You can point an ultrasonic speaker at an iPhone from a few feet away, play an audio command that no human ear can hear, and the phone will wake up, open Safari, and dial a phone number. To everyone standing in the room, it sounds like dead silence. To the phone, it sounds like someone speaking directly into the microphone. Mobile operating systems use digital low-pass filters to delete all sound above 20,000 Hz, assuming inaudible frequencies can never reach the voice assistant. Yet this attack succeeds without exploiting a single line of software code. The flaw is not in the operating system. It is in the microscopic silicon plate inside the microphone itself. 1. The microscopic machine inside your microphone Inside modern smartphones, microphones are not miniature versions of studio microphones. They are micro-electro-mechanical systems (MEMS) chips smaller than a grain of rice. Inside the chip package sits a flexible silicon diaphragm suspended barely two micrometers above a rigid metal backplate. The two plates form a variable capacitor. When sound waves hit the silicon diaphragm, it flexes inward and outward, changing the electrical capacitance. An onboard preamplifier converts that movement into an electrical voltage. At normal room volumes, the silicon plate moves evenly: double the sound pressure, and the plate flexes twice as far. 2. The non-linear spring catch The flaw appears when sound waves hit the microphone at high pressure (above 90 dB SPL). If you broadcast an ultrasound carrier wave (say, 28,000 Hz) that has an audio command modulated on top of it, the microphone front-end cannot move symmetrically. The mechanical spring resistance of the silicon, the electrical pull between the plates, and the preamplifier circuit all reach their limits. Instead of flexing smoothly, the silicon plate bends slightly more inward than outward. This asymmetry acts like an old crystal radio receiver. Mathematically, a non-linear response squares the incoming wave. That squaring action strips the silent 28,000 Hz carrier away and leaves behind the original human voice command in the audible 300 Hz to 3,500 Hz range. By the time the analog-to-digital converter reads the signal, the ultrasound is already gone. It has physically transformed into ordinary low-frequency sound inside the microphone chamber. The phone digital filter never triggers because the audio reaching the software is already normal human voice. 3. What researchers actually proved (DolphinAttack) In 2017, researchers at Zhejiang University published DolphinAttack, demonstrating this hardware flaw across Siri, Google Now, and Alexa. They successfully forced phones to initiate FaceTime calls, navigate to malicious websites, turn on airplane mode, and unlock smart doors paired to the device. Later research expanded this into attacking through solid tables, using the furniture itself as a physical acoustic conductor. 4. Why this fails in the wild (The physical friction) Demonstrating this in an acoustic laboratory is straightforward. Pulling it off in a crowded coffee shop runs into strict physical limits: First, air absorbs high-frequency sound rapidly. Bass travels through concrete walls, but 30,000 Hz ultrasound loses roughly 1 to 1.5 decibels of power per meter in normal room air. In the original DolphinAttack paper, the effective range was limited between a few centimeters and 1.75 meters. Reaching across an entire room requires a heavy array of high-voltage transducers. Second, ultrasonic emitters act like laser pointers. High-frequency sound travels in narrow beams of 15 to 20 degrees. If you fail to aim directly at the phone one-millimeter microphone port, sound pressure drops below the 90 dB threshold needed to bend the plate. Third, modern phones are waterproof. Devices with IP68 ratings place a hydrophobic Gore-Tex mesh over the microphone hole. The mesh lets air equalize while stopping water, but it acts like a dense acoustic muffler against ultrasonic frequencies, absorbing another 14 dB of signal strength. Finally, voice assistants use personal voice training. If Siri or Google Assistant is set to only respond to the device owner, a generic synthesized ultrasonic command is ignored unless the attacker models the owner vocal pitch. 5. How modern hardware catches it Defending against inaudible voice injection requires catching the acoustic mismatch before speech recognition executes: * Multi-microphone cross-checks: Modern smartphones carry three or four microphones positioned on the bottom, top, and camera bump. When a real human speaks, their voice reaches all microphones with natural arrival delays. A narrow ultrasonic beam hitting one microphone port creates an unnatural phase imbalance across the device. * Harmonic distortion analysis: When a microphone is driven into non-linear demodulation, it does not produce a clean voice recording. It leaves distinct distortion products and second-order harmonics. Software filters can analyze the spectrum and mute the assistant if they detect the signature of mechanical demodulation. * Acoustic damping barriers: Microphone manufacturers can install physical acoustic damping layers inside the chip housing that attenuate frequencies above 22,000 Hz before the sound wave ever reaches the silicon diaphragm. Inaudible voice injection works because digital security models assume analog sensors behave linearly. When sound waves push silicon past its linear limits, the hardware itself executes operations the operating system never authorized.

Are we ready? Are we serious? This is an undeclared emergency. You thought you were still inside the secure bastion of the king’s castle. You have awoken in Helm’s Deep. The orc armies are coming. Cathedral’s AI agents were inside Anthropic’s most sensitive model Slack channels in under 12 hours. Frontier AI is dual-use national power. Agent-speed offense has already outrun static defenses and private channels. Build the post-AI secure bastion. Move what you can into it. Harden the crown jewels. But deterrence is not restored by better walls alone. It is restored by American builders who can see the battlefield, operate at machine speed, and project both defense and offense. Bat signal for the Heretics.

Sydney Sweeney reveals in an interview that she doesn’t care about the PHP vulnerability because she moved everything to Rust in 2024. “They said the rewrite would take six months. We’re on month 30. We haven’t shipped a feature since, but I’m having a very normal Wednesday.”

Lol I am pretty sure someone is runing a deepseek swarm to remotely patch unpatched php boxes. Well good on them.

Complete Tesla Roadster FLYING demo. INSANE!!!

Principal engineer telling product to stop adding requirements at the last second

I am gonna say something risky: Most of the FDEs I've seen are solving BS problems. 1. Existing enterprise workflows were designed around people, not agents. 2. Real AI gains require rebuilding the org chart. 3. Most execs have no incentive to do that, and most CEOs aren't in founder mode. 4. So FDEs automate the status quo, because that's what's easy to sell. But the status quo is stupid and will be obsolete. 5. If you FDE on critical workflows, 1) enterprises are really this dumb to hand off trade secrets? 2) if you know that, shouldn't you start a competing firm? If you FDE on non-essential AND soon-obselete workflows, did you learn anything meaningful and repeatable? 6. If you are a smart young FDE, why spend your best years automating dying workflows and managing people who fear AI will take their jobs? Shouldn't you start an agent-native firm from scratch in that industry instead? Analogy would be, instead of teaching everyone to be AI builders within a tech company, you as FDE build agents that auto-ingest meeting notes for PM, QA, front-end, back-end, devops, UX and help each of them write PRD, Figma, and meeting notes faster for their sync meeting, but the right solution should be to shrink roles, hire full-stack AI builders, and kill meetings. You gain lots of experience with your PRD/Figma/standup meeting sync agents but it's a useless skill. I am not a FDE expert so I might oversimplify things. I am genuinely curious about this topic and welcome any critiques and comments.

I forget where I found this image. Presumably I found it somewhere.