machine learning | Breaking Cybersecurity News | The Hacker News

Did you know that Network Detection and Response (NDR) has become the most effective technology to detect cyber threats? In contrast to SIEM, NDR offers adaptive cybersecurity with reduced false alerts and efficient threat response. Are you aware of  Network Detection and Response (NDR)  and how it's become the most effective technology to detect cyber threats?  NDR massively upgrades your security through risk-based alerting, prioritizing alerts based on the potential risk to your organization's systems and data. How? Well, NDR's real-time analysis, machine learning, and threat intelligence provide immediate detection, reducing alert fatigue and enabling better decision-making. In contrast to SIEM, NDR offers adaptive cybersecurity with reduced false positives and efficient threat response. Why Use Risk-Based Alerting? Risk-based alerting is an approach where security alerts and responses are prioritized based on the level of risk they pose to an organization's syst...

Google has announced that it's open-sourcing  Magika , an artificial intelligence (AI)-powered tool to identify file types, to help defenders accurately detect binary and textual file types. "Magika outperforms conventional file identification methods providing an overall 30% accuracy boost and up to 95% higher precision on traditionally hard to identify, but potentially problematic content such as VBA, JavaScript, and Powershell," the company  said . The software uses a "custom, highly optimized deep-learning model" that enables the precise identification of file types within milliseconds. Magika implements inference functions using the Open Neural Network Exchange ( ONNX ). Google said it internally uses Magika at scale to help improve users' safety by routing Gmail, Drive, and Safe Browsing files to the proper security and content policy scanners. In November 2023, the tech giant unveiled  RETVec  (short for Resilient and Efficient Text Vectorizer),...

Vulnerability Management (VM) has long been a cornerstone of organizational cybersecurity. Nearly as old as the discipline of cybersecurity itself, it aims to help organizations identify and address potential security issues before they become serious problems. Yet, in recent years, the limitations of this approach have become increasingly evident.  At its core, Vulnerability Management processes remain essential for identifying and addressing weaknesses. But as time marches on and attack avenues evolve, this approach is beginning to show its age. In a recent report, How to Grow Vulnerability Management into Exposure Management (Gartner, How to Grow Vulnerability Management Into Exposure Management, 8 November 2024, Mitchell Schneider Et Al.), we believe Gartner® addresses this point precisely and demonstrates how organizations can – and must – shift from a vulnerability-centric strategy to a broader Exposure Management (EM) framework. We feel it's more than a worthwhile read an...

In nearly every segment of our lives, AI (artificial intelligence) now makes a significant impact: It can deliver better healthcare diagnoses and treatments; detect and reduce the risk of financial fraud; improve inventory management; and serve up the right recommendation for a streaming movie on Friday night. However, one can also make a strong case that some of AI's most significant impacts are in cybersecurity. AI's ability to learn, adapt, and predict rapidly evolving threats has made it an indispensable tool in protecting the world's businesses and governments. From basic applications like spam filtering to advanced predictive analytics and AI-assisted response, AI serves a critical role on the front lines, defending our digital assets from cyber criminals. The future for AI in cybersecurity is not all rainbows and roses, however. Today we can see the early signs of a significant shift, driven by the democratization of AI technology. While AI continues to empower organizations ...

Continuous integration and continuous delivery (CI/CD) misconfigurations discovered in the open-source  TensorFlow  machine learning framework could have been exploited to orchestrate  supply chain attacks . The misconfigurations could be abused by an attacker to "conduct a supply chain compromise of TensorFlow releases on GitHub and PyPi by compromising TensorFlow's build agents via a malicious pull request," Praetorian researchers Adnan Khan and John Stawinski  said  in a report published this week. Successful exploitation of these issues could permit an external attacker to upload malicious releases to the GitHub repository, gain remote code execution on the self-hosted GitHub runner, and even retrieve a GitHub Personal Access Token (PAT) for the  tensorflow-jenkins user . TensorFlow uses GitHub Actions to automate the software build, test, and deployment pipeline. Runners, which refer to machines that execute jobs in a GitHub Actions workflow, can ...

Wing Security announced today that it now offers  free discovery and a paid tier for automated control  over thousands of AI and AI-powered SaaS applications. This will allow companies to better protect their intellectual property (IP) and data against the growing and evolving risks of AI usage. SaaS applications seem to be multiplying by the day, and so does their integration of AI capabilities. According to Wing Security, a SaaS security company that researched over 320 companies, a staggering 83.2% use GenAI applications. While this statistic might not come as a surprise, the research showed that 99.7% of organizations use SaaS applications that leverage AI capabilities to deliver their services. This usage of GenAI in SaaS applications that are not 'pure' AI often goes unnoticed by security teams and users alike. 70% of the most popular GenAI applications may use your data to train their models, and in many cases it's completely up to you to configure it differently...

The U.S. National Institute of Standards and Technology (NIST) is calling attention to the  privacy and security challenges  that arise as a result of increased deployment of artificial intelligence (AI) systems in recent years. "These security and privacy challenges include the potential for adversarial manipulation of training data, adversarial exploitation of model vulnerabilities to adversely affect the performance of the AI system, and even malicious manipulations, modifications or mere interaction with models to exfiltrate sensitive information about people represented in the data, about the model itself, or proprietary enterprise data," NIST  said . As AI systems become integrated into online services at a rapid pace, in part driven by the emergence of generative AI systems like OpenAI ChatGPT and Google Bard, models powering these technologies face a number of threats at various stages of the machine learning operations. These include corrupted training data,...

Google has revealed a new multilingual text vectorizer called  RETVec  (short for Resilient and Efficient Text Vectorizer) to  help detect  potentially harmful content such as spam and malicious emails in Gmail. "RETVec is trained to be resilient against character-level manipulations including insertion, deletion, typos, homoglyphs, LEET substitution, and more," according to the  project's description  on GitHub. "The RETVec model is trained on top of a novel character encoder which can encode all UTF-8 characters and words efficiently." While huge platforms like Gmail and YouTube rely on text classification models to spot phishing attacks, inappropriate comments, and scams, threat actors are known to devise counter-strategies to bypass these defense measures. They have been observed resorting to adversarial text manipulations, which range from the use of homoglyphs to keyword stuffing to invisible characters. RETVec , which works on over 100 langua...

The U.K. and U.S., along with international partners from 16 other countries, have released new guidelines for the development of secure artificial intelligence (AI) systems. "The approach prioritizes ownership of security outcomes for customers, embraces radical transparency and accountability, and establishes organizational structures where secure design is a top priority," the U.S. Cybersecurity and Infrastructure Security Agency (CISA)  said . The goal is to  increase cyber security levels of AI  and help ensure that the technology is designed, developed, and deployed in a secure manner, the National Cyber Security Centre (NCSC)  added . The guidelines also build upon the U.S. government's  ongoing   efforts  to manage the risks posed by AI by ensuring that new tools are tested adequately before public release, there are guardrails in place to address societal harms, such as bias and discrimination, and privacy concerns, and setting up robust ...

Here is what matters most when it comes to artificial intelligence (AI) in cybersecurity: Outcomes.  As the threat landscape evolves and  generative AI is added  to the toolsets available to defenders and attackers alike, evaluating the relative effectiveness of various  AI-based security  offerings is increasingly important — and difficult. Asking the right questions can help you spot solutions that deliver value and ROI, instead of just marketing hype. Questions like, "Can your predictive AI tools sufficiently block what's new?" and, "What actually signals success in a cybersecurity platform powered by artificial intelligence?" As BlackBerry's AI and ML (machine learning) patent portfolio attests, BlackBerry is a leader in this space and has developed an exceptionally well-informed point of view on what works and why. Let's explore this timely topic. Evolution of AI in Cybersecurity Some of the earliest uses of ML and AI in cybersecurity date back to th...

Malicious ads served inside Microsoft Bing's artificial intelligence (AI) chatbot are being used to distribute malware when searching for popular tools. The findings come from Malwarebytes, which revealed that unsuspecting users can be tricked into visiting booby-trapped sites and installing malware directly from Bing Chat conversations. Introduced by Microsoft in February 2023, Bing Chat is an  interactive search experience  that's powered by OpenAI's large language model called  GPT-4 . A month later, the tech giant  began   exploring  placing ads in the conversations. But the move has also opened the doors for threat actors who resort to malvertising tactics and propagate malware. "Ads can be inserted into a Bing Chat conversation in various ways," Jérôme Segura, director of threat intelligence at Malwarebytes,  said . "One of those is when a user hovers over a link and an ad is displayed first before the organic result." In an example highli...

A novel cloud-native cryptojacking operation has set its eyes on uncommon Amazon Web Services (AWS) offerings such as AWS Amplify, AWS Fargate, and Amazon SageMaker to illicitly mine cryptocurrency. The malicious cyber activity has been codenamed  AMBERSQUID  by cloud and container security firm Sysdig. "The AMBERSQUID operation was able to exploit cloud services without triggering the AWS requirement for approval of more resources, as would be the case if they only spammed EC2 instances," Sysdig security researcher Alessandro Brucato said in a report shared with The Hacker News. "Targeting multiple services also poses additional challenges, like incident response, since it requires finding and killing all miners in each exploited service." Sysdig said it discovered the campaign following an  analysis of 1.7 million images  on Docker Hub, attributing it with moderate confidence to Indonesian attackers based on the use of Indonesian language in scripts and use...

There's been a great deal of AI hype recently, but that doesn't mean the robots are here to replace us. This article sets the record straight and explains how businesses should approach AI. From musing about self-driving cars to fearing AI bots that could destroy the world, there has been a great deal of AI hype in the past few years. AI has captured our imaginations, dreams, and occasionally, our nightmares. However, the reality is that AI is currently much less advanced than we anticipated it would be by now. Autonomous cars, for example, often considered the poster child of AI's limitless future, represent a narrow use case and are not yet a common application across all transportation sectors. In this article, we de-hype AI, provide tools for businesses approaching AI and share information to help stakeholders educate themselves.  AI Terminology De-Hyped AI vs. ML AI (Artificial Intelligence) and ML (Machine Learning) are terms that are often used interchangeably, but the...