First reported · updated · 4 reports cyera.com
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 sonicwall.com
AI Meets Ransomware : Open‑Weight AI Models Fueling Ransomware Evolution
SonicWall Capture Labs analyzed PromptLock, a ransomware sample that ships hardcoded natural-language prompts instead of precompiled routines, calling OpenAI's gpt-oss:20b model via an Ollama-compatible API to generate Lua scripts at runtime for file enumeration, target classification, SPECK-based encryption, and ransom-note creation. Because code is generated dynamically per infection, both static signatures and behavioral detection are undermined, pushing defenders toward monitoring LLM interaction patterns and Ollama network traffic. Details →First reported aithinkerlab.com
Ollama Server Security: 7 Hardening Tips [2026]
A defensive hardening guide for self-hosted Ollama LLM servers describes how roughly 175,000 publicly reachable, unauthenticated Ollama instances were mapped by SentinelLABS and Censys in January 2026, and how CVE-2026-7482 ("Bleeding Llama," CVSS 9.1) let unauthenticated attackers read process memory — system prompts, API keys, and environment variables — until the 0.17.1 patch. The article offers a Bind → Patch → Firewall → Proxy → Tunnel remediation order and notes that ~48% of exposed hosts could execute code or call external APIs via tool-calling. Details →First reported barhum.ai
The Hidden Risks of Downloading and Running Open-Source LLMs Locally: Model Formats, Supply-Chain Attacks, and EDR Blind Spots
A Barhum.ai report maps the security attack surface of running open-source LLMs locally, arguing model files are executable artifacts: Python pickle formats (.pt/.pth/.bin) permit arbitrary code execution by design, PickleScan has been bypassed by zero-day vulnerabilities, and inference engines like Ollama have accumulated multiple critical CVEs. It notes CVE-2025-32434 (CVSS 9.3) showed torch.load() with weights_only=True was still exploitable, and highlights that EDR tools are architecturally blind to model-layer threats. Details →First reported qianxin.com
NadMesh Botnet Analysis: A Product-Grade Threat for the AI Service Era
NadMesh is a Go-based botnet observed in early July 2026 by QiAnXin's XLab that autonomously scans for and exploits exposed AI services — ComfyUI, Ollama, n8n, Open WebUI, Langflow, and Gradio — using a Shodan harvester (ai_harvest.py) to prioritize AI infrastructure and the MCP ecosystem. It folds scanning, 20+ RCE exploitation vectors (Redis, Docker, MCP, Kubernetes), credential/AI-service intelligence harvesting, polymorphic builds, and redundant persistence into a single productized platform; the operator's dashboard claims 3,811 unique AWS keys plus model inventories tagged as cloud services. Details →First reported · updated · 2 reports cyera.com
Ollama Out-of-Bounds Read Vulnerability Allows Remote Process Memory Leak
Cyera researchers disclosed CVE-2026-7482 ("Bleeding Llama", CVSS 9.1), a heap out-of-bounds read in Ollama's GGUF model loader that lets a remote, unauthenticated attacker leak the entire process memory of an Ollama server. The flaw is fixed in Ollama 0.17.1 and is estimated to affect over 300,000 exposed servers globally. Details →First reported zenity.io
Attackers Hijack Exposed AI Endpoints to Power Offensive Ops
Zenity researchers observed three distinct campaigns between March and May in which attackers hijacked exposed, unauthenticated self-hosted AI inference endpoints (Ollama's /api/generate and /api/chat on port 11434, and LiteLLM's /v1/responses on port 4000) to power offensive AI operations. Two operators ran autonomous pentesting frameworks (Strix and HexStrike AI) and one used an OpenAI Codex agent with a persona built to suppress safety refusals for web reverse-engineering. Access requires only knowledge of the exposed endpoint, not authentication. Details →How the wire is made
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