30
60
55
55
60
30
30
30
30
42
55
55
42
Bisonal Malware Used in Attacks Against Russia and South Korea
Unit 42 details a Bisonal malware variant, active since 2014, targeting Russian and South Korean defense organizations via PDF-disguised spearphishing emails.
In early May, Unit 42 discovered a campaign delivering a Bisonal malware variant against at least one Russian communications security and cryptography company and one unidentified organization in South Korea. The variant, in the wild since at least 2014, introduces a new C2 cipher and rewritten networking and persistence code, with only 14 samples collected to date. Attackers spoofed Russian state corporation Rostec in spearphishing emails carrying an executable disguised with a PDF icon; the dropper decrypts an RC4-encrypted DLL and establishes persistence via a registry Run key. Bisonal has been used since 2013 against government, military, and defense targets in South Korea, Russia, Japan, and India, alongside successors Bioazih and Dexbia.
48
55
55
42
55
30
55
30
30
30
55
57
55
55
Cybersecurity, emerging technology and systemic risk: What it means for the medical device industry?
57
55
60
60
30
30
Ask HN: Anyone still coding like 2021? Where do you work?
Hacker News users debate coding without LLMs, with one developer fired for refusing AI tools and others describing daily hand-coding practice to counter skill atrophy.
An Ask HN thread collects experiences of developers who still write code without LLM assistance. One contributor says he was fired for political reasons after refusing to use LLMs despite adequate stated performance, and observes fewer job ads now require LLM use. Others describe starting each day with a LeetCode problem or 30-60 minutes of hand-coding to stay sharp, contractual bans on AI-generated code for a government-adjacent embedded product over unresolved copyright issues, and inconsistent corporate policies where ChatGPT or Codex use flip-flops between allowed and blocked while a CIO mandates 70-80% AI-generated code next year.
12
Building the materials foundation for AI
Syensqo's CTO says AI pushes semiconductors and data centers to physical limits, driving advanced materials demand and AI-accelerated materials discovery.
MIT Technology Review's Business Lab podcast, produced in partnership with Syensqo, features CTO Mike Finelli discussing how AI workloads push semiconductors and data centers to physical limits in performance, thermal management, and reliability. Syensqo develops high-voltage data center materials, semiconductor sealing materials, and immersion cooling fluids, while using AI agents to digitally synthesize millions of molecular combinations and predict performance before lab testing. Finelli describes a reinforcing cycle where AI improves materials that in turn enable better AI infrastructure.
25
30
55
42
55
55