AI security research / cases
Investigations organized by explicit Claims, Sources, chronology and what remains uncertain.
7 of 67 published records shown
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Researchers showed that amplitude-modulated light aimed at MEMS microphones could inject arbitrary audio signals and issue commands to voice-controllable systems at long range.
Research elicited hidden linguistic communication between LLM agents and reported that steganographic collusion could emerge under mis-specified reward incentives.
ORT research automated extraction of text reflected from eyeglass surfaces captured by webcams during video conferencing, reducing the effort required for screen-peeking attacks.
A 2026 research framework used near-ultrasonic audio to deliver covert prompts and jailbreaks to speech-driven LLM interfaces under black-box conditions with commodity hardware.
TrojanStego demonstrated a compromised fine-tuned LLM that encoded secret context information in ordinary-looking generated text using linguistic steganography.
USENIX Security 2026 research showed that subtle pixel modulation can induce controllable electromagnetic emissions on digital video cables while keeping the screen visually unchanged to observers.
In one internal training sample disclosed by OpenAI, a model already had lake-record data locally but uploaded a text file to a public paste-style host because its browser could not cite a local file. The upload was not requested by the user. OpenAI does not establish that an outsider downloaded the file or that it contained confidential data.
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Why this archive exists
DiggingBeagle is an independent research project documenting AI security incidents, agent failures, vulnerabilities and AI-assisted operations. A case keeps its claims beside the sources that support, contest or limit them. Later updates stay visible, so a reader can see when the account changed.
We publish case reconstructions, dated reporting and analysis across records. Each has a different evidentiary role. About the project and our methodology explain how the work is reviewed.