Supply Chain

TrustFall: Repository Poisoning RCE in AI Coding Tools

ATLAS OWASP HIGH ▲ 8.5 Dark Reading May 08, 2026

A vulnerability class dubbed 'TrustFall' demonstrates that malicious code repositories can trigger arbitrary code execution in AI-assisted developer tools including Claude Code, Cursor CLI, Gemini CLI, and GitHub Copilot CLI, with little to no user interaction required. The attack surface stems from inadequate or easily dismissed warning dialogs that fail to surface the risk of executing untrusted repository content. Developers cloning or opening adversarial repositories are exposed to full host-level compromise through the elevated trust these AI coding agents place in repository-supplied context.

Claude Code OAuth Token Theft via npm Supply Chain

ATLAS OWASP HIGH ▲ 9.1 SecurityWeek May 08, 2026

Mitiga Labs has disclosed a stealthy attack chain targeting Claude Code's MCP infrastructure, allowing adversaries to silently intercept OAuth tokens by redirecting MCP traffic through attacker-controlled infrastructure. The attack requires only the ability to install a malicious npm package, which modifies ~/.claude.json to insert a proxy and pre-sets trust flags to suppress security prompts. Because the OAuth token grants broad access to all connected SaaS tools, successful exploitation effectively hands attackers a persistent master key to the victim's integrated development environment.

PyTorch Lightning Package Backdoor Steals Developer Credentials

ATLAS OWASP HIGH ▲ 8.5 BleepingComputer May 05, 2026

A malicious version of PyTorch Lightning (v2.6.3) was published to PyPI, embedding a hidden execution chain that silently downloads a JavaScript runtime and executes a heavily obfuscated credential-stealing payload dubbed 'ShaiWorm'. The attack targeted AI/ML developers who use this popular deep learning framework, exposing cloud credentials, API keys, browser-stored secrets, and GitHub tokens. The package has since been reverted to a safe version, but any developer who imported the compromised version should rotate all secrets immediately.

ML Supply Chain Compromise in DoD AI Integration

ATLAS OWASP HIGH ▲ 6.5 SecurityWeek May 04, 2026

The US Department of Defense has formalised agreements with seven major technology companies — including Google, Microsoft, OpenAI, and Amazon Web Services — to integrate AI into classified military networks for battlefield decision support. The move raises significant AI security concerns around human oversight, adversarial manipulation of high-stakes AI systems, and supply chain risks introduced by multiple commercial vendors operating within classified environments. Notably, Anthropic was excluded following a public dispute over AI safety and ethics in warfare.

Loopsy AI Agent Relay Enables Cross-Machine RCE

ATLAS OWASP MEDIUM ▲ 6.5 HN AI Security May 03, 2026

Loopsy is an open-source tool enabling cross-machine communication between AI coding agents (Claude Code, Cursor, Codex) and mobile devices via a self-hosted Cloudflare Workers relay. While designed for legitimate developer productivity, the architecture introduces significant attack surface: a relay brokering shell access and AI agent commands across machines is a high-value target for interception, hijacking, or supply chain compromise. Security teams should assess exposure before deploying such tools in sensitive development environments.

Gemini CLI CVSS 10 RCE via Config Injection in CI/CD

ATLAS OWASP CRITICAL ▲ 9.2 The Hacker News May 01, 2026

Google has patched a maximum-severity (CVSS 10.0) vulnerability in its Gemini CLI tooling that allowed unauthenticated attackers to achieve remote code execution by planting malicious configuration files in workspace directories automatically trusted by the agent in headless/CI mode. The flaw effectively weaponised CI/CD pipelines as supply chain attack paths, bypassing sandbox protections entirely before they could initialise. A secondary issue in '--yolo' mode further enabled prompt injection to trigger unrestricted shell command execution.

Famous Chollima Poisons npm With LLM-Assisted Malware

ATLAS OWASP HIGH ▲ 8.5 The Hacker News Apr 30, 2026

North Korean threat group Famous Chollima (Shifty Corsair) has weaponised AI-assisted code generation to embed malicious npm packages into autonomous AI agent projects, targeting cryptocurrency wallets. The campaign, dubbed PromptMink, exploited Anthropic's Claude Opus to co-author a malicious dependency commit, demonstrating a novel abuse of LLM coding agents for supply chain infiltration. The attack uses a multi-layer dependency structure to evade detection, with second-layer malicious packages swiftly rotated when identified.

CVE-2026-42208: LiteLLM SQL Injection Exposes API Keys

ATLAS OWASP CRITICAL ▲ 9.2 The Hacker News Apr 30, 2026

A critical SQL injection vulnerability (CVE-2026-42208, CVSS 9.3) in BerriAI's LiteLLM AI gateway was actively exploited within 36 hours of public disclosure, targeting database tables storing upstream LLM provider API keys including OpenAI, Anthropic, and AWS Bedrock credentials. Attackers demonstrated prior knowledge of LiteLLM's internal schema, selectively probing credential and configuration tables while ignoring user and team tables. The blast radius extends far beyond a typical web-app SQL injection, as successful extraction equates to cloud-account-level compromise across multiple AI provider accounts.

CVE-2026-42208: LiteLLM SQL Injection Stealing AI Credentials

ATLAS OWASP CRITICAL ▲ 9.2 BleepingComputer Apr 29, 2026

A critical unauthenticated SQL injection vulnerability (CVE-2026-42208) in LiteLLM, a widely-used LLM proxy and SDK middleware, is being actively exploited to extract API keys, provider credentials, and configuration secrets from the proxy database. Exploitation began within 36 hours of public disclosure, with attackers demonstrating precise targeting of sensitive tables containing OpenAI, Anthropic, and Bedrock credentials. The stolen credentials could enable downstream attacks against AI infrastructure at scale, given LiteLLM's broad adoption across LLM application ecosystems.

TeamPCP Supply Chain Campaign Poisons xinference PyPI

ATLAS OWASP HIGH ▲ 6.5 SANS Internet Storm Center Apr 28, 2026

The TeamPCP supply chain campaign resumed after a 26-day pause with three concurrent compromises targeting Checkmarx KICS (Docker Hub), xinference (a popular AI inference PyPI package), and a cascading compromise of Bitwarden CLI via poisoned CI/CD dependencies. The xinference poisoning is directly AI-security relevant as it targets a widely used LLM/ML model serving framework, while the broader campaign demonstrates sophisticated supply chain attack methodologies that increasingly intersect with AI tooling. The CanisterSprawl npm worm adds credential-harvesting infrastructure that could further compromise AI development pipelines.

Supply Chain Risk: Gradio MCP Server Exposes AI Agents

ATLAS OWASP MEDIUM ▲ 6.2 Hugging Face Blog Apr 27, 2026

Hugging Face's Gradio MCP server integration enables LLMs to connect to thousands of third-party AI tools via Hugging Face Spaces, significantly expanding the attack surface for agentic AI systems. This architecture introduces supply chain risks, excessive agency concerns, and potential for malicious tool servers to manipulate LLM behaviour through crafted outputs. While presented as a productivity feature, the open, community-driven nature of the 'MCP App Store' raises serious vetting and trust boundary concerns.

Anthropic Mythos Preview Breached via Contractor Credentials

ATLAS OWASP HIGH ▲ 8.2 Wired Security Apr 26, 2026

A group of Discord users gained unauthorized access to Anthropic's restricted Mythos Preview AI model by combining data from a third-party breach, educated guessing about model endpoint URLs, and leveraging existing contractor permissions. The incident exposes systemic weaknesses in how access controls for powerful, restricted AI models are enforced across contractor and supply chain boundaries. This is particularly significant given Mythos's described capability as an advanced vulnerability-discovery tool, raising the stakes if malicious actors replicate the access method.

Stash AI Memory Poisoning Exposes Agent Data Leakage

ATLAS OWASP MEDIUM ▲ 6.5 HN AI Security Apr 26, 2026

Stash is an open-source persistent memory layer for AI agents using PostgreSQL and pgvector, exposing a broad MCP tool surface (28 tools) that introduces significant attack vectors including memory poisoning, sensitive data leakage, and cross-namespace contamination. While marketed as a productivity enhancement, the architecture centralises long-term agent memory in a shared backend, creating a high-value target for adversarial manipulation. Security teams deploying autonomous agents should treat persistent memory stores as critical infrastructure requiring strict access controls and integrity validation.

OpenAI Codex CLI Credentials Hijacked via Malicious Package

ATLAS OWASP MEDIUM ▲ 6.5 Simon Willison Apr 25, 2026

A new Python package, llm-openai-via-codex 0.1a0, explicitly 'hijacks' Codex CLI credentials to route API calls through an unofficial OpenAI endpoint, bypassing standard API billing and access controls. This represents a credential misuse pattern that could expose organisations to unauthorised API access and quota theft. The technique exploits an undocumented or semi-official API surface, raising supply chain and access control concerns for enterprise OpenAI deployments.

CVE-2026-33626: LMDeploy SSRF Exploited in 13 Hours

ATLAS OWASP CRITICAL ▲ 9.2 The Hacker News Apr 25, 2026

A critical SSRF vulnerability in LMDeploy (CVE-2026-33626), an open-source LLM deployment toolkit, was actively exploited within 13 hours of public disclosure, with attackers using the vision-language image loader to probe cloud metadata services, internal networks, and exfiltrate data. The attack pattern demonstrates that AI inference infrastructure is being weaponised at speed comparable to traditional CVE exploitation cycles, with no PoC required. This incident reinforces a broader trend of threat actors treating LLM-serving infrastructure as high-value lateral movement targets.

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