LiteLLM version 1.107.0 was compromised and distributed via PyPI and official container images on October 21, 2026. The malicious package used Python startup hooks to automatically execute credential-stealing payloads without requiring explicit import of LiteLLM. Attackers stole developer GitHub credentials to redirect release workflows to a fake repository. The payload targeted authentication credentials across developer tools, AI applications, cloud environments, browsers, and infrastructure. Credentials were encrypted and exfiltrated to attacker-controlled servers. The compromise affected developer workstations, CI/CD agents, test systems, containers, and LiteLLM gateway deployments where Python was executed.
On October 21, 2026, the LiteLLM Python proxy library version 1.107.0 was compromised in a supply chain attack. The malicious release was available on PyPI and official Docker images for approximately two hours. Attackers used stolen GitHub CLI OAuth tokens from three engineers to deploy a malicious fork via a private release workflow. The payload included a credential stealer targeting cloud, developer, AI-tool, browser, and LiteLLM proxy credentials, as well as a second-stage remote access trojan backdoor. The malware executes automatically whenever Python starts by placing files in the site-packages directory. This is the second known supply chain compromise of LiteLLM in 2026, unrelated to the previous incident linked to TeamPCP activity.
LiteLLM version 1.107.0 was compromised in a supply chain attack affecting PyPI packages and Docker images. The malicious release includes Python startup files that execute automatically, stealing cloud credentials, private keys, browser data, and AI development tool authentication tokens. The attack used a lookalike repository in the release workflow and targets credentials for AWS, Azure, Google Cloud, GitHub CLI, SSH keys, npm/PyPI, and AI tools such as Claude, Gemini, and Cursor. Stolen data is encrypted and sent to a command-and-control server. A loader enables remote Python code execution. The package has approximately 23 million weekly downloads, indicating a significant potential impact.
A supply chain poisoning attack on LiteLLM, a popular AI model gateway, was detected by NSFOCUS Technology CERT. The TeamPCP group compromised the Trivy security scanning tool used in LiteLLM's release process, allowing them to publish malicious versions 1.82.7 and 1.82.8 on PyPI. These versions contained credential-stealing programs that collected sensitive data and, if a Kubernetes cluster was detected, deployed privileged Pods and implanted persistent backdoors. The attack impacted numerous dependent packages and potentially affected millions of users. The incident highlights the growing risks in AI infrastructure and the need for robust supply chain security measures.
TeamPCP has launched a supply chain attack targeting LiteLLM, an open-source Python library used in 36% of cloud environments. Malicious versions 1.82.7 and 1.82.8 were published on PyPI, employing sophisticated techniques for payload delivery and persistence. The compromised packages exploit Python's .pth mechanism for stealthy execution across any Python process. The malware collects sensitive data including API keys, cloud credentials, and CI/CD secrets, encrypting and exfiltrating them to attacker-controlled domains. This attack follows TeamPCP's previous compromises of Aqua Security's Trivy and Checkmarx tools, highlighting an ongoing campaign against the open-source ecosystem. The incident underscores the potential for widespread impact and the need for vigilance in software supply chain security.
A malicious supply chain attack has been discovered in the Python Package Index package litellm version 1.82.8. The compromised package contains a malicious .pth file that executes automatically when the Python interpreter starts, without requiring explicit import. This file, located in site-packages/, exfiltrates sensitive information including environment variables, SSH keys, and cloud credentials to an attacker-controlled server. The payload is double base64-encoded to evade basic static analysis. PyPI administrators have quarantined the project to limit its spread. Users are advised to check for the malicious file, rotate all potentially exposed credentials, and audit their PyPI publishing process. The attack is attributed to TeamPCP and is actively exploited in the wild.
