us voter | Breaking Cybersecurity News | The Hacker News

Information on more than 198 Million United States citizens, that's over 60% of the US population, was exposed in what's believed to be the largest ever known exposure of voter-related to date. This blunder was caused by Deep Root Analytics (DRA) , a data analytics firm employed by the US Republican National Committee (RNC), who "mistakenly" left sensitive personal details of more than 198 million US voters exposed on an unsecured Amazon S3 server. Chris Vickery, a security researcher at UpGuard, who discovered the exposed database said anyone could have downloaded more than a Terabytes of files containing voters data without the need for any password from the Amazon S3 server maintained by DRA. Vickery is the same security researcher who discovered over 191 million voter records stored in an unsecured database in late 2015. In April, Vickey also reported information on 93 million Mexican voters. Vickery discovered the exposed databases on June 12, which...

BREAKING: A misconfigured database has resulted in the exposure of around 191 Million voter records including voters' full names, their home addresses, unique voter IDs, date of births and phone numbers. The database was discovered on December 20th by Chris Vickery , a white hat hacker, who was able to access over 191 Million Americans' personal identifying information (PII) that are just sitting in the public to be found by anyone looking for it. Vickery is the same security researcher who uncovered personal details of 13 Million MacKeeper users two weeks ago, which included names, email addresses, usernames, password hashes, IP addresses, phone numbers, and system information. However, the recent discovery made him shocked when he saw his own information in the database, according to DataBreaches.net, whom the researcher contacted and provided all the details about his finding. 300GB Trove of Voters' Information Leaked Vickery has his hands on all ...

As SaaS providers race to integrate AI into their product offerings to stay competitive and relevant, a new challenge has emerged in the world of AI: shadow AI.  Shadow AI refers to the unauthorized use of AI tools and copilots at organizations. For example, a developer using ChatGPT to assist with writing code, a salesperson downloading an AI-powered meeting transcription tool, or a customer support person using Agentic AI to automate tasks – without going through the proper channels. When these tools are used without IT or the Security team's knowledge, they often lack sufficient security controls, putting company data at risk. Shadow AI Detection Challenges Because shadow AI tools often embed themselves in approved business applications via AI assistants, copilots, and agents they are even more tricky to discover than traditional shadow IT. While traditional shadow apps can be identified through network monitoring methodologies that scan for unauthorized connections based on...