The New York Times has a long article (alt link) on surveillance systems aimed at babies. They are increasingly using AI.

Nanit and its rivals want to own 24/7 health tracking for the sub-four-foot set. And their already astonishing levels of baby data collection are just the beginning. Nanit recently raised $50 million from investors to expand its use of A.I. and use its camera to track speech and language development, motor skills and more, while extending its presence in children’s bedrooms into early adolescence.

At least one malware developer is adding text about nuclear and biological weapons to their spyware, in an effort to stop automatic AI analysis.

Details:

The _index.js payload begins with a large JavaScript block comment containing fake system instructions and policy-triggering content. Because it is inside a comment, it does not affect JavaScript execution. The runtime skips it. The real malware begins after the comment with a try{eval(…)} wrapper around a large character-code array and a ROT-style substitution function.

This header appears designed for AI-mediated analysis, not for Node, Bun, or Python. It attempts to derail scanners or analyst copilots that feed the beginning of a file to a language model without clearly isolating the content as untrusted data. In weak pipelines, this can cause refusal behavior, prompt confusion, context pollution, or premature classification before the scanner reaches the actual malware.

This is not a magical bypass against static detection. YARA rules, entropy checks, AST parsing, string extraction, deobfuscation, and behavioral rules still work. But it is a practical anti-analysis trick against naive LLM-first triage systems.

WhatsApp has caught the NSO Group phishing its users, in violation of a court order.

ICE has admitted that it uses spyware from the Israeli company Graphite.