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Cybersecurity researchers have disclosed multiple security flaws impacting open-source machine learning (ML) tools and frameworks such as MLflow, H2O, PyTorch, and MLeap that could pave the way for code execution
Cybersecurity researchers have uncovered nearly two dozen security flaws spanning 15 different machine learning (ML) related open-source projects
A little over three dozen security vulnerabilities have been disclosed in various open-source artificial intelligence (AI) and machine learning (ML) models, some of which could lead to remote code execution and information theft
Cybersecurity researchers are warning about the security risks in the machine learning (ML) software supply chain following the discovery of more than 20 vulnerabilities that could be exploited to target MLOps platforms
Also: Dangers of Malicious Code Embedded in ML Models; Is Ransomware in Decline?AI's influence on social engineering and election security has become a focal point at Black Hat. ISMG editors discuss how advanced technologies are making it easier to manipulate people and compromise security systems and offer key insights on machine learning vulnerabilities.
Data-Poisoning Attacks Are Critical Threat to Machine Learning Security, NIST WarnsMachine learning systems continue are vulnerable to cyberattacks that could allow hackers to evade security and prompt data leaks, scientists at the National Institute of Standards and Technology warned. There is "no foolproof defense" against some of these attacks, researchers said.
The company released NB Defense, ModelScan, and Rebuff, which detect vulnerabilities in machine learning systems, on GitHub.
In today's digital landscape, your business data is more than just numbers—it's a powerhouse. Imagine leveraging this data not only for profit but also for enhanced AI and Machine Learning (ML) threat detection
Why Data Exfiltration Detection is Paramount? The world is witnessing an exponential rise in ransomware and data theft employed to extort companies. At the same time, the industry faces numerous critical vulnerabilities in database software and company websites. This evolution paints a dire picture of data exposure and exfiltration that every security leader and team is grappling with. This
The third iteration of the Exploit Prediction Scoring System (EPSS) performs 82% better than previous versions, giving companies a better tool for evaluating vulnerabilities and prioritizing patching.
Four different Microsoft Azure services have been found vulnerable to server-side request forgery (SSRF) attacks that could be exploited to gain unauthorized access to cloud resources
Newly disclosed RCE flaw in Cosmos DB's Jupyter Notebook feature highlights some of the weaknesses that can arise from emerging tech in the cloud-native and machine learning worlds.
As many as 350,000 open source projects are believed to be potentially vulnerable to exploitation as a result of a security flaw in a Python module that has remained unpatched for 15 years
Code hosting platform GitHub today launched new machine learning-based code scanning analysis features that will automatically discover more common security vulnerabilities before they end up in production. [...]