{
 "id": "AIR-2026-1396",
 "slug": "mobileinject-cross-modal-consistency-injection-against-mobil",
 "title": "MobileInject Cross-Modal Consistency Injection Against Mobile Agents",
 "summary": "Researchers presented MobileInject to evaluate how multimodal large language model mobile agents are vulnerable to indirect cross-modal prompt injection. The attack embeds malicious instructions within cross-application smartphone content to steer agent behavior.",
 "type": "attack_on_ai",
 "categories": [
  "prompt_injection"
 ],
 "severity": 1,
 "targets": [
  "framework_or_tooling",
  "individual_victims"
 ],
 "products": [
  "MobileInject",
  "Mobile MLLM Agents"
 ],
 "incident_date": "2026-10-19",
 "incident_date_precision": "day",
 "first_reported": "2026-10-19",
 "sources": [
  {
   "url": "https://arxiv.org/abs/2610.23307",
   "publisher": "arXiv",
   "title": "MobileInject: Evaluating Reasoning-to-Action Security of MLLM-Based Mobile Agents under Cross-Modal Consistency Injection",
   "published_at": "2026-10-19"
  }
 ],
 "source_count": 1,
 "confidence": 0.95,
 "status": "published",
 "origin": "news",
 "tags": [
  "multimodal",
  "prompt-injection",
  "mobile-agents",
  "mllm"
 ],
 "created_at": "2026-10-19T05:07:38.588Z",
 "updated_at": "2026-10-19T05:07:38.588Z"
}