Two Supermicro BMC flaws (CVE-2025–7937, 6198) bypass signature checks, risking persistent server compromise
Category: security – Page 4
U.S. Secret Service Seizes 300 SIM Servers, 100K Cards Threatening U.S. Officials Near UN
The U.S. Secret Service on Tuesday said it took down a network of electronic devices located across the New York tri-state area that were used to threaten U.S. government officials and posed an imminent threat to national security.
“This protective intelligence investigation led to the discovery of more than 300 co-located SIM servers and 100,000 SIM cards across multiple sites,” the Secret Service said.
The devices were concentrated within a 35-mile (56 km) radius of the global meeting of the United Nations General Assembly in New York City. An investigation into the incident has been launched by the Secret Service’s Advanced Threat Interdiction Unit.
China develops fabric that withstands 2,192°F heat with ease
A Chinese company has showcased new types of fabrics that can withstand extreme temperatures. Some of the fabric materials presented were waterproof and windproof while remaining breathable.
Safmax presented these advanced fabrics at the second Public Security Tech Expo in Lianyungang, China.
The company’s new flame-retardant material can withstand temperatures up to 2,192 degree Fahrenheit (1,200 degrees Celsius). This fabric can maintain its structure without deforming, shrinking, or melting.
This type of fabric can be used in firefighting suits and fire blankets to isolate airflow during battery fires in new energy vehicles.
Safmax’s new flame-retardant material can withstand high temperatures maintaining its structure without deforming, shrinking, or melting.
ShadowLeak Zero-Click Flaw Leaks Gmail Data via OpenAI ChatGPT Deep Research Agent
ShadowLeak zero-click flaw in ChatGPT Deep Research leaks Gmail data via hidden HTML prompts, bypassing security
Space Habitat Clusters & Conglomerations
Space isn’t just for lonely colonies—it’s for communities. Join us as we imagine constellations of space habitats bound by tethers, trade, and trust, building not just homes in the stars but entire civilizations.
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Credits:
Space Habitat Clusters & Conglomerations.
Written, Produced & Narrated by: Isaac Arthur.
Graphics: Jarred Eagley, Jeremy Jozwik, Udo Schroeter.
Select imagery/video supplied by Getty Images.
Music Courtesy of Stellardrone and Epidemic Sound http://epidemicsound.com/creator.
Chapters.
0:00 Intro.
1:13 Why Clustered Habitats?
6:00 Habitat Types and Roles Within Clusters.
9:41 Mobility and Modularity – The Politics of Moveable Worlds.
14:02 Tethers, Transit, and Shared Infrastructure.
17:35 Shapes of Clusters and Dynamic Conglomerations.
23:43 Nebula.
25:21 Digital Ecosystems and Cultural Identity.
25:19 Economics and Trade in Habitat Constellations.
26:52 Education and Intergenerational Planning.
28:17 Security and Conflict Management.
29:10 A Tale of Unity.
32:29 Religion, Ritual, and Meaning.
33:19 The Long View: Legacy and Civilization.
34:07 Closing Reflections
Doing The Math On CPU-Native AI Inference
A number of chip companies — importantly Intel and IBM, but also the Arm collective and AMD — have come out recently with new CPU designs that feature native Artificial Intelligence (AI) and its related machine learning (ML). The need for math engines specifically designed to support machine learning algorithms, particularly for inference workloads but also for certain kinds of training, has been covered extensively here at The Next Platform.
Just to rattle off a few of them, consider the impending “Cirrus” Power10 processor from IBM, which is due in a matter of days from Big Blue in its high-end NUMA machines and which has a new matrix math engine aimed at accelerating machine learning. Or IBM’s “Telum” z16 mainframe processor coming next year, which was unveiled at the recent Hot Chips conference and which has a dedicated mixed precision matrix math core for the CPU cores to share. Intel is adding its Advanced Matrix Extensions (AMX) to its future “Sapphire Rapids” Xeon SP processors, which should have been here by now but which have been pushed out to early next year. Arm Holdings has created future Arm core designs, the “Zeus” V1 core and the “Perseus” N2 core, that will have substantially wider vector engines that support the mixed precision math commonly used for machine learning inference, too. Ditto for the vector engines in the “Milan” Epyc 7,003 processors from AMD.
All of these chips are designed to keep inference on the CPUs, where in a lot of cases it belongs because of data security, data compliance, and application latency reasons.
6 Browser-Based Attacks Security Teams Need to Prepare For Right Now
Attacks that target users in their web browsers have seen an unprecedented rise in recent years. In this article, we’ll explore what a “browser-based attack” is, and why they’re proving to be so effective.
What is a browser-based attack?
First, it’s important to establish what a browser-based attack is.
New layered material successfully confines terahertz light to the nanoscale
A new study has successfully demonstrated the confinement of terahertz (THz) light to nanoscale dimensions using a new type of layered material. This could lead to improvements in optoelectronic devices such as infrared emitters used in remote controls and night vision and terahertz optics desired for physical security and environmental sensing.
The paper, “Ultraconfined terahertz phonon polaritons in hafnium dichalcogenides,” is published in Nature Materials. The research was led by Josh Caldwell, professor of mechanical engineering and Director of the Interdisciplinary Materials Science graduate program at Vanderbilt University, and Alex Paarmann of the Fritz Haber Institute in collaboration with Prof. Lukas M. Eng from the Technische Universität Dresden (TUD), Germany.
While THz technology promises high-speed data processing, integrating it into compact devices has been challenging due to its long wavelength. Traditional materials have struggled to confine THz light effectively, limiting the potential for miniaturization.
AI system leverages standard security cameras to detect fires in seconds
Fire kills nearly 3,700 Americans annually and destroys $23 billion in property, with many deaths occurring because traditional smoke detectors fail to alert occupants in time.
Now, the NYU Fire Research Group at NYU Tandon School of Engineering has developed an artificial intelligence system that could significantly improve fire safety by detecting fires and smoke in real-time using ordinary security cameras already installed in many buildings.
Published in the IEEE Internet of Things, the research demonstrates a system that can analyze video footage and identify fires within 0.016 seconds per frame—faster than the blink of an eye—potentially providing crucial extra minutes for evacuation and emergency response. Unlike conventional smoke detectors that require significant smoke buildup and proximity to activate, this AI system can spot fires in their earliest stages from video alone.