How to Audit All Python Virtual Environments for Compromised Packages Without Executing Python
The growing number of supply-chain attacks targeting popular packages has prompted developers to seek reliable ways to audit their Python installations. Recent incidents affected the npm package Axios, the vulnerability scanner Trivy, and the Python package LiteLLM. In response, one developer created a system to locate every virtual environment on a machine and inspect its installed packages without ever executing Python code.
Virtual environments isolate project dependencies by storing symbolic links to the Python interpreter and site-packages inside a dedicated directory, conventionally named .venv. Because Python itself does not track created environments, the author maintains a personal registry file at ~/.venv_registry that is updated both by periodic find commands and by a shell function that records every newly created environment.
The registry enables a simple Bash script that reads each path, verifies the directory still exists, and then calls uv pip freeze --python against the environment’s interpreter. Because uv is written in Rust, it parses installation metadata without running any Python code—an important safeguard after the LiteLLM compromise demonstrated that even innocuous commands such as python --version could execute attacker-controlled .pth files.
The same registry supports additional security and maintenance tasks. It can be used to identify outdated package versions across all projects, locate remaining usages of libraries the developer wishes to retire, and search project source trees for calls to specific functions without scanning the entire disk.
Global installations outside virtual environments are prevented by setting PIP_REQUIRE_VIRTUALENV=true and by relying on uv, which refuses to modify the system Python unless the --system flag is explicitly supplied. The resulting workflow therefore provides both rapid detection of known malicious packages and ongoing hygiene for a large collection of Python projects on macOS.
Related articles
Passwordless Kubernetes Image Pulling with Artifact Keeper via ServiceAccount Tokens
Kubernetes 1.34 and later enables kubelet to forward a pod's ServiceAccount token to an external image credential provider plugin, allowing the plugin to exchange it for short-lived read-only credentials from a compatible registry. Artifact Keeper, an open-source Rust-based OCI and package registry, implements an OIDC provider that validates these tokens and issues temporary credentials without requiring imagePullSecrets in manifests. The approach follows zero-trust principles by eliminating long-lived secrets that can leak across namespaces or clusters. A custom credential provider binary handles the token exchange, enforces audience restrictions, and redacts sensitive data from logs. The solution requires specific ClusterRole permissions for nodes, kubelet flags, and registry-side OIDC mappings that bind Kubernetes namespaces to read-only groups. Testing on kind 1.34.3 confirmed successful pulls for authorized ServiceAccounts and clear 401 errors for unauthorized ones when imagePullPolicy is set to Always.
Malicious Code Injected into LiteLLM Open Source AI Package via Supply Chain Attack
The open-source generative AI tool LiteLLM had malicious code inserted into its official distribution packages, enabling credential theft and remote code execution. The compromise affected version 1.107.0 released on October 21, 2026, and was delivered through legitimate channels in a classic software supply chain attack. Seven malicious wheel files were uploaded to PyPI, while official container images on Docker Hub and GitHub Container Registry were also tainted. Security firm JFrog discovered that the malware steals a wide range of secrets including cloud credentials, SSH private keys, browser-stored passwords, development tokens, and AI service API keys from LiteLLM's database. The code also supports execution of externally fetched payloads and abuses Python's startup mechanisms to run even when the application itself is not loaded. This marks the second supply chain incident involving the project in 2026, following a separate event in March.
GhostAction Campaign Compromises 790 GitHub Repositories via Malicious Workflows
Researchers from OpenSourceMalware have identified 790 publicly accessible GitHub repositories containing malicious workflows planted by the GhostAction campaign as of October 9. The campaign abuses trusted maintainer accounts to inject workflows that automatically exfiltrate secrets including AWS access keys and tokens for GitHub, GitLab, Google, Slack, SendGrid, OpenAI, Anthropic, and OpenRouter. Earlier counts by GitGuardian recorded 772 repositories between August 31 and September 30, though the datasets differ and are not cumulative. A separate wave on October 8 impacted 346 repositories linked to two maintainer accounts, including a project belonging to Uber. The malicious workflow runs on code pushes or manual triggers, scans repository files and full Git history for credentials, and sends findings in plaintext to attacker infrastructure. Removing the workflow file does not mitigate exposure, as successful executions already leak credentials and old commits may still contain secrets.
SberTech Launches Platform V Orchestrator for Security Services to Scan Software Before Corporate Deployment
SberTech has announced the launch of a new direction focused on analyzing the security of software prior to its integration into corporate infrastructures. The initiative is built around the company's own Laboratory for Software Verification and the technological platform Platform V Orchestrator for Security Services. This platform combines components for working with both built-in and external analysis tools, enabling checks of digital artifacts, control over software composition and changes, and detection of vulnerabilities, hidden threats, and defects in source code and repositories. SberTech aims to replace fragmented checks and manual result processing with a single managed process, allowing scaled verification without proportional team growth. The move responds to the adoption of hundreds of products from various vendors, widespread use of open-source components, and rising attacks on software supply chains. Primary customers include banks, industrial enterprises, telecom operators, energy companies, and the public sector. The solution is offered as a standalone product that supports on-premises deployment and operation in isolated environments such as private clouds and dedicated data processing contours.