmarksOpen story →

GPT-6-Astra solves 49 of 50 physics research problems at $2.40 apiece

On the TheoPhysEval benchmark, GPT-6-Astra solves 49 of 50 unpublished theoretical physics calculations as accurately as leading specialists. In some cases where the agent seemed to fail, the experts' own reference solutions turned out to contain errors. But the researchers say physics hasn't had a breakthrough like the ones in mathematics, because the agents lack "taste." They still think autonomous, top-level AI research could arrive soon. They already see consequences for how young p

BenchmarksOpen story →

Google wants Gemini 4 Argon to be the only AI model robots need

Google's Gemini 4 Argon controls robots, generates simulations from photos or sketches, and evaluates training videos. On Google's own ERQA benchmark, it scores 87 percent. But the published example prompts show that the demos still need a lot of human guidance. The article Google wants Gemini 4 Argon to be the only AI model robots need appeared first on The Decoder.

BenchmarksOpen story →

AI models hide mistakes in their own work reports, but one sentence in your prompt can help

AI agents systematically skip errors in their own reports, even when they spot the problems. In a study by Google Research, MIT, and Harvard, GPT-5.5 left out negative results in 198 out of 200 paper abstracts. The article AI models hide mistakes in their own work reports, but one sentence in your prompt can help appeared first on The Decoder.