Threats Tagged 'docker'

Bulletin ID: 2026-050-AWS Scope: AWS Content Type: Important (requires attention) Publication Date: 07/01/2026 12:15 PM PDT Description: AWS CDK (aws-cdk-lib) is an open-source framework for defining cloud infrastructure in code and provisioning it through AWS CloudFormation. We identified CVE-2026-13760, an OS command injection issue in the NodejsFunction Docker bundling pipeline in aws-cdk-lib before 2.260.0 that could allow an actor who controls dependency version strings in a project's package.json file to execute arbitrary commands on the host running the CDK toolchain via injected shell metacharacters in the OsCommand helper. This issue requires the actor to control the content of a package.json dependency version string that is processed during Docker-based bundling with nodeModules specified. Impacted versions: < 2.260.0 Please refer to the article below for the most up-to-date and complete information related to this AWS Security Bulletin.

CVE-2026-107608 is a vulnerability in aws-cdk-lib where the asset bundling process using Docker files could improperly include symlinked files or directories in the output without those symlinks being part of the input. This affects all versions prior to 2.267.0. The issue arises when bundling assets with Docker files, potentially causing unexpected files to be included in the deployment package.

This report summarizes multiple cybersecurity incidents and emerging threats including the takeover of the Clop ransomware gang's leak site by the ShinyHunters group, the BragJack vulnerability that allows malicious browser extensions to hijack AI assistants, a new Go implant malware targeting AI agent tooling, and a Docker botnet that steals AI API keys. Additionally, it covers exposed remote access credentials in the US water utility sector, a novel Windows implant using commercial AI models for command decisions, and a high-severity pre-authentication denial-of-service vulnerability in TDengine industrial telemetry software. The report also notes Canonical's changes to Ubuntu kernel update cycles to accelerate patching and the discovery of a new Android banking trojan with AI-assisted development. These events highlight evolving attack methods leveraging AI and targeting critical infrastructure and cloud-native environments.

A new botnet malware called Carbonato is targeting insecure hosts running Docker daemons to install the Hermes Agent AI framework and take control. [...]

ThreatDown researchers discovered CARBONATO, a Docker botnet that exploits exposed Docker daemons on port 2375. The operation was uncovered through an unauthenticated Docker registry exposed since May 2026, revealing two parallel activities: distribution of trojanized cryptocurrency wallet applications and a botnet infrastructure. The botnet leverages Hermes Agent, an MIT-licensed open-source AI framework, modified with a custom prompt directing it to execute commands via Telegram, maintain persistence, and harvest credentials. The campaign infrastructure spans multiple hosting providers including Linode, Hetzner, and Contabo, with activity documented from October 2024 through August 2026.

In this article AI workloads are becoming high-value control points Case study 1: LiteLLM gateway compromise Case study 2: RAGFlow compromise Case study 3: Kestra compromise Mitigation and protection guidance MITRE ATT&CK techniques observed References Learn more AI is creating a new layer of enterprise infrastructure. Gateways, retrieval platforms, orchestration services, and containerized runtimes now sit between users, applications, data, and models. These systems concentrate credentials, data access, model connectivity, and execution privileges, making them some of the most powerful components in the AI stack. That concentration of trust is also creating new opportunities for attackers. In recent investigations, Microsoft observed activity targeting three distinct AI workloads: a LiteLLM gateway, a RAGFlow deployment, and a Kestra workflow environment. The intrusion paths varied, but the objectives were strikingly similar. Attackers sought to steal credentials, establish persistence, and monetize compromised compute resources. The individual techniques matter, but the broader pattern matters more. Across these cases, attackers treated AI infrastructure as a control plane where credential theft, host compromise, and downstream data access can converge. As organizations continue to deploy AI systems, these platforms are becoming high value targets that deserve the same security scrutiny as other critical enterprise infrastructure. AI workloads are becoming high-value control points The campaign-level signal extends beyond one product. The targeted workloads served different functions, but each exposed assets that could support follow-on abuse, including model-provider keys, proxy-issued virtual keys, database connection strings, tenant configuration, workflow execution, or host compute. Post-compromise behavior varied by workload role. Defenders should inventory exposed AI management surfaces, restrict administrative access, and monitor for gateway-originated execution and secret access. Three observed compromises across AI workloads AI workload Observed activity Attacker objective LiteLLM Observed attacker activity : Python droppers, runtime secret harvesting, PostgreSQL collection, miner deployment, and persistence activity from the LiteLLM gateway context. Microsoft assessment: Initial access likely occurred through exploitation of the exposed LiteLLM gateway surface, consistent with the vulnerability chain involving CVE-2026-42271 and CVE-2026-48710. Credential theft, backend database access, durable host access, and compute monetization. RAGFlow Observed attacker activity : Possible SSRF-style reconnaissance followed several days later by code execution, application-path modification, and placement of a Python hook in the TenantLLM credential-configuration flow. Public research: Describes multiple RAGFlow execution paths; Microsoft does not attribute this intrusion to a specific vulnerability. Intercept newly configured LLM provider credentials and model metadata. Kestra Observed attacker activity : Workflow-origin shell execution, Docker and container-environment discovery, XMRig deployment, and follow-on data collection. Microsoft assessment: Initial access likely involved exploitation of the exposed Kestra orchestration surface, with CVE-2026-49869 providing relevant public vulnerability context. Secret discovery, container-level access, data collection, and rapid compute monetization. Case study 1: LiteLLM gateway compromise Framework role and affected runtime context LiteLLM is commonly deployed as a proxy or gateway between applications and model providers. In that position, the service may hold or retrieve model-provider keys, LiteLLM master keys, virtual-key records, database connection strings, routing configuration, and tenant policy data. Command execution in the gateway runtime therefore exposed a process context close to AI routing and credential material. Figure 1. LiteLLM gateway compromise – attack chain…

OPeNDAP Hyrax contains a Server Side Request Forgery (SSRF) vulnerability that allows attackers to bypass allowed hosts restrictions via unvalidated HTTP redirects. This can cause the application to communicate with unauthorized internal or external systems. Additionally, user authentication headers, including a legacy Echo-Token credential, may be leaked to attacker-controlled endpoints during these redirects. Exploitation could enable unauthenticated attackers to access internal services and disclose credentials of authenticated users. A fix addressing these issues was released in Hyrax version 1.18.0. Until patched, administrators are advised to restrict gateway exposure to trusted networks.

Deployment of the VPS.org one-click Supabase template deploys a PostgreSQL instance that is published on all interfaces (0.0.0.0:5432) with a default database password set to "postgres". Because Docker installs its own iptables rules, this exposure bypasses a standard host UFW configuration.

This vulnerability allows local attackers to escape the model runner sandbox on affected installations of Docker Desktop for macOS. An attacker must first obtain the ability to execute low-privileged code within the sandbox in order to exploit this vulnerability. The ZDI has assigned a CVSS rating of 8.8.

This article provides a detailed technical analysis of the critical CVE-2026-20896 vulnerability in Gitea Docker images, which allows unauthenticated attackers to bypass authentication via a misconfigured reverse proxy trust setting. It includes actionable remediation steps such as immediate patching to version 1.26.4 or applying configuration fixes to restrict trusted proxies, helping defenders mitigate active exploitation risks.