Pillar Security unveils full-lifecycle AI platform securing assets from design to runtime—critical for safe AI deployment.

A vulnerability in Google’s Gemini CLI allowed attackers to silently execute malicious commands and exfiltrate data from developers’ computers using allowlisted programs.
The flaw was discovered and reported to Google by the security firm Tracebit on June 27, with the tech giant releasing a fix in version 0.1.14, which became available on July 25.
Gemini CLI, first released on June 25, 2025, is a command-line interface tool developed by Google that enables developers to interact directly with Google’s Gemini AI from the terminal.
Attackers could use a recently patched macOS vulnerability to bypass Transparency, Consent, and Control (TCC) security checks and steal sensitive user information, including Apple Intelligence cached data.
TCC is a security technology and a privacy framework that blocks apps from accessing private user data by providing macOS control over how their data is accessed and used by applications across Apple devices.
Apple has fixed the security flaw tracked as CVE-2025–31199 (reported by Microsoft’s Jonathan Bar Or, Alexia Wilson, and Christine Fossaceca) in patches released in March for macOS Sequoia 15.4 with “improved data redaction.”
Khalifa University is building the foundation for a smarter, more secure and more connected world, one silicon chip at a time.
In the rapidly evolving world of artificial intelligence and smart devices, the System-on-Chip Lab (SoCL) at Khalifa University is emerging as a regional hub of innovation. Led by Baker Mohammad, a professor of Computer and Information Engineering and a veteran with 15 years of experience at tech giants Intel and Qualcomm, the lab is uniquely positioned to bridge the gap between fundamental research and market-ready solutions.
“We’re the only facility in the region with comprehensive expertise across the full electronics design stack, from devices to circuits to systems,” Mohammad explains. This distinctive capability allows the lab to address critical challenges in energy-efficient, high-performance edge devices for data-intensive AI applications, while also integrating hardware security to protect sensitive user data.