DeepSeek v4.1-Flash
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Headlines · 7
- Censys Finds 800+ Passwordless Artex AI Pentest Deployments
Censys found more than 800 Artex deployments accessible from the internet without passwords, according to TechCrunch; TechRadar reported an updated scan of 1,465 exposed hosts. Artex is an open-source autonomous penetration-testing tool that combines AI agents with reconnaissance, and some exposed instances also ran offensive tools such as Cobalt Strike, Vshell, or Adaptix C2. Microsoft and CrowdStrike have linked Artex use to attacks involving South Korean financial institutions and ConnectWise Cloud Backup customer environments, while Censys said not every exposed instance was malicious.
TechCrunch AI · 🔥 4 - Together AI launches TKCC for continual inference optimization
Together AI introduced Together Compiler (TKCC), a continual optimization system that uses high-throughput agents to generate and test inference-engine optimizations for changing workloads and hardware. The company reports that TKCC delivered up to 2.6x higher throughput across several open-source models in less than 24 hours, using persistent engines and parallel experimentation. These performance and benchmark figures are vendor-provided and were not independently corroborated by the report.
Together AI Blog · 🔥 0 - DeepSeek V4.1-Flash Shows Reduced Phase-Sensitive Retrieval Weakness
ByteDance Seed researchers linked periodic retrieval failures in DeepSeek-V4-Flash-Base to position-dependent behavior in chunked KV-cache compression, with a 40.2-point gap between the best and worst position groups in a controlled 128K-context test. LeiPhone AI tested DeepSeek V4.1-Flash through the official API and found all 64 fixed-sampling completions correct, although prediction probabilities varied as irrelevant prefix length changed. Seed’s data show the best-to-worst position gap narrowing from 40.2 points in V4-Flash-Base to 19.1 points after post-training and 6.1 points in V4.1-Flash.
雷峰网 AI · 🔥 0 - OpenDS-World tests agents on real-web deep search
A multi-institution team introduced OpenDS, a deep-search task paradigm, and OpenDS-World, a 200-task benchmark for research agents operating across the open web. According to 机器之心, the tasks cover four modalities, 42 resource formats and seven evidence-access requirements; GPT-6 Astra led the 12 tested models with 39.0% accuracy, while Claude Opus 5.5 and Gemini 3.8 Flash scored 38.0% and 36.5%. The evaluation also records tool failures, execution time, search termination decisions and other execution traces.
机器之心 · 🔥 0 - ASUS GX10 Tests Show No Thermal Throttling at 82°C
A r/LocalLLaMA author tested DeepSeek V4.1-Flash on four ASUS GX10 systems across six cooling arrangements while recording temperatures, clocks, power and throughput. The highest observed temperature was 82°C, with no thermal throttling behavior and a maximum clock reduction of about 3%, which the author attributed to power-leakage management. The author found no meaningful performance difference between the coolest and hottest runs, though this was a single community report without independent corroboration.
r/LocalLLaMA · 🔥 0 - $0.88 and 22 seconds: ARTEX AI tool tied to South Korean bank breaches
Between Sept. 28 and Oct. 1, 2026, seven South Korean financial institutions were hit in the same wave of cyberattacks, with more than 68,000 customer records leaked, including 25,729 at Shinhan Bank. A CrowdStrike report dated Oct. 7 said the attacker may be an individual hacker from Guangdong, China, who mainly used the open-source AI penetration-testing agent ARTEX, invoking DeepSeek V4.1-Flash and also using GLM-5.3 and Grok 4.6 in Claude Code sessions. South Korean security firm Everspin's reproduction test said a similar attack took 22 seconds, about 44,000 tokens and roughly $0.88, with attackers targeting peripheral systems such as loan-agency and mobile-work systems rather than core online banking.
虎嗅 AI · 🔥 0 - PaperBenchX: best AI agent fully reproduces only 14% of papers
UniPat AI's PaperBenchX benchmark gives 10 frontier agent configurations a published paper and asks them to re-run the key experiments in real scientific software, across 93 tasks covering 12 research directions. According to the team's published results, 70 of the 93 tasks were not fully reproduced by any configuration, and the top performer, GPT-6 Astra, fully cleared only 14% (13 tasks), while Chinese models clustered around 7% — roughly half that. Scoring separates modeling, execution and scientific verification across 3,168 scorable criteria, with a 4–24 hour per-task budget and outputs wiped and re-run in an isolated environment before grading.
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