{
 "id": "AIR-2022-0029",
 "slug": "backdoor-attacks-on-deep-learning-models-in-mobile-apps",
 "title": "Backdoor Attacks on Deep Learning Models in Mobile Apps",
 "summary": "Researchers discovered that numerous real-world mobile applications were vulnerable to backdoor attacks through neural payload injection. The empirical study covered critical applications such as face authentication and financial services.",
 "type": "attack_on_ai",
 "categories": [
  "supply_chain",
  "adversarial_evasion"
 ],
 "severity": 1,
 "targets": [
  "enterprise_deployment"
 ],
 "products": [
  "Mobile deep learning apps"
 ],
 "incident_date": "2021-01-18",
 "incident_date_precision": "day",
 "first_reported": "2022-02-03",
 "sources": [
  {
   "url": "https://atlas.mitre.org/studies/AML.CS0013",
   "publisher": "MITRE ATLAS",
   "title": "Backdoor Attack on Deep Learning Models in Mobile Apps",
   "published_at": "2022-02-03"
  },
  {
   "url": "https://arxiv.org/abs/2101.06896",
   "publisher": "arXiv",
   "title": "DeepPayload: Black-box Backdoor Attack on Deep Learning Models through Neural Payload Injection",
   "published_at": "2022-02-03"
  }
 ],
 "source_count": 2,
 "confidence": 0.95,
 "status": "published",
 "origin": "seed_atlas",
 "tags": [
  "backdoor",
  "mobile-apps",
  "neural-payload-injection"
 ],
 "created_at": "2026-10-18T06:55:08.239Z",
 "updated_at": "2026-10-18T06:55:08.239Z"
}