Malicious npm packages, pypi malicious packages, and other forms of malicious code continue to infiltrate open-source ecosystems. The Malicious Code Digest is Xygeni’s weekly malware report that tracks and verifies new threats in the software supply chain, including confirmed backdoors, trojans, and spyware spreading through registries like npm and PyPI.
Our research team updates this page weekly with the latest indicators of compromise (IOCs), technical breakdowns, and real-world exploit patterns. Developers, AppSec leads, and security engineers can use this digest to stay ahead of npm malware and pypi malware campaigns targeting CI/CD environments.
Weekly Summary: Novemeber 15 – 21, 2025
In the last few days, researchers confirmed 49 new malicious npm packages, with no activity detected in PyPI or other ecosystems.
Key findings
Finance- and banking-themed clusters
A noticeable wave of packages used financial or fintech-like names, including superbankbackdoor, xmljs2bank, beijingcrisis, pavelpopover, netflixpad, and debiancgs, suggesting attempts to mimic internal banking modules or lure developers working in financial environments.
Parser-based malware variants
Two different parser-themed lines appeared:
- xmljs2bank (0.30.2)
- Multiple gibertserctf* variants
- globby-legacy and flaresdsdsdsdsd
These follow patterns seen in previous XML/JS parser impersonations where attackers reuse and mutate small payload templates.
High-volume multi-version republishing
Several families showed automated republishing behavior, including:
- @acitons/artifact (two versions: 4.0.13, 4.0.14)
- superbankbackdoor (1.0.0 and 0.30.1)
- megaexploitvorkemol* (four sequential variants)
- focusync-custom-controls (versions 99.0.0 and 100.0.0)
These waves indicate scripted pushes meant to evade heuristics or artificially inflate version trust.
Exploit-themed malware families
A coordinated cluster used exploit-style naming, including:
supermoy1, supervot5, finalmoyloyt, megadepsexploit, and the megaexploitvorkemol series.
These appear to be related through identical versioning (0.30.1) and publishing timestamps.
Brand or corporate impersonation
Attackers continued abusing internal-sounding or enterprise-like names such as:
adyen-web-v5, payouts-report, startupkit-umbraco-webpack,
@secretcollect/identity-core, kiatu-bolivia, and worldskills,
attempting to blend into private registries or internal CI toolchains.
Clear signs of automated malicious pipelines
Multiple packages shared identical metadata patterns, timestamps, or sequencing:
- study-lab-npm-test, study-lab-e53
- superbankbackdoor series
- focusync-custom-controls (99.x → 100.x)
- worldskills
These strongly suggest automated script-driven publication pipelines.
No cross-ecosystem attacks this week
All confirmed malicious packages were exclusively in npm, with no PyPI or Maven overlap, unlike prior weeks where attackers tested parallel registry deployments.
View the full weekly malware report →
Monthly Malware Report: Confirmed Malicious npm Packages in October 2025
In October 2025, Xygeni analyzed and reported over 280 malicious packages across npm and PyPI. This monthly report includes all confirmed malicious npm packages and pypi malicious packages for the month, including those discovered in the last week.
| Ecosystem | Package | Date |
|---|---|---|
| npm | @adobe/helix-rum-js:2.13.6 | Oct 21, 2025 |
| npm | @agent-velo/era:0.1.0 | Oct 21, 2025 |
| npm | @ledgerhq/live-common:34.52.0-nightly.0 | Oct 21, 2025 |
| npm | @shopify.com/shopifyql-parser:3.999.9 | Oct 20, 2025 |
| npm | ai-protocol:3.0.0 | Oct 20, 2025 |
| npm | cpilot-coding-assistant:1.0.7 | Oct 21, 2025 |
| npm | iwf-ant-design-draggable-modal:1.1.15 | Oct 24, 2025 |
| npm | mediapipe:1.3.5 | Oct 23, 2025 |
| npm | porscheofficial:2.9.9 | Oct 24, 2025 |
| pypi | pdfdancer-client-python:0.2.11 | Oct 22, 2025 |
How We Detect Malicious Code in npm Malware and PyPI Malware
Xygeni uses multi-layered techniques to stop malicious code before it spreads. First of all, static code analysis detects obfuscation patterns, hidden payloads, and script abuse. In addition, behavioral sandboxing analyzes install hooks, runtime commands, and persistence tricks. Moreover, machine learning detection identifies zero-day npm malware and pypi malware variants missed by signature scanners. Finally, the Early Warning System monitors public repositories in real time, validates findings, and alerts DevOps teams immediately.
As a result, this combination ensures developers receive fast, actionable intelligence integrated directly into CI/CD workflows.
Why Developers Should Care About Malicious npm Packages
Modern threats rarely wait for runtime. For example, malicious npm packages often execute during installation, while pypi malicious packages hide token exfiltration or backdoors. Attackers:
- Flip private GitHub repos to public to replicate them.
- Exfiltrate credentials and secrets using encoded payloads.
- Use obfuscated JavaScript loaders to deploy ransomware or botnets.
In fact, malicious open-source packages surged 156% in one year. Therefore, teams that rely only on delayed feeds or basic scanners fall behind.
What This Malware Report Tracks in npm and PyPI
This digest is the central hub for:
- Confirmed malicious npm packages
- Confirmed pypi malicious packages
- Behavior-based detections of malicious code
- Registry-confirmed incidents
- Weekly and monthly malware report summaries
- Historical changelog of all npm malware and pypi malware findings
In other words, it provides a single point of reference. The research team at Xygeni updates this page weekly with links to full technical analyses and GitHub IOCs.
How to Protect Against Malicious npm Packages and PyPI Malware
Because of this growing risk, organizations need more than basic dependency checks. Strong defenses against malicious npm packages and pypi malicious packages require both preventive controls and runtime enforcement:
Enforce Lockfile-Only Installs Against Malicious npm Packages
Use npm ci or pip install --require-hashes in CI/CD.
This ensures the exact dependency tree defined in lockfiles is used. As a result, attackers cannot slip in modified or typosquatted versions of malicious npm packages.
Pre-Install Scanning for npm Malware and PyPI Malware
Integrate Xygeni’s Early Warning Engine to scan npm malware and pypi malware before packages reach your environment.
Moreover, detect suspicious postinstall scripts, obfuscated loaders, or hardcoded C2 URLs.
Guardrails to Block Builds with Malicious Code
Set guardrails to fail builds automatically if confirmed malicious npm packages or pypi malicious packages are detected.
For example, break builds on packages with unpublished maintainers, obfuscation patterns, or IOC matches. Consequently, malicious code never passes unnoticed.
Generate and Validate SBOMs Against Malicious npm Packages and PyPI Malware
Create SBOMs (CycloneDX, SPDX) for every build.
Afterward, compare against known malicious npm packages and pypi malware feeds to track both direct and transitive dependencies.
Credential and Token Protection from npm Malware and PyPI Malware
Many malicious npm packages try to read .npmrc, .pypirc, or environment variables.
Therefore, run builds in hardened containers with minimal secrets exposed. Additionally, use secrets managers instead of environment variables to block malicious code abuse.
Monitor Registry and Maintainer Changes in Malicious npm Packages
Attackers often hijack abandoned projects.
In particular, watch for sudden maintainer swaps, unusual versioning jumps, or excessive publishes in npm malware and pypi malicious packages.
Developer Training on Detecting Malicious Code in npm and PyPI
Teach teams to spot red flags such as:
- Package names with typos (
reqeustinstead ofrequest). - Unusual
installorpreparescripts. - Recently created packages with suspiciously high version numbers.
Above all, this awareness helps detect malicious code early.
Runtime Anomaly Detection for Malicious npm Packages and PyPI Malware
Even if malware bypasses static checks, runtime detection in CI/CD can catch:
- Unexpected network connections.
- File system modifications outside expected directories.
- Persistence attempts across jobs.
Finally, this ensures npm malware and pypi malware threats are stopped even after installation.
By combining these controls, teams prevent malicious npm packages and pypi malicious packages from ever reaching production pipelines.
Try Xygeni’s Malware Detection Tools
Xygeni delivers:
- Real-time detection of malicious code, including backdoors, spyware, and ransomware.
- In contrast to basic scanners, analysis across npm, PyPI, Maven, NuGet, RubyGems, and more.
- Automatic build blocking when the malware report identifies risk.
- Exploitability insights, maintainer reputation checks, and anomaly detection.
Stay Informed
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