The npm ecosystem was hit yesterday by a malware attack affecting popular packages like 

. Both packages are typically bundled into frontend builds. Once included, the malicious payload executes.

These attacks are becoming more frequent - we reported on a 

similar attack on npm packages just 12 days ago

How you react depends on what is known about the threat:

The issue is real, but not yet reported in public databases

You cannot automatically detect or block it - your only option is rapid manual actions

The issue is documented and tracked (i.e. it has a CVE or MAL ID)

Security feeds and tools, including Cloudsmith’s Enterprise Policy Management (EPM), can use that tracking to automatically quarantine or block affected packages

, it was considered a zero-day threat (potentially compromised packages were identified, but no official designation yet).

Within 24 hours, these packages were confirmed as malicious, and added to the 

. Cloudsmith and other similar platforms can then OSV.dev updates and thereby enable automated remediations.

We recommend the following actions for all Cloudsmith customers, regardless of whether you’ve confirmed that any affected packages have been used in builds or are currently present in any of your Cloudsmith repositories.

For Zero-day threats - Block with Deny Rules

1. Add [Deny Rules] that block downloads immediately. 

This stops any installs in dev, CI, or production environments.

For this scenario, a simple set of rules targeting the compromised packages/versions would have blocked all download attempts. This protects developers who may not have heard the news yet.

See the end of this article for a full list of Deny Rules.

 to identify who pulled compromised packages and when. Cloudsmith logs are near real-time, so searching for and identifying users andservice accounts that have accessed these packages will help determine potential impact.

For N-Day threats - Quarantine and Flag with EPM

. Put policies in place to quarantine malicious packages that do not have a fix, or have not been verified and granted an exception from your security team.

Our OSV.dev feed refreshes every hour and will detect newly identified malicious packages automatically. This protects you if compromised packages are already in Cloudsmith repositories. In order to enable continuous securityadd an 

 to automatically tag and quarantine new malware.

The gap between zero-day and n-day is when development teams are most exposed. This “lag” introduces risk, against which the fastest defense is Deny Rules.

Once advisories are live and the zero-day is now an n-day, EPM and Continuous Security take over, eliminating manual effort and keeping build pipelines safe.

Looking ahead: smarter protection is coming

Cloudsmith includes detection and protection against malware and vulnerabilities as a native capability in our Ultra and Enterprise tiers. Every artifact in a Cloudsmith repository is, by definition, in a controlled, policy-enforced environment.

We’re working to include more threat intel sources, richer context, and community feeds like deps.dev, along with the ability to bring your own internal threat data into Continuous Security.

Create a Deny Rule for each separate query string.

npm ecosystem alert: What you need to do today with Cloudsmith

I learned to code in BASIC on a Commodore 64 in the early 1980s. BASIC was actually a pretty neat high-level abstraction of assembly language, which itself was an abstraction sitting on top of machine code! Since then, I’ve seen a steady stream of higher-level abstractions - relational databases, object-oriented languages, package dependencies, open source libraries, cloud-native development, containers, serverless - that have made software developers more productive, and helped us build ever more powerful applications with them.

AI is the latest abstraction layer that sits on top of existing technology, making the underlying components more powerful and easier to use. A huge amount of R&D and startup capital in the past few years has gone towards exploiting this new abstraction.

The newest and best ideas naturally attract top talent and funding. Companies and startups building cool new AI-powered apps have their choice of tech stack. And many of them are creating their new software development tool chains around Cloudsmith, which is very satisfying to Cloudsmithers.

, who built an AI-powered platform pathologists use to diagnose cancers. They manage binary packages in Cloudsmith that they use to build for a wide variety of target environments. Or 

, who builds industrial computer vision applications that improve quality and productivity, using Cloudsmith to manage binary artifacts that go into their build pipelines. 

 provides a machine learning platform for document processing and automation, built on Cloudsmith for internal development and external distribution of containers and packages. And 

, who have built an AI-powered due diligence platform, using Cloudsmith as their single source of truth for binary artifacts.

Companies that build critical infrastructure for use by other AI companies are also gravitating to Cloudsmith. Take 

, who helps organizations use, manage, and govern AI metadata with their enterprise-grade context platform. They chose Cloudsmith to make sure their artifacts are reliably and securely distributed to enterprise developers. Or 

, who distributes their SDKs and runtimes via Cloudsmith for delivery of AI-driven perception solutions to robotics and computer vision tool companies. Then there’s 

, an open source AI search platform used to develop and run large-scale applications, combining big data, vector search, machine-learned ranking, and real-time inference to enable AI applications like retrieval-augmented generation, recommendation, and intelligent search at enterprise scale. Cloudsmith supports distribution for Vespa, streamlining delivery for their open source community as well as enterprise users.

And then it’s companies who deliver AI directly to the hands of end users. 

 calls itself “the world’s most private AI,” assisting users in real time across a wide range of personal tasks. They use Cloudsmith to build and distribute packages across the software supply chain.

Cloudsmith is best known for our enterprise-grade artifact management platform, which controls and secures the software supply chain for the world’s most demanding Fortune 500 and Global 2000 organizations. But there’s a reason we also show up so often as the platform of choice for innovative AI startups and spinoffs. These companies are typically run by lean teams of seasoned software engineers. They know what they need, and they want to do it right the first time. They want developer-friendly, well-documented tools that just work.

 to manage their Hugging Face models and datasets, and we’re increasingly powering our own development of new features with AI tools. But it’s also notable that the world’s most interesting AI companies are also choosing Cloudsmith - not just to manage ML models, but to power their entire software supply chain. That’s a vote of confidence that makes us proud to be Cloudsmithers.

The platform of choice for AI companies

In the world of artifact management, a repository structure refers to how software artifacts—such as Docker images, Python packages, npm modules, and more—are organized, stored, and accessed. It defines how repositories are named, grouped, and managed, often aligning with how software development teams build, release, and consume software binaries across an organization.

Repository structure is a fundamental foundation of secure, efficient artifact management practices. Your goal is to create the right structure that meets the needs of your developers.

Cloudsmith has an intrinsically flexible approach to repositories. We don’t force you to have a separate repository for each format type, like most other artifact management systems do. This presents you with an opportunity to define a more meaningful structure for your repositories, and this means you have many more interesting options!

We see some common patterns among Cloudsmith users that fall into the following groups:

We’ll be covering each structure in greater detail in our upcoming blogs as part of our Repository Structure Best Practices series.

Now that we’ve identified the “what” behind repository structures, we can dig into the “why” a little bit.

We address repository structure at the beginning of our onboarding process for new customers. If you get the repo structure wrong, then over time, artifact repositories can become a ‘dumping ground’ for all manner of software artifacts. When platform engineering teams are migrating to Cloudsmith, we find that there’s often a newfound interest in organization and consolidation of software artifacts, in order to ‘do better next time’ than they were able to with their legacy solution.

Perhaps the number one question we get at this point is, “How do we balance software supply chain security best practices with a great developer experience?”

While there isn’t really one simple answer to this question, the good news is that the flexibility Cloudsmith offers in choosing the repository structure can help you to check both boxes – security AND productivity.

Key benefits of the right repository structure

Choosing a clear, intuitive structure removes significant friction for developers. If they are able to easily locate the packages they need, pull the open-source dependencies for their builds in a central location, and integrate quickly with CI/CD pipelines, you’re winning as a platform team already.

Many enterprise customers of Cloudsmith leverage a dedicated repository for all ingress packages, where open-source dependencies are proxied and cached for developers and pipelines to begin accessing. This centralized repository makes it easy for developers to remember the direct path URL for pulling on their local machines and even easier for updating their CI/CD pipelines.

With our API and UI, a developer can quickly review what packages are within a specific repository. No digging through countless folders and subfolders to find what you’re looking for!

You’ll want your developers to be able to pull dependencies, create repositories, and configure upstream sources easily. But you also want to ensure developers are working securely. Repository structure directly influences how platform teams will be able to configure repository access controls, set permissions, review vulnerabilities, and inspect audit trails for suspicious signals.

In Cloudsmith, platform teams can restrict repository access by designating only specific developer teams to have access to specific repositories. At the permissions level, you can set read/write/admin permissions for each repository. This allows for granular access control, self-serve ownership, multiformat flexibility, and better visibility into team-by-team usage.

Observability and auditability of packages within your artifact management environment are directly correlated to how fine-grained your repositories are structured. The more segmented you configure them (i.e., by specific team, application, or environment), the clearer an observability team is able to view when a package was pulled and by whom. On the contrary, if an organization just has “non-prod” and “prod” repositories with many different service accounts and users pulling packages, it might be more difficult to pin down a specific action or event.

The right repository structure really impacts an organization’s CI/CD pipelines. When pipelines are tightly coupled to poorly structured repositories, the result can be pipeline failures due to ambiguous package resolution, security risks from pulling artifacts from the wrong stage, and even increased build times due to inefficiencies in caching.

As your organization grows, what originally worked for your first few developers will often break at scale. Without a flexible, scalable repository structure, you will quickly become susceptible to artifact sprawl, naming collisions, and access control issues. Cloudsmith’s fully cloud-native architecture helps enterprise customers scale tremendously while also maintaining order and consistency across repositories.

Managing Artifacts Across Multiple Formats

Your organization is building all kinds of software, with software development across many different language formats, development teams, and environments to consider. It helps to have an artifact management platform that can support multi-format repositories, flexible upstream configurations to open-source registries, and easy-to-use package tagging.

Balancing Security With Developer Velocity

Tighter security controls and a lack of freedoms can oftentimes frustrate developers, while open policies may create security gaps. A well-thought-out repository structure strikes a balance by allowing autonomy with clear guardrails. This is part of the developer “golden path” that can be architected by a platform team. 

How the right repository structure delivers business value

Faster Software Delivery & Reduced Operational Overhead

When artifacts are easy to find, manage, and deploy, your development teams spend less time figuring out where their artifacts are and more time building great software. Reducing toil and time to market is critical for any business creating software.

Improved Agility for New Development Teams

A well-structured repository architecture supports growth by paving the way for new teams – which may include contractors – to spin up new environments (repos, teams, service accounts, tokens, etc.) by enabling replication across teams. A clear, concise, repeatable structure that only requires a few API calls makes it easier to scale without worrying about the underlying infrastructure to support globally distributed teams.

Reduced Risk With Better Visibility And Controls

Platform teams are tasked with enabling development teams to write software efficiently and securely. By having a well-defined repository structure that every development team can follow, platform teams can create clear access control policies, artifact retention policies, and user permissions. Having this visibility and control lowers the risk of shipping insecure or unverified software.

Cloudsmith’s approach to repository structure

 is a trusted advisor, helping customers design and implement the optimal repository structure that balances security, scalability, and developer productivity to support their software delivery goals.

Stay tuned for the next part of the blog series, where we will discuss the “hybrid” repository approach that factors in an organization’s services, teams, and environments in Cloudsmith.

Why does repository structure matter for developers?

A clear repository structure saves time for developers by making it easy to find and pull the right packages. It also helps avoid confusion in CI/CD pipelines and improves overall productivity.

How does repository structure improve CI/CD pipelines?

When repositories are well-structured, pipelines resolve dependencies faster, reduce build failures, and pull the right artifacts for each stage (dev, test, prod) — making delivery more reliable.

How does repository structure affect security?

Repository structure impacts how access controls, permissions, and audit logs are managed. A good structure ensures that only the right people or services can access sensitive packages.

How does Cloudsmith support flexible repository structures?

 and supports multi-format repositories, fine-grained access controls, upstream proxying for open-source, and automation via API — making it easy to design the structure you need.

How do I choose the right repository structure for my organization?

The right structure depends on your scale, security needs, and workflows. Many teams use a hybrid approach, combining team, environment, and service-based structures for flexibility and control.

Why Repository Structure Matters

attackers published malicious versions of the popular 

 and several plugins to npm, abusing a post-install script (telemetry.js) that ran on Linux and macOS to sweep developer machines and CI for secrets (SSH keys, GitHub/npm tokens, API keys, crypto wallets). Uniquely, the payload also tried to 

co-opt local AI CLI tools (Claude, Gemini, q)

 to help with recon and exfiltration, one of the first documented cases of malware doing so.

 – A vulnerable GitHub Actions workflow was introduced in the Nx repo; although reverted in master on Aug 22, an outdated branch was later exploited to steal a GITHUB_TOKEN with read/write perms and ultimately the npm publish token.

 – Multiple malicious Nx releases and plugins were pushed over ~2 hours; within hours, npm removed them and 

2FA required for all packages and publishing moved to npm’s Trusted Publisher

, and the window, though brief, was enough to 

1,000+ valid GitHub tokens, dozens of valid cloud and npm credentials, and ~20,000 files

 exfiltrated; execution was seen on developer machines (often via the Nx VS Code extension) and in CI (e.g., GitHub Actions).

Cloudsmith integrates this data feed via 

, providing hourly checks against the OpenSSF database. When an already cached or a newly uploaded package is detected as malicious, Continuous Security works with 

 (EPM) to automatically flag and quarantine it, preventing the harmful software from entering your builds.

Cloudsmith offers this capability as a part of our 

 (EPM) feature, a programmable policy-as-code layer that controls the security, compliance, and flow of artifacts across the software supply chain.

When a new threat is discovered that affects an artifact in your workspace, Continuous Security will flag it via EPM without the need for a full manual or scheduled re-scan.

In the Nx incident, entries for nx and related @nx/* packages appeared in the OpenSSF/OSV malicious-package feed within ~24 hours of first detection (e.g., MAL-2025-41443 for npm/nx, plus @nx/devkit, @nx/node, @nx/workspace, and others). With Cloudsmith’s hourly ingestion, these packages would have been automatically flagged and quarantined, shrinking exposure time and limiting downstream blast radius.

You can check out a deeper dive of how EPM uses OSV to detect and block malicious packages here.

: EPM enforces organization-wide rules automatically upon detection (no manual triage to start protecting builds).

: OpenSSF’s open database aggregates cross-ecosystem reports in the OSV schema, which Cloudsmith consumes directly.

Enable EPM and add a Malicious Package policy

 (OSV/OpenSSF source). This is the switch that turns detection into 

Understanding the defense in depth approach: 

A malicious package can be ingested into a build pipeline before threat intelligence sources like OpenSSF or OSV publish indicators, creating a blind spot during which the artifact remains undetected. Mitigating this exposure requires a defense-in-depth strategy: enforce ingress controls at the artifact repository level (e.g., Cloudsmith) to block known and suspicious packages, and implement downstream detection via CI scanners and endpoint monitoring to identify and remove compromised dependencies already in use. 

(This is about realistic risk staging: block new ingress at Cloudsmith; find and purge what’s already inside with endpoint/CI scans.)

: Even though npm has removed the bad Nx versions, follow the incident guidance (rotate tokens/keys, search for s1ngularity-repository* and results.b64, clean shell startup files, audit CI). Wiz and the Nx advisory provide concrete steps.

AI-assisted malware isn’t hypothetical anymore, it’s in mainstream OSS supply chains. Cloudsmith’s 

 that can turn multi-hour chaos into a contained non-event. Pair it with good credential hygiene and CI hardening—and insist on provenance/Trusted Publisher for your own releases, just as the Nx team has done post-incident.

NX npm Supply Chain Attack: How Cloudsmith Would Have Contained the Blast Radius

Typosquatting is now a well-known exploit, whereby malicious actors register domains or package names that are visually similar to popular ones. Examples include misspelling 

 as “expresss” - a mistake we’ve all made when typing too fast under pressure. Normally, when you make a typo retrieving a software package, you just get a build error since the package doesn’t exist. However, adversaries pick up on these subtle behaviours and in the process publish package names, deliberately containing malware, knowing someone is inevitably going to make this mistake at some point.

We just saw this threat has escalated. Instead of just mimicking individual package names in ecosystems like npm or PyPI, attackers are squatting on 

An alarming post by Bruno Schaatsbergen on 

 highlights this issue. A user discovered an active container registry at 

, which is the GitHub Container Registry. The poster warns: “I'm not sure who owns it, but be careful”. And it makes sense, unless investigated further, it’s unclear what is currently being distributed via this fake registry. Funny side note, if you go to the fake (ghrc.io) instead of the correct Github Container Registry address, it displays one of those generic default Nginx web server pages instead of the expected Github redirect (

Again, simple typo, swapping the positions of “r” and “c” leads to a completely different registry. Given that container workflows often operate in scripts or automated pipelines, a single-character mistake can redirect your push or pull operations to an attacker-controlled endpoint.

While it might seem unlikely that this is happening right now in any organisation, a simple 

 would show you that this typo has been made on quite a number of occasions. If your CI/CD workflow is also scripted to push to 

, those images will never reach GitHub, and instead will end up elsewhere. In doing so, the adversaries operating 

 could intercept or modify container images. They might serve backdoored images, leak credentials, or inject exploits. But this stuff is easy to make mistakes with. In logs or configuration files, 

 basically look identical at a glance. Developers may not notice the swap until something breaks, or even worse, when the damage is already done.

But you can take action. As an immediate first step, you can carefully review your registry URLs, especially in automation files like Dockerfiles, CI pipelines, docker push or docker pull commands. Additionally, you could enforce DNS or host-level protections to prevent access to known malicious or typo versions like GHRC. Explicitly only allow the registries that you expect to work with.

 exists as a live container registry masquerading behind a one-letter typo of 

This reflects an escalation from typosquatting individual package names to targeting entire registries.

The implications are severe. As the story evolves, it is worth adopting some vigilance when working with your container registries.

 later clarified that while the 401 response and 

 header are standard parts of the OCI spec, in this case they’re being returned by a server that isn’t a registry at all. The fact that only the 

 endpoint mimics OCI behavior, while the rest of the site is a default nginx install, suggests the setup is intentionally crafted to lure OCI clients into sending credentials to a fake token API.

This scenario highlights why companies should prefer providing developers a registry within their organisation. Having a control plane (like Cloudsmith) in front of registries in which to verify and block things like this fake registry, backed-up by a powerful audit trail for post-incident forensics.

Typosquatting a package? How about typosquatting the whole registry!

In July 2025, two of the npm ecosystem’s most widely used packages became unwitting carriers of malware. The first, 

, was compromised after its maintainer was deceived by a phishing email disguised as a message from npm support. With stolen credentials, attackers published malicious versions that spread rapidly into developer environments worldwide, dragging related packages into the breach.

Shortly afterwards, the seemingly innocuous utility ‘

’ (a lightweight library downloaded more than 2.3 million times each week) was taken over in the same way. For roughly six hours, anyone installing the package, directly or through the countless tools that rely on it, was unknowingly pulling a version laced with a backdoor. What makes this striking is not the sophistication of the malware, but the ubiquity of its host. The ‘is’ Javascript testing library does little more than check whether a value is a number, a string, or empty, yet precisely because it is so simple, it is embedded everywhere. Its compromise meant that risk cascaded across the software ecosystem almost instantly.

These events were part of a broader wave of supply chain attacks in which malicious packages are deliberately seeded into public registries. Analysts now estimate that the OpenSSF’s 

 project tracks more than 35,000 confirmed cases across npm, PyPI and other ecosystems. What once seemed rare is now industrialised.

Traditional vulnerabilities are flaws to be patched. Malicious packages are different. They are intentional weapons that arrive through normal developer workflows; invisible, inherited deep in dependency trees, and executed automatically by build systems. When a package with millions of weekly downloads is compromised, six hours is enough to spread malware worldwide. By the time advisories are published or scanners raise alerts, the damage is already done.

Intelligence is only valuable if it is enforced

Open source intelligence has improved dramatically, and projects like OpenSSF Malicious Packages and OSV.dev provide vital, structured data. But feeds alone do not change outcomes. What matters is whether that intelligence is enforced at the moment a package attempts to enter your organisation. Otherwise it becomes background noise while builds continue to ingest whatever registries serve.

Cloudsmith’s approach to artifact security

 (EPM). Intelligence from OSV.dev and OpenSSF is now integrated directly into Cloudsmith repositories, so known hostile packages can be blocked, quarantined or tagged at the point of entry; before they touch developer machines, CI pipelines, or production builds.

Even with strong ingress enforcement, new vulnerabilities and threats can emerge after artifacts are already in your repositories. A package that was safe yesterday might later be linked to a newly disclosed CVE or malware signature.

 steps in. This feature, available in EPM-enabled workspaces, performs hourly checks of your stored artifacts against up-to-date vulnerability and threat intelligence sources, such as CVE aggregators and EPSS databases. When a new threat is detected in a previously ingested artifact, Continuous Security flags it immediately without relying on manual re-scans or waiting for scheduled checks. This ensures that your repository remains secure not just at the moment of ingestion, but continuously over time, adapting to evolving risks.

The crucial difference between this approach and those of other legacy artifact management platforms is that Cloudsmith treats this as core to artifact management, not as an optional add-on. When security is sold separately, it is inconsistently applied and easy to bypass. In Cloudsmith it is inseparable from the platform itself, which means every package is subject to the same level of scrutiny the moment it arrives.

), organisations can tune enforcement to their own needs; strict blocking in production, tagging in development, quarantining for review in sensitive environments. Developers do not need to stop and think about dependency safety: those controls are enforced automatically, enabling development teams to move quickly without increasing risk.

Why a unified multi-format repository matters

Attackers are promiscuous in their choice of target. Today it is npm, tomorrow PyPI, RubyGems or Docker Hub. A fragmented security model (one tool for JavaScript, another for Python, another for containers) leaves seams. Seams are where gaps form, where integration fails, and where policy is not applied consistently.

Cloudsmith’s multi-format repositories eliminate those seams. Whether the artifact is npm, PyPI, Docker or NuGet, it traverses the same controlled gateway, subject to the same policies and the same intelligence sources, organised in a manner that makes sense to your organisation. Security and distribution are not separate concerns; they are two sides of the same process.

From artifact management to artifact trust

The compromise of ‘is’ demonstrated how quickly risk can propagate when even a trivial dependency is weaponised. Six hours, millions of downloads, and the possibility of global exposure. In that context, treating malware detection as an optional extra bolted onto artifact management is no longer defensible.

Cloudsmith brings intelligence, policy and artifact management together into one fully managed, cloud-native platform, where trust is enforced automatically at the point of entry across every format your teams use. Developers keep building at pace. Security teams know every package is vetted.

Trust is not inherited within the software supply chain. It has to be enforced.

Interested in exploring our advanced security features more for yourself? 

Grab some time with me or another member of our team.

Six Hours Too Late: Why Malware Detection Must Be Built Into Artifact Management

By submitting this form, you agree to our 

 is right around the corner, and there are 11 clear new Python Enhancement Proposals (PEPs) added to the Python project! There are several over significant changes listed within the 

Python 3.14 brings a whole bunch of useful build improvements, including discontinuation of PGP signatures in 

. Python versions 3.14 and onwards will no longer provide PGP signatures for release artifacts. Instead, Sigstore is recommended for verifiers. Similarly, free-threaded mode (

), which was introduced in the previous version, 3.13, has undergone major enhancements. The implementations outlined in this enhancement are now complete, incorporating updates to the C API, and the interpreter’s earlier temporary fixes have been replaced with long-term solutions.

The Cloudsmith team is really excited about this release and everything that comes with it! Note that some of the statuses may change between the time of this blog being posted and the final release date. Knowing that, let’s jump into all of the new features and improvements in Python 3.14.

Here are a few of the changes that Cloudsmith employees are most excited about in this release:

PEP 761: Discontinuation of PGP signatures

“From my perspective at Cloudsmith, the move away from PGP signatures in Python is a welcome change. PGP has long struggled with usability and the burden of managing long-lived private keys, and while it was the default for artifact signing, it never felt ideal. Sigstore offers a much more practical approach, using short-lived keys tied to human-readable identities, and it’s already gaining traction across ecosystems like PyPI, NPM, Homebrew, and GitHub. We’re also seeing projects we work with, like 

, embracing Sigstore, which reinforces that this shift is a real step forward for security and usability.”

PEP 734: Multiple interpreters in the stdlib

“This was an inevitable development, in my opinion. While the CPython runtime has supported running multiple interpreters, which are independent copies of Python within the same process, for well over 20 years at this point, the feature was still limited to the C-API and thus saw little adoption due to low awareness and the absence of a standard library module. With Python 3.14 introducing the new 

 module, this long-standing capability is finally becoming more accessible, marking a significant step toward mainstream usage. While current limitations remain, their impact will diminish as CPython evolves and the community contributes solutions via 

PEP 784: Adding Zstandard to the standard library

“Python 3.14’s addition of Zstandard (via 

) is an exciting upgrade because it brings one of the fastest, most efficient modern compression algorithms directly into the standard library, alongside a new unified 

, consistently outperforms older formats like 

 by offering both higher compression ratios and dramatically faster decompression speeds, which has made it the de facto standard across filesystems, packaging tools, and industry at large.

By including it natively, Python eliminates the confusion of multiple third-party bindings, enables direct support in core modules like 

, and opens the door for faster, smaller Python wheels and other packaging improvements. The reserved 

 namespace not only avoids naming conflicts with PyPI packages but also creates a clean, future-proof home for compression libraries, much like 

 does for hashing. This change reflects Python’s “batteries included” philosophy while giving developers a state-of-the-art compression tool that is both practical today and well-positioned for long-term usage.”

Free-threaded Python is now officially supported

 this enhancement proposal, which actually sets requirements for advancing 

, which was the larger, ongoing effort to make Python’s 

) optional. PEP 703 outlines a three-phase plan:

First phase introduces an experimental GIL-free build in Python 3.13

Phase two makes this build officially supported - though still optional

While Phase 3 makes it the default. 
This new feature defines the expectations for the second phase, ensuring the free-threaded build is stable, usable, and performant enough for broader adoption.

The motivation behind this shift is to balance the benefits of free-threaded Python, which offers greater concurrency, reduced latency, and expanded threading capabilities against costs such as performance penalties, memory overhead, and ecosystem complexity. Current benchmarks show around a 10% slowdown and 15-20% more memory use compared to the traditional GIL build, both considered acceptable trade-offs for Phase 2.

The APIs introduced so far have proven stable, and further refinements are expected without breaking changes. With growing third-party support and clear criteria for performance, memory use, documentation, and API stability, Python 3.14 is targeted as the point where free-threaded Python becomes an officially supported build.

Standard Library Support for Isolated Python Interpreters

Python 3.14 sees the addition of a new standard library module, 

, to expose CPython’s long-standing support for multiple interpreters in a single process. Each interpreter is strictly isolated, with its own modules, classes, and variables, while sharing only certain immutable or low-level process state. Unlike threads, which share most of the same runtime state, interpreters provide stronger isolation, making them better suited for parallelism, especially now that 

The new module will provide a high-level interface for creating, inspecting, and executing code in interpreters, as well as managing communication through a built-in, cross-interpreter-safe 

. This brings powerful functionality, previously limited to the C API, into Python code. An additional 

concurrent.futures.InterpreterPoolExecutor

Cloudsmith Blog

Python 3.14 – What you need to know

Extending Supply Chain Governance to AI and ML Artifacts

Compliance policies in EPM

Npm ecosystem update: a new attack vector emerged with ‘s1ngularity’ and ‘shai-hulud’ attacks

7 Ways Cloud-Native Improves Artifact Management Scalability and Performance

Cloud-native means better customer support, too