{
  "id": 14868424,
  "title": "🚨 Does your LLM have a Trojan horse? Meet WeightWatch (and no, it's not for dieting)",
  "url": "https://urgent.news/2026/10/16/tu-llm-tiene-un-caballo-de-troya-conoce-weightwatch-y-no-no-es-para",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-16T04:31:05.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/magopredator/tu-llm-tiene-un-caballo-de-troya-conoce-weightwatch-y-no-no-es-para-hacer-dieta-2a09"
  },
  "original_language": "es",
  "account": "WeightWatch is a new open-source tool designed to detect backdoors in fine-tuned language models. A backdoor is a hidden vulnerability that can be triggered by a specific word or phrase, causing the model to behave maliciously. WeightWatch is a black-box scanner that can detect backdoors without needing access to the original training data or a clean version of the base model. The tool uses a technique called output-to-input loop and canary samples to identify anomalies in the model's behavior. WeightWatch provides a clear verdict on whether a model is clean, suspicious, or backdoored.",
  "summary": "https://github.com/amurlaniakea/weightwatch Si estás leyendo esto en dev.to, es muy probable que hayas descargado un modelo de lenguaje de Hugging Face (o de ese colega entusiasta) para hacer fine-tuning o simplemente para jugar un rato. Pero, ¿alguna vez te has preguntado si ese modelo viene con \"sorpresas\"? No, no me refiero a alucinaciones raras ni a respuestas torpes. Me refiero a un…",
  "key_points": [
    "WeightWatch is open-source tool to detect backdoors in fine-tuned models.",
    "Detects hidden backdoors that activate with specific keywords.",
    "Scans models without original training data or clean base version."
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}