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#intel
Menlo Park, California, USA, 7th August 2025, CyberNewsWire
Hackers tricked workers over the phone at Google, Adidas, and more to grant access to Salesforce data.
Now that we are well into 2025, cloud attacks are evolving faster than ever and artificial intelligence (AI) is both a weapon and a shield. As AI rapidly changes how enterprises innovate, security teams are now tasked with a triple burden: Secure AI embedded in every part of the business. Use AI to defend faster and smarter. Fight AI-powered threats that execute in minutes—or seconds. Security
The Hague, Netherlands, 7th August 2025, CyberNewsWire
The Hague, Netherlands, 7th August 2025, CyberNewsWire
The malicious ad tech purveyor known as VexTrio Viper has been observed developing several malicious apps that have been published on Apple and Google's official app storefronts under the guise of seemingly useful applications. These apps masquerade as VPNs, device "monitoring" apps, RAM cleaners, dating services, and spam blockers, DNS threat intelligence firm Infoblox said in an exhaustive
Using invisible prompts, the attacks demonstrate a physical risk that could soon become reality as the world increasingly becomes more interconnected with artificial intelligence.
Recent developments and an escalating trade war have made travel to cities like Beijing challenging but by no means impossible.
For likely the first time ever, security researchers have shown how AI can be hacked to create real world havoc, allowing them to turn off lights, open smart shutters, and more.
A Regular Expression Denial of Service (ReDoS) vulnerability exists in the Hugging Face Transformers library, specifically in the `convert_tf_weight_name_to_pt_weight_name()` function. This function, responsible for converting TensorFlow weight names to PyTorch format, uses a regex pattern `/[^/]*___([^/]*)/` that can be exploited to cause excessive CPU consumption through crafted input strings due to catastrophic backtracking. The vulnerability affects versions up to 4.51.3 and is fixed in version 4.53.0. This issue can lead to service disruption, resource exhaustion, and potential API service vulnerabilities, impacting model conversion processes between TensorFlow and PyTorch formats.