Google has agreed to pay $1.375 billion to settle two major privacy lawsuits filed by the state of Texas, marking one of the largest legal recoveries from the tech giant in a state-level data privacy case.

Allegations of Unlawful Data Collection

The lawsuits, originally filed in 2022 by Texas Attorney General Ken Paxton, accused Google of illegally collecting and storing users’ personal data, including: location, tracking private “incognito” mode searches, and capturing voice and facial recognition data—all without proper user consent.

“For years, Google secretly tracked people’s movements, private searches, and even their voiceprints and facial geometry through their products and services,”

Paxton said in a statement.

“In Texas, Big Tech is not above the law. I fought back and won.”

Paxton’s office called the resolution the largest recovery nationwide by any state attorney general for enforcement of privacy laws against Google.

No Admission of Wrongdoing

Google is settling the lawsuits without admitting any wrongdoing or liability and without making changes to its current products or services. In a statement, spokesperson José Castañeda said the cases involved outdated policies.

“This settles a raft of old claims, many of which have already been resolved elsewhere, concerning product policies we have long since changed,”

Castañeda said.

“We are pleased to put them behind us, and we will continue to build robust privacy controls into our services.”

Legal Context and Background

The litigation is part of a broader wave of privacy and antitrust scrutiny against Big Tech. The Texas case echoes a similar lawsuit settled last year by Meta—Facebook’s parent company—for its use of facial recognition technology, also led by Paxton’s office.

Google has previously pushed back against the Texas suits. In one instance, an appeals court found the company lacked sufficient ties to Texas to be sued there. Google also argued that its products had been mischaracterized, stating, for example, that Google Photos only scans users’ faces to group similar images and does not use that data for advertising.

The settlement also follows a string of high-profile antitrust rulings against Google. U.S. courts recently found that the company had illegally maintained monopolies in web search and advertising technology, with remedies under consideration—including a possible divestment of its Chrome browser business. Google has said it intends to appeal both decisions.

Image: Freepik

President Donald Trump has dismissed Shira Perlmutter, the Register of Copyrights and head of the U.S. Copyright Office, in a move that is drawing sharp criticism from lawmakers and legal observers. The firing, first reported by CBS News and Politico, was effectively confirmed through a statement by Representative Joe Morelle, the top Democrat on the House Administration Committee.

A Sudden Dismissal with AI Implications

“This is a brazen, unprecedented power grab with no legal basis,”

Morelle said in response to the firing. He suggested that the decision came directly in retaliation to Perlmutter’s refusal to endorse Elon Musk’s attempts to use copyrighted material to train artificial intelligence models.

Perlmutter, who assumed the position in 2020 during Trump’s first term, was appointed by Carla Hayden, the Librarian of Congress, who was also reportedly dismissed by Trump earlier this week.

The news comes amid heightened tensions surrounding the use of copyrighted content to train generative AI systems—an issue at the heart of a growing number of legal and policy battles.

The Copyright Office’s Position on AI and Fair Use

The firing coincided with the pre-release of Part III of a comprehensive report from the U.S. Copyright Office examining the intersection of copyright and artificial intelligence. While the report does not explicitly reference Elon Musk or his companies, it offers detailed commentary on the legal boundaries of training AI systems using copyrighted works.

According to the report, although certain uses such as research and analysis may fall under the legal doctrine of fair use, “making commercial use of vast troves of copyrighted works to produce expressive content that competes with them in existing markets” likely falls outside of fair use protections—especially if the content was accessed illegally.

The Office ultimately concludes that government regulation would be “premature” at this stage but supports the continued development of licensing markets. It also recommends considering “alternative approaches such as extended collective licensing” to address potential market failures.

Musk’s Role and Broader Tech Tensions

The situation is further complicated by the involvement of Elon Musk, a longtime Trump ally and a co-founder of both OpenAI and rival startup xAI, which is being integrated into X (formerly Twitter). Musk has voiced support for Jack Dorsey’s provocative call to “delete all IP law,” a sentiment that has stirred controversy in tech and legal circles alike.

While Musk has not publicly commented on Perlmutter’s firing, Trump acknowledged the story by “ReTruthing” a post from conservative attorney Mike Davis, who ironically appeared to disapprove of the move:

“Now tech bros are going to attempt to steal creators’ copyrights for AI profits.”

Meanwhile, OpenAI and other AI companies are currently facing multiple lawsuits alleging copyright infringement. The company has publicly advocated for legislative clarity that would allow AI developers to operate under expanded fair use protections—a move likely to face resistance from artists, authors, and lawmakers concerned about creative rights.

Looking Ahead

As generative AI continues to reshape the media, tech, and legal landscapes, the abrupt removal of the nation’s top copyright official underscores the growing political and economic stakes. With Perlmutter’s departure and the Copyright Office’s critical report now in circulation, the question of how U.S. law should adapt to the AI era is more urgent than ever.

Image Credit: 

Gage Skidmore from Surprise, AZ, United States of America

At its Delivering the Future event in Dortmund, Germany, Amazon announced the debut of Vulcan, a groundbreaking robot that introduces a fundamental new capability to warehouse automation: the sense of touch.

Unlike previous robotic systems that rely primarily on vision and pre-programmed motions, Vulcan is engineered to physically “feel” the objects it handles—offering a major leap forward in dexterity, safety, and efficiency across Amazon’s vast network of fulfillment centers.

“Vulcan represents a fundamental leap forward in robotics,”

said Aaron Parness, Amazon’s Director of Applied Science.

“It’s not just seeing the world, it’s feeling it—enabling capabilities that were impossible for Amazon robots until now.”

The announcement was made via Amazon’s official blog post and showcased how Vulcan is already transforming warehouse operations in locations such as Spokane, Washington, and Hamburg, Germany.

From “Numb and Dumb” to Tactile Intelligence

While robots have become adept at tasks ranging from autonomous driving to cleaning pet hair, most commercial units lack a sense of touch—rendering them fragile or clumsy in environments that require nuance.

“In the past, when industrial robots have unexpected contact, they either emergency stop or smash through that contact,”

said Parness.

“They often don’t even know they have hit something.”

This is the problem Vulcan was built to solve.

Equipped with advanced force-feedback sensors and an “end of arm tooling” system that mimics human-like grip adjustments, Vulcan can manipulate items with care—gently repositioning objects inside densely packed bins without causing damage.

Its design resembles a ruler attached to a hair straightener, where:

• The ruler component makes space in crowded bins,
• The paddles grip and insert items using built-in conveyor belts that help “zhoop” them into place.

Vulcan’s ability to pick and stow items makes our associates’ jobs easier—and our operations more efficient.

Built for the Bin: Solving Amazon’s Unique Storage Challenge

In Amazon’s warehouses, items are stored in fabric-covered pods split into one-foot square compartments—each containing up to ten items. The irregularity and density of these compartments have long posed a challenge to robotic systems.

While earlier robots like Sparrow, Cardinal, and Robin relied on computer vision and suction cups to handle packages, they lacked the tactile intelligence to finesse objects in tight spaces. Vulcan, however, changes the game.

Using a suction-based picking arm guided by a camera and stereo vision system, Vulcan identifies items and the best gripping points while avoiding accidental co-extraction of surrounding objects—an error engineers refer to as “co-extracting non-target items.”

Vulcan can pick and stow about 75% of the diverse inventory found in fulfillment centers, performing at speeds that rival Amazon’s human workers. And when it encounters an object it can’t confidently handle, it’s smart enough to call in a human colleague—striking a balance between AI autonomy and human judgment.

Vulcan uses an arm that carries a camera and a suction cup to pick items from our storage pods.

Enhancing Safety and Ergonomics for Employees

One of Vulcan’s key contributions is in improving worker safety and reducing ergonomic strain.

Traditionally, reaching items stored in the top or bottom rows of pods—some as high as eight feet—required workers to use ladders or stoop to floor level. Vulcan now handles these less ergonomic zones, allowing employees to work comfortably at waist height.

“Working alongside Vulcan, we can pick and stow with greater ease,”

said Kari Freitas Hardy, a front-line employee at Amazon’s Spokane facility.

“It’s great to see how many of my co-workers have gained new job skills and taken on more technical roles.”

The company has already deployed over 750,000 robots across its operations, including systems like Proteus, Titan, and Hercules, all built to handle physically demanding tasks. Vulcan is the latest and most advanced addition in this line—focusing on precision and adaptability rather than brute strength.

Vulcan will let our associates spend less time on step ladders and more time working in their power zone.

A Decade of Robotics Innovation

Amazon’s approach to robotics has never been about building flashy tech for its own sake. Instead, the company zeroes in on specific operational problems and builds purpose-driven solutions.

“We pick out important problems and find or develop solutions—we don’t create interesting tech and then look for ways to use it,”

Parness emphasized.

Vulcan’s development began with a simple observation: each time a worker uses a ladder to access a high shelf, efficiency drops and injury risk increases. Tackling this required breakthroughs in physical AI, including:

• Real-world training based on tactile feedback rather than simulation,
• Algorithms to identify item types and bin availability,
• Adaptive grip mechanics to handle everything from tubes of toothpaste to delicate electronics.

Vulcan was trained on thousands of real-world scenarios, and like a child learning through experience, it improves its understanding of object properties through trial and error.

“This is a technology that three years ago seemed impossible,”

Parness said,

“but is now set to help transform our operations.”

Vulcan represents “a technology that three years ago seemed impossible but is now set to help transform our operations,” says Aaron Parness, Amazon’s director of robotics AI.

Empowering the Workforce of the Future

The ripple effects of Vulcan extend beyond automation. As robots take on more of the physical burden, Amazon is investing in reskilling its workforce through programs like Career Choice, helping employees transition into roles like robotics maintenance and automation systems engineering.

With robots now assisting in 75% of customer orders, Amazon’s strategy appears to be less about replacing humans and more about augmenting them—with Vulcan standing as the latest proof that automation and human labor can coexist and even elevate each other.

Images/Photos: Amazon

Google announced on Wednesday the discovery of a new strain of malware, dubbed “LOSTKEYS”, which has been attributed to the Cold River hacking group—an actor previously linked to Russian state interests.

The revelation was detailed in a blog post by Google’s Threat Intelligence Group (GTIG), highlighting the evolving tactics of a threat actor known for targeting high-profile geopolitical entities.

A New Chapter in Cold River’s Toolkit

According to Wesley Shields, a security researcher at Google GTIG, LOSTKEYS represents “a new development in the toolset” of Cold River. The malware is capable of exfiltrating files and transmitting system information back to its operators, enhancing the group’s surveillance and espionage capabilities.

Cold River—also known in cybersecurity circles as Callisto Group or Seaborgium—has been previously linked to Russia’s Federal Security Service (FSB). The group is notorious for its phishing campaigns and credential theft, often aimed at extracting sensitive information from targets aligned with Western institutions and governments.

Recent Campaigns: Intelligence Gathering on Ukraine and the West

The blog notes that Cold River’s activities have persisted into 2025, with observed campaigns in January, March, and April targeting:

• Current and former advisers to Western governments and militaries
• Journalists
• Think tanks
• Non-governmental organizations (NGOs)
• Unnamed individuals associated with Ukraine

These efforts appear to support Russian strategic objectives, consistent with Cold River’s historical operations.

A Track Record of High-Profile Intrusions

Cold River has been implicated in several high-stakes cyber campaigns over the past few years. In the summer of 2022, the group targeted three U.S. nuclear research laboratories, attempting to gain access to highly sensitive scientific data.

Later that year, in an operation exposed in May 2022, the group published the private email correspondence of former MI6 chief Richard Dearlove and other pro-Brexit figures. The campaign appeared to be part of a broader disinformation effort aimed at influencing public discourse in the United Kingdom.

Image: Freepik

Apple is reportedly developing its own AI-driven search engine, a move that could significantly shift the dynamics of its long-standing relationship with Google. The revelation, reported by Bloomberg, suggests Apple may be looking to reduce or even sever its dependency on Google’s search technology—a partnership that has been a cornerstone of both companies’ mobile strategies for over a decade.

A New Chapter in Search

The news comes amid growing interest in next-generation, AI-powered search engines, such as those developed by Perplexity, OpenAI, and Anthropic. These tools use large language models to provide more conversational, context-aware answers—posing a direct challenge to traditional search engines like Google.

Apple appears to be eyeing a similar path. The company is exploring the integration of artificial intelligence into its search experience, possibly laying the groundwork for a native AI search solution across its ecosystem.

Confirmed in Court

Apple’s intent was disclosed during Google’s ongoing antitrust trial, where Eddy Cue, Apple’s Senior Vice President of Services, testified to the shifting search landscape. Cue noted a recent decline in user searches—a trend he attributed to growing adoption of AI-powered tools that offer faster, more relevant results.

Cue also revealed that Apple is “actively looking at” integrating AI search providers—such as OpenAI and Anthropic—directly into its Safari browser, further signaling a break from its reliance on Google.

This shift could have major financial implications. Google currently pays Apple billions annually to remain the default search engine on iOS devices. If Apple ultimately replaces or deprioritizes Google in favor of its own AI solution, it could disrupt a significant revenue stream tied to Google’s advertising business.

Market Reaction

Investors responded swiftly to the potential shake-up. Shares of Alphabet Inc., Google’s parent company, fell more than 7% following the news, erasing over $75 billion in market value. Apple, by contrast, saw a relatively modest decline of around 2%.

The stark contrast reflects growing investor concern that Google could lose its grip on one of the most valuable digital entry points: the default search position on Apple devices.

The Bigger Picture

While Apple has yet to make any official announcements via a press release or public blog post, its ambitions in AI search align with broader trends reshaping the tech industry. As consumer expectations evolve, driven by advances in generative AI and large language models, traditional web search is increasingly being reimagined.

Should Apple move forward with its own AI-powered search product, the move would not only intensify competition in search—it could also redefine how users interact with information on mobile devices.

Image: Apple Newsroom

In a seismic shift for the mobile app economy, a federal judge has ruled that Apple violated a longstanding injunction by continuing to block app developers from directing users to alternative payment systems—potentially costing the tech giant billions and opening the door for new market entrants.

The decision stems from the high-profile legal battle Epic Games, Inc. v. Apple Inc. (Case No. 21-16506), first launched in 2020 when Epic challenged Apple’s control over in-app transactions. U.S. District Judge Yvonne Gonzalez Rogers, who presided over the original case, found Apple in contempt of the 2021 injunction she previously issued. 

The order prohibited Apple from preventing developers from steering users to non-App Store payment methods.

Apple’s Defiance and Legal Fallout

Despite the clear terms of the original injunction, Apple introduced a new 27% fee on purchases made outside the App Store—a move the court interpreted as a tactic to maintain its dominant revenue model.

In her ruling, Judge Gonzalez Rogers stated:

“Apple, despite knowing its obligations thereunder, thwarted the Injunction’s goals, and continued its anticompetitive conduct solely to maintain its revenue stream.”

The court also referred Apple’s Vice President of Finance, Alex Roman, to the U.S. Attorney’s Office for potentially lying under oath about the fee’s timing—an unprecedented escalation that signals the court’s frustration with Apple’s noncompliance.

Apple has filed for an emergency stay with the Ninth Circuit Court of Appeals, hoping to pause the enforcement of the ruling during the appeals process.

Consequences for Apple—and the Entire Tech Landscape

This decision does more than punish Apple; it redefines how app commerce can function on iOS. The ruling confirms that developers must be allowed to include in-app links or buttons directing users to alternative payment platforms.

Here’s what it could mean going forward:

1. Rise of Third-Party Payment Solutions

The ruling creates fertile ground for a wave of fintech innovation. Startups and established players like Stripe, PayPal, and Adyen are likely to roll out mobile-native payment tools that integrate seamlessly into apps. These solutions could offer lower fees, better user experience, and more flexible payment models, threatening Apple’s dominance.

2. Reduced Costs and New Business Models for Developers

Smaller developers and content creators—long squeezed by Apple’s 15–30% commission—now have a chance to take control of their payment flow. Subscription-based apps, games, and streaming services may lower prices or introduce new service bundles via direct web links.

3. Global Ripple Effects

This case complements regulatory moves abroad, including the EU’s Digital Markets Act and South Korea’s App Store reform. Together, these efforts are reshaping global norms around platform governance and competition.

4. Apple’s Next Move: Compliance or Control?

While Apple must comply with the order, industry analysts expect the company to introduce new terms that retain some leverage—such as additional security vetting, administrative fees, or user interface restrictions for apps using third-party payments.

“This ruling may mark the beginning of a parallel app commerce economy—one where Apple no longer owns the toll booth,”

said Antonia Ramirez, a legal scholar focused on digital markets.

“It’s not just a legal victory for developers—it’s a green light for innovation.”

Looking Ahead

Apple’s appeal may yet delay the practical implementation of the ruling, but the legal foundation has been laid. The mobile app ecosystem—long shaped by Apple’s strict controls—now faces a reckoning. Developers, users, and competitors alike are watching closely as the rules of digital commerce are rewritten in real time.

Image: Freepik

IBM has introduced a suite of new technologies aimed at scaling enterprise AI across hybrid environments, as announced today at its annual THINK conference. This move reinforces IBM’s commitment to breaking down barriers to AI deployment with integrated solutions that unify data, orchestrate AI agents, and simplify enterprise operations.

With over one billion applications projected to emerge by 2028, businesses are under increasing pressure to streamline operations across fragmented systems. IBM is responding with hybrid technologies, enhanced agent capabilities, and the consulting expertise of IBM Consulting, aiming to help clients accelerate AI adoption and realize measurable business value.

Arvind Krishna, Chairman and CEO of IBM

“The era of AI experimentation is over,”

said Arvind Krishna, Chairman and CEO of IBM.

“Today’s competitive advantage comes from purpose-built AI integration that drives measurable business outcomes.”

Enterprise AI Agents Powered by watsonx Orchestrate

Central to IBM’s announcement is the expanded functionality of watsonx Orchestrate, designed to help businesses create, deploy, and manage AI agents across a wide array of enterprise tools.

Key features include:

• Agent Builder: Enables users to create custom AI agents in under five minutes using no-code to pro-code tools.
• Pre-built Domain Agents: Ready-to-use agents tailored for HR, sales, procurement, and more.
• Wide Integration: Supports over 80 leading enterprise applications, including solutions from Adobe, AWS, Microsoft, Oracle, Salesforce Agentforce, SAP, ServiceNow, and Workday.
• Agent Orchestration: Coordinates multi-agent workflows and tools across vendors.
• Agent Observability: Provides monitoring, guardrails, and lifecycle governance.

IBM also unveiled the Agent Catalog, offering access to over 150 agents and tools co-developed with partners like Box, Mastercard, Symplistic.ai, 11x, and others. Sample integrations include a Salesforce-native prospecting agent and a conversational HR agent for Slack.

Tackling Integration Challenges with webMethods Hybrid Integration

A common obstacle to enterprise AI adoption is integration complexity. IBM is addressing this with the launch of webMethods Hybrid Integration, a solution for automating workflows across applications, APIs, partners, and clouds.

According to a Forrester Total Economic Impact (TEI) study, organizations using webMethods realized:

• 176% ROI over three years
• 40% reduction in downtime
• Up to 67% time savings on project execution
• Improved ease of use, security, and visibility

This integration technology complements IBM’s existing automation offerings and is enhanced by collaborations with HashiCorp, including integrations with Terraform and Vault, to support secure, scalable hybrid cloud operations.

Unlocking the Value of Unstructured Data

Unstructured data—such as contracts, spreadsheets, and presentations—represents a largely untapped asset in enterprise AI. IBM is advancing watsonx.data to help organizations activate this data with greater accuracy.

Highlights include:

• Open Data Lakehouse: Now with data fabric features like lineage tracking and governance.
• watsonx.data integration: A unified tool for orchestrating data pipelines across formats.
• watsonx.data intelligence: AI-driven tools for deep insights from unstructured data.

Early testing indicates watsonx.data enables up to 40% more accurate AI compared to traditional retrieval-augmented generation (RAG) methods.

In support of this strategy, IBM recently announced plans to acquire DataStax, a leader in unstructured data handling for generative AI. Additionally, watsonx is now integrated with Meta’s Llama Stack, further enhancing its generative AI capabilities.

IBM’s Content-Aware Storage (CAS) is also now available on IBM Fusion, with support for IBM Storage Scale arriving in Q3. CAS enables contextual processing of unstructured data to speed up AI inferencing.

Infrastructure for AI at Scale: Introducing IBM LinuxONE 5

To support high-performance AI workloads, IBM introduced IBM LinuxONE 5, its most secure and powerful Linux platform to date. It can process up to 450 billion AI inference operations per day.

Innovations include:

• Telum II AI Processor & IBM Spyre Accelerator: High-speed processing for generative AI, with Spyre available in late 2025.
• Confidential Containers & Quantum-Safe Encryption: Advanced security for sensitive workloads.
• Cost and Energy Efficiency: Compared to x86 systems, LinuxONE 5 can lower total cost of ownership by up to 44% over five years.

IBM also expanded partnerships with AMD, Intel, CoreWeave, and NVIDIA to deliver new compute and storage solutions for AI-driven applications.

The Road Ahead

IBM’s latest announcements represent a strategic push toward operationalizing AI at enterprise scale through modular, secure, and hybrid-ready technologies. As businesses move from AI experimentation to enterprise-wide adoption, IBM aims to be the infrastructure backbone enabling that transformation.

Image: IBM video

Zencoder, a provider of AI agents integrated directly into developers’ environments, announced today that it has acquired Machinet, a developer of context-aware AI coding assistants with over 100,000 downloads in JetBrains IDEs. The strategic acquisition further cements Zencoder’s position in the rapidly expanding AI coding assistant market, while broadening its multi-integration ecosystem across popular development platforms.

Expanding the Developer Experience

Following the acquisition, Machinet users will gain access to a significantly enhanced developer experience, including:

• Enhanced JetBrains Integration

By combining Machinet’s specialized expertise in JetBrains IDEs with Zencoder’s existing support, developers can look forward to even more powerful tools tailored for these widely-used environments.

• Augmented Unit Testing

Machinet’s context-aware unit test generation technology will be integrated with Zencoder’s advanced testing agents, offering developers a more comprehensive and automated testing experience.

• Industry-Leading Customization

Machinet’s developer community will now benefit from Zencoder’s deep capabilities in understanding large codebases, adapting to team-specific coding styles, and aligning with organizational architecture patterns.

“This acquisition aligns perfectly with our mission to turn everyone into a 10x engineer by providing AI solutions that handle routine coding tasks and let developers focus on innovation,”

said Andrew Filev, CEO and Founder of Zencoder.

“By bringing our advanced coding agent to Machinet’s thriving JetBrains community, we’re fulfilling our mission to deliver the best AI coding experience regardless of development environment.”

Streamlined Transition for Customers

As part of the acquisition, Machinet’s domain and marketplace presence will be transferred to Zencoder. Current Machinet customers will receive detailed guidance on transitioning to Zencoder’s platform, which leverages its proprietary Repo Grokking technology and AI agents.

Existing Machinet users will now gain access to Zencoder’s full feature set, including:

• Advanced multi-file editing and refactoring capabilities
• Deep codebase understanding across repositories using Repo Grokking™
• Sophisticated self-repair mechanisms that automatically test and refine outputs
• Expanded integration with over 20 developer tools, including Jira, GitHub, and GitLab
• Access to Zencoder’s specialized coding and unit testing AI agents

Industry-Leading Performance

Earlier this year, Zencoder’s AI platform demonstrated benchmark-breaking performance:

• A 2x improvement over previous best results on SWE-Bench-Multimodal
• State-of-the-art results on the challenging “IC SWE (Diamond)” section of SWE-Lancer, outperforming top published results by 23%

With the integration of Machinet’s technologies, Zencoder aims to further enhance its capabilities, reinforcing its leadership position in AI-assisted software development.

Availability and Next Steps

Zencoder’s full suite of AI coding and testing tools, including the newly enhanced JetBrains integration, is now available through zencoder.ai, with subscription options ranging from free basic plans to comprehensive enterprise solutions.

Current Machinet users will be provided with detailed transition instructions in the coming weeks.

About Zencoder

Based in Silicon Valley, Zencoder offers powerful AI coding and testing agents designed to empower professional developers. Founded by serial entrepreneur Andrew Filev, Zencoder’s globally distributed team of over 50 engineers helps organizations accelerate innovation and ship impactful software faster. The company holds ISO 27001 certification, is SOC 2 Type II compliant, and is in the process of finalizing its ISO 42001 certification.

Snyk has introduced a groundbreaking solution to tackle the next wave of cybersecurity challenges. The company announced the launch of Snyk API & Web, a next-generation Dynamic Application Security Testing (DAST) tool engineered to secure modern, AI-powered applications.

Bridging the Security Gap in AI-Driven Development

Traditional DAST solutions have long struggled to keep up with the rapidly evolving architectures and increasing complexity of APIs brought by AI-centric development. Recognizing this critical need, Snyk acquired Probely in 2024, integrating its advanced DAST capabilities into Snyk’s broader security ecosystem—complementing existing offerings like SAST, SCA, container, and Infrastructure as Code security.

The result is a unified platform that delivers a holistic, end-to-end view of application security throughout the entire Software Development Life Cycle (SDLC).

AI-Powered Innovations for Modern Applications

Snyk API & Web introduces several forward-thinking features designed specifically for the AI era:

• AI-Driven API Testing: Leveraging in-house fine-tuned Large Language Models (LLMs), the platform automates API discovery and vulnerability scanning—detecting complex issues like Broken Object Level Authorization (BOLA) more efficiently.
• Code-Informed Dynamic Testing: By correlating DAST results with SAST findings, Snyk provides deeper context for vulnerabilities, supporting more accurate prioritization and enabling AI-powered auto-remediation via DeepCode AI Fix.
• CI/CD-Ready: Designed with DevOps in mind, the tool offers seamless CI/CD integration, allowing developers to perform self-service scans within pipelines, guided by organizational AppSec policies.

Strategic Vision from the Top

“Our vision is to empower developers and AppSec teams to secure their entire application surface without slowing down innovation,”

said Geva Solomonovich, Snyk CIO.

“Snyk API & Web is the culmination of that vision—bringing together the speed of AI with the depth of full-lifecycle security.”

Momentum and Market Response

Since integrating Probely, Snyk has reported a 245% quarter-over-quarter growth in Annual Recurring Revenue (ARR) for DAST services—a clear signal of strong market demand for modern, AI-augmented security tools.

Looking forward, the company plans to deepen its AI capabilities, broaden API coverage, and provide even richer context for faster, more accurate vulnerability remediation.

In a significant stride towards bolstering software supply chain security, Docker has introduced the Docker Maintained Community Packages (MCP) Catalog and Toolkit. This initiative is designed to offer developers and organizations a repository of secure, high-quality open-source packages maintained directly by Docker, addressing the growing concerns over the integrity and trustworthiness of software components in containerized applications.

The Docker MCP Catalog serves as a curated collection of frequently used open-source packages, selected based on community usage patterns and relevance to contemporary development workflows. By standardizing these images under Docker’s stewardship, the company provides a more trustworthy alternative to packages that are often sourced from less vetted or anonymous contributors.

Complementing the catalog is the Docker MCP Toolkit, an open-source suite of utilities aimed at simplifying the processes of building, testing, and verifying Docker images. This toolkit not only assists developers in reproducing Docker-maintained packages but also empowers contributors to create similarly secure and reliable images tailored to their specific use cases.

“Security remains a top priority for the open source and container ecosystems,”

stated Docker in its official blog post.

“By offering both the catalog and toolkit, we aim to reduce uncertainty in the software supply chain and help teams ship with confidence.”​

Docker’s MCP initiative aligns with broader industry trends emphasizing software supply chain integrity, especially in the wake of high-profile vulnerabilities and dependency attacks. It also supports best practices such as Software Bill of Materials (SBOMs) and digital signing, both of which are integrated into the MCP offerings.

The project is anticipated to see widespread adoption among developers seeking vetted base images, DevOps teams aiming to enhance CI/CD hygiene, and organizations striving to meet compliance standards related to open-source usage.​

Docker encourages community feedback and contributions to the MCP initiative via GitHub, promoting transparency and collaboration in building a more secure container ecosystem.

As threats to the software supply chain continue to evolve, Docker’s MCP Catalog and Toolkit represent a timely and proactive measure towards fortifying one of the most critical layers of modern application infrastructure.