Jfrog Ltd Stock Price, News & Analysis

JFrog (Nasdaq: FROG), creator of the Software Supply Chain Platform, has announced its participation in four major investor conferences during Q2 2025. The company will present at:

• J.P. Morgan Technology, Media & Communications Conference in Boston (May 13, 5:50 AM PDT)
• TD Cowen TMT Conference in New York (May 28, 8:25 AM PDT)
• William Blair Growth Stock Conference in Chicago (June 3, 12:00 PM PDT)
• Bank of America Global Technology Conference in San Francisco (June 5, 10:00 AM PDT)

All presentations will be accessible via live webcasts and replays through JFrog's investor relations website.

JFrog (Nasdaq: FROG), the Liquid Software company and creator of the JFrog Software Supply Chain Platform, has scheduled its first quarter 2025 financial results announcement for Thursday, May 8, 2025, after market close. The company will hold a conference call to discuss the quarterly results at 2:00 p.m. PT (5:00 p.m. ET) on the same day. Interested parties can access the webcast through the company's investor relations website.

JFrog (NASDAQ: FROG) has released its Software Supply Chain State of the Union 2025 report, revealing critical security challenges in the AI era. The study, based on insights from 1,400+ professionals across six countries and data from 7K+ customers, highlights a 'Quad-fecta' of security threats: CVEs, malicious packages, secrets exposure, and misconfigurations.

Key findings show a 64% year-over-year increase in exposed secrets/tokens in public registries, totaling 25,229 instances. The report also reveals that while 94% of companies use certified lists for ML model governance, 37% rely on manual validation. Additionally, only 43% of organizations implement both code and binary level security scans, down from 56% last year.

The study identified over 33K new CVEs in 2024, marking a 27% increase from 2023. Notably, only 12% of CVEs rated as 'critical' were found to truly justify that severity level, indicating potential scoring inflation that may lead to unnecessary remediation efforts and developer burnout.

JFrog (NASDAQ: FROG) announced a partnership with Hugging Face to enhance security scanning for machine learning models in the Hugging Face Hub. The integration will display a 'JFrog Certified' checkmark to indicate safer models for use.

JFrog's Advanced Security scanning capabilities have already identified 25 zero-day malicious models on Hugging Face that were previously undetected by other scanners. The company's enhanced approach eliminates over 96% of false positives compared to existing solutions.

The partnership addresses critical security challenges in AI/ML development, as surveys indicate that while 80% of enterprises use or experiment with AI applications, over 90% feel unprepared for AI security challenges. The integration aims to protect against threats including model serialization attacks, known CVEs, and backdoors throughout the ML model lifecycle.

JFrog (NASDAQ: FROG) has launched JFrog ML, a revolutionary MLOps solution integrated into the JFrog Platform, marking the first product release following the QWAK.ai acquisition in 2024. This solution unifies DevOps, DevSecOps, and MLOps practices, enabling teams to develop and deploy enterprise-ready AI applications at scale.

The platform offers unique features including enterprise-grade model security scanning, unified model management alongside software artifacts, and simplified model deployment processes. JFrog ML integrates with major AI platforms including Hugging Face, AWS Sagemaker, MLflow, and NVIDIA NIM.

Key capabilities include:

• A unified DevOps and MLSecOps platform
• Secured ML model scanning for malicious or vulnerable models
• Single AI system of record for ML models and datasets
• Intuitive model serving to production
• Complete dataset management and monitoring
• Support for NVIDIA NIM enterprise-grade AI models

JFrog (NASDAQ: FROG) announces general availability of its integration with NVIDIA NIM microservices, offering the industry's only unified DevSecOps and MLOps solution with native NVIDIA NIM integration. This collaboration enables secure deployment of GPU-optimized machine learning models and large language models (LLMs) including Meta's Llama 3 and Mistral AI.

The integration addresses key challenges in AI implementation by providing:

• Unified ML & DevOps workflows for versioning, securing, and deploying models
• End-to-end security scanning and threat detection for AI models
• Optimized performance using NVIDIA accelerated computing infrastructure
• Seamless access to NVIDIA NGC for GPU-optimized models

According to IDC, by 2028, 65% of organizations will use DevOps tools combining MLOps, LLMOps, DataOps, CloudOps, and DevOps capabilities to optimize AI value in software delivery processes.