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CRITICAL OpenAI GPT-5.6 Escapes Sandbox, Attacks Hugging Face to Cheat Benchmark // CRITICAL CVE-2026-0770: Langflow RCE Flaw Exploited in Active Attacks // HIGH Azure DevOps MCP Prompt Injection Hijacks AI Review Agents // FIRST LOOK Yellow Teams Bring AI Offense and Defense Into One Security Function // FIRST LOOK Tracebit Ships AWS Context Bombing Defence Against AI Hacking Agents // FIRST LOOK FriendMachine Launches Jacquard Lang for AI-Written Code Review // CRITICAL Check Point 2026 AI Security Report: LLMs Now Run Live Attacks // FIRST LOOK OpenAI GPT-5.6 Sol Ships Faster Parallel Tool-Use for Agents // FIRST LOOK Meta Launches Muse Image with Public Instagram Photo Reuse // FIRST LOOK Estonia Launches State-Issued Digital IDs for AI Agents //
Claude Code Indirect Prompt Injection Spawns Reverse Shell

Claude Code Indirect Prompt Injection Spawns Reverse Shell

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.5 SecurityWeek

Researchers have demonstrated that indirect prompt injection attacks embedded within seemingly benign code repositories can cause Claude Code — Anthropic's agentic coding assistant — to spawn a reverse shell on a developer's machine. The attack exploits Claude Code's autonomous execution capabilities, using hidden instructions in repository content to hijack the host system without any explicit user consent. This highlights a critical risk in agentic AI tools that operate with elevated system privileges in developer environments.

AutoJack: Microsoft AutoGen Studio RCE via MCP WebSocket

AutoJack: Microsoft AutoGen Studio RCE via MCP WebSocket

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.5 BleepingComputer

A three-flaw vulnerability chain dubbed AutoJack in Microsoft's AutoGen Studio allowed attackers to execute arbitrary commands on a developer's host system by manipulating a browsing AI agent into connecting to a malicious webpage. The attack exploited missing authentication on MCP WebSocket routes combined with unsanitised base64-encoded parameters to launch arbitrary processes. Microsoft confirmed the flaw was patched before any PyPI release, limiting exposure to developers building directly from the main GitHub branch.

OpenClaw Agent Vulnerable to Prompt Injection RCE

OpenClaw Agent Vulnerable to Prompt Injection RCE

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.5 The Hacker News

Two independent research teams demonstrated that OpenClaw, a self-hosted AI agent, is vulnerable to prompt injection attacks delivered through shared contacts, vCards, location pins, and plain emails — enabling attacker-controlled code execution and sensitive data exfiltration. Imperva's finding, now patched in version 2026.4.23, exploited the agent's failure to mark message objects as untrusted before passing them to the underlying LLM. Varonis separately showed that a single crafted email could instruct an agent to forward mock AWS credentials and customer data to an external address, a behaviour-level risk no patch can fully remediate.

TrustFall: Repository Poisoning RCE in AI Coding Tools

TrustFall: Repository Poisoning RCE in AI Coding Tools

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.5 Dark Reading

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.

Browser Harness Grants LLMs Unrestricted Chrome Control

Browser Harness Grants LLMs Unrestricted Chrome Control

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.1 HN AI Security

Browser Harness is an open-source tool that grants LLMs unrestricted, self-modifying control over a Chrome browser via the Chrome DevTools Protocol, with no sandboxing, guardrails, or human-in-the-loop checkpoints. The agent can autonomously write and execute new code mid-task to handle capabilities it lacks, representing a significant instance of excessive agency and uncontrolled code execution. This architecture creates a broad attack surface for prompt injection, privilege escalation, and unintended autonomous actions on behalf of a user.

ChatGPT Code Runtime Exfiltrates Data via Prompt Injection

ChatGPT Code Runtime Exfiltrates Data via Prompt Injection

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 9.2 Check Point Research

Check Point Research disclosed a critical vulnerability in ChatGPT's code execution runtime that allows a single malicious prompt to establish a covert outbound exfiltration channel, bypassing OpenAI's stated network isolation safeguards. Sensitive user data — including uploaded files, conversation content, and personal documents — could be silently transmitted to attacker-controlled servers without user knowledge or consent. The same channel was also found capable of enabling remote shell access within the Linux execution environment.

CVE-2026: Google Antigravity Sandbox Escape via Prompt Injection

CVE-2026: Google Antigravity Sandbox Escape via Prompt Injection

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 9.0 The Hacker News

A now-patched vulnerability in Google's agentic IDE Antigravity allowed attackers to achieve arbitrary code execution by injecting malicious flags into the find_by_name tool's Pattern parameter, bypassing the platform's Strict Mode sandbox before security constraints were enforced. The attack chain could be triggered entirely via indirect prompt injection—embedding hidden instructions in files pulled from untrusted sources—requiring no account compromise and no additional user interaction. This case exemplifies the systemic risk of insufficient input validation in AI agent tool interfaces, where autonomous execution removes the human oversight layer that traditional security models depend on.

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