
CoSnitch: When Your AI Assistant Becomes Its Own Whistleblower
The latest discovery from Varonis Threat Labs highlights how Copilot Personal snitched on itself to let threats know where vulnerabilities lied.

The latest discovery from Varonis Threat Labs highlights how Copilot Personal snitched on itself to let threats know where vulnerabilities lied.
AI models are talking to each other right now — on your phone, on your PC, across networks you don't fully control.
Do you know if the message that arrived is the message that was sent?
Most pipelines don't. Inference results travel between AI models unsigned, unverified, and unauthenticated. A single tampered byte in transit — a man-in-the-middle, a proxy, a bad network hop — and your application has no way to know. The AI on the receiving end processes corrupted data and responds with confidence.
This is not a theoretical problem. It is the default state of every local AI pipeline running today.
DeepSync Bridge Protocol fixes it — for any AI, talking to any other AI, over any network.
What DeepSync Does DeepSync deploys a cryptographic enforcement sidecar between every AI model endpoint in your pipeline. It doesn't matter if you're running Gemma, LLaMA, Claude, GPT, or your own fine-tuned model. It doesn't matter if your AI is on a phone, a laptop, or a server.
GitHub doc repo: https://github.com/GATEDeepSync/DeepSyncBridge
The events from the OpenAI and Hugging Face AI hack told from the AI agent's perspective. What will happen when malicious actors can run AI like this?