China Sort of Admits to Being Behind Volt Typhoon

The Wall Street Journal has the story:

Chinese officials acknowledged in a secret December meeting that Beijing was behind a widespread series of alarming cyberattacks on U.S. infrastructure, according to people familiar with the matter, underscoring how hostilities between the two superpowers are continuing to escalate.

The Chinese delegation linked years of intrusions into computer networks at U.S. ports, water utilities, airports and other targets, to increasing U.S. policy support for Taiwan, the people, who declined to be named, said.

The admission wasn’t explicit:…

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Silk Typhoon Hackers Indicted

Lots of interesting details in the story:

The US Department of Justice on Wednesday announced the indictment of 12 Chinese individuals accused of more than a decade of hacker intrusions around the world, including eight staffers for the contractor i-Soon, two officials at China’s Ministry of Public Security who allegedly worked with them, and two other alleged hackers who are said to be part of the Chinese hacker group APT27, or Silk Typhoon, which prosecutors say was involved in the US Treasury breach late last year.

[…]

According to prosecutors, the group as a whole has targeted US state and federal agencies, foreign ministries of countries across Asia, Chinese dissidents, US-based media outlets that have criticized the Chinese government, and most recently the US Treasury, which was breached between September and December of last year. An internal Treasury report …

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Cyberattack on Lee Enterprises Causes Disruptions at Dozens of Newspapers

Dozens of local newspapers owned by media company Lee Enterprises experienced disruptions as a result of a cyberattack. 
The post Cyberattack on Lee Enterprises Causes Disruptions at Dozens of Newspapers appeared first on SecurityWeek.
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On Generative AI Security

Microsoft’s AI Red Team just published “Lessons from
Red Teaming 100 Generative AI Products
.” Their blog post lists “three takeaways,” but the eight lessons in the report itself are more useful:

  1. Understand what the system can do and where it is applied.
  2. You don’t have to compute gradients to break an AI system.
  3. AI red teaming is not safety benchmarking.
  4. Automation can help cover more of the risk landscape.
  5. The human element of AI red teaming is crucial.
  6. Responsible AI harms are pervasive but difficult to measure.
  7. LLMs amplify existing security risks and introduce new ones…

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