First reported · updated · 2 reports huggingface.co
Lead dispatch
First reported · updated · 3 reports embracethered.com
AWS Kiro: Arbitrary Code Execution via Indirect Prompt Injection
Researchers found a vulnerability (CVE-2026-10591) in AWS Kiro, an agentic IDE, where hidden instructions planted in a web page or source file that Kiro processes can trigger indirect prompt injection to rewrite Kiro's own MCP server configuration (~/.kiro/settings/mcp.json) or allowlist arbitrary Bash commands in .vscode/settings.json, achieving arbitrary code execution on the developer's machine with no approval prompt. The human-in-the-loop approval boundary is bypassed because Kiro can write to these config files without user consent, and AWS has issued a fix and CVE.indirect-prompt-injection · prompt-injection · remote-code-execution · tool-abuse · config-poisoning
ai-agents · mcp · llm · agentic-ide
Severity
0.85
The wire · latest
First reported · updated · 2 reports screetsec.com
Maland | Another Cursor 0-day Enabling Arbitrary Code Execution Beyond Git.exe
Cursor 3.0.0 patches CVE-2026-48124, a class of sandbox-to-host code execution weaknesses affecting AI coding agents including Cursor, OpenAI Codex CLI, Google Gemini CLI, and Antigravity, where files written by a sandboxed agent are later consumed and executed by trusted host tooling (extensions, task runners, Git integrations, Docker). Related research by Mindgard and others details a Windows binary-planting flaw where opening a repository auto-executes a malicious git.exe planted at the repo root, yielding zero-click arbitrary code execution with no prompt injection or model in the loop. Details →First reported medium.com
AutoJack: The New Vulnerability Class Letting a Single Webpage Hijack Your AI Agent | by Raj Namdev | CodeToDeploy
A Medium write-up describes AutoJack, a named vulnerability class in which a single malicious webpage embeds content that hijacks an AI browsing agent's reasoning during a normal task (summarizing, price-checking, form-filling) and redirects it to execute the attacker's instructions with no user click, download, or approval. The piece frames it as a recently demonstrated form of indirect prompt injection against AI browsing agents. Details →First reported · updated · 2 reports nhimg.org
Who is accountable when an AI agent triggers code execution through a trusted tool?
An NHIMG editorial FAQ argues that accountability for an AI agent triggering code execution through a trusted tool sits with the teams that defined the tool's trust boundary, approval model, and runtime policy, not just whoever deployed it. It frames agentic risk as a governance and identity problem, offering a checklist for evaluating execution paths (identity presented, static vs context-aware access, credential lifetime, file/process write capability, and approval scope) and references OWASP Agentic Top 10, NIST AI RMF, and the CSA MAESTRO framework. Details →First reported huggingface.co
Generative AI for Cybersecurity: A Practical Guide (2026)
Hugging Face disclosed a July 2026 intrusion into its production infrastructure that it describes as driven end-to-end by an autonomous AI agent framework. A malicious dataset abused two code-execution paths in dataset processing (a remote-code dataset loader and a template-injection in a dataset configuration) to run code on a processing worker, then escalated to node-level access, harvested cloud and cluster credentials, and moved laterally across internal clusters using thousands of actions from short-lived sandboxes with self-migrating C2. Hugging Face says it closed the code-execution paths, rebuilt compromised nodes, and rotated credentials. (Note: the layer3labs aggregator adds sensational, unverified claims not supported by Hugging Face's own disclosure.) Details →First reported datadoghq.com
Before the first prompt: Code execution paths in trusted coding-agent projects | Datadog Security Labs
Datadog Security Labs demonstrates that trusting a repository in coding agents such as OpenAI Codex and Claude Code can trigger repository-controlled code execution before the first prompt, without a model response or shell-command approval. In Codex, project-scoped MCP configurations start an attacker-controlled process, and in Claude Code a project-controlled PATH causes Claude's automatic Git probes to run a tracked repository wrapper — bypassing hook-approval controls. Details →First reported · updated · 2 reports pillar.security
The Week of Sandbox Escapes
Pillar Security researchers (Eilon Cohen, Dan Lisichkin, Ariel Fogel) published 'The Week of Sandbox Escapes,' demonstrating seven ways to break out of the sandboxes in four AI coding agents — Cursor, OpenAI's Codex, Google's Gemini CLI and Antigravity — without attacking the sandbox directly. A prompt injection planted in a README, issue, dependency, or diff drives the sandboxed agent to write workspace files (e.g. a .claude hook config, a virtualenv interpreter, or Git fsmonitor metadata) that trusted tools running outside the sandbox later execute, achieving host command execution; one Cursor issue is tracked as CVE-2026-48124 and fixed in v3.0.0. Details →First reported · updated · 3 reports huggingface.co
OpenAI, Google, and Anthropic absent from Nvidia-led Open Secure AI Alliance — 30+ companies join security alliance after OpenAI agent breach | Tom's Hardware
Hugging Face disclosed a July 2026 intrusion into its production infrastructure that was driven end-to-end by an autonomous AI agent framework: a malicious dataset abused two code-execution paths (a remote-code dataset loader and a template-injection in a dataset configuration) to run code on a processing worker, then escalated to node-level access, harvested cloud/cluster credentials, and moved laterally across internal clusters using thousands of automated actions and self-migrating C2 on public services. The incident, reported alongside a related OpenAI agent breach, prompted Nvidia to form the 30+ member Open Secure AI Alliance, notably without OpenAI, Google, or Anthropic. Details →First reported · updated · 2 reports canopii.dev
State of MCP Security 2026 v2
Canopii's "State of MCP Security 2026" report scanned more than 11,000 published Model Context Protocol servers and found 830 graded D or F, 232 with confirmed dangerous code sinks (eval, shell injection, unsafe deserialization) that can turn prompt injection into host code execution, 184 versions that silently altered tool definitions after publication ("rug pulls"), 1,617 servers shipping dependencies with known vulnerabilities, 260 running install-time scripts, and 7 confirmed typosquats. Popular servers with 1,000+ GitHub stars were over 5x more likely to be high-risk. Details →First reported wiz.io
Amazon Q VS Extension Flaw Leads to Cloud Credential Theft
A vulnerability in the Amazon Q Visual Studio extension could let adversaries plant a malicious repository that executes arbitrary code and steals cloud credentials, highlighting growing MCP-related risk. Details →How the wire is made
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