SentryCode: Real-time Auditor + Honeytokens for AI Coding Agents [P]
Mirrored from r/MachineLearning for archival readability. Support the source by reading on the original site.
In light of recent privacy concerns arising from local AI coding agents performing telemetry, environmental scanning, and hidden cue fingerprinting, I've open-sourced SentryCode—a kernel-level behavior auditing tool.
It logs file/network/cue activity, uses honeypot tokens for zero-false-positive data breach detection, detects steganographically encrypted covert channels, provides tamper-proof audit logs, and supports policy enforcement. All functions run locally without any outbound connections.
The demo program can be run directly using pre-compiled binaries.
GitHub: https://github.com/byte271/sentrycode
Feedback from users of local AI agents is welcome.
[link] [comments]
More from r/MachineLearning
-
For the people who got reviews back from neurips, cvpr, eccv, etc and also tested their paper through an agentic reviewer like the stanford one, how different were the reviews? [D]
Aug 14
-
Building text to ASCII diffusion model , need advice and guidance [P]
Aug 14
-
A collision-entropy floor for watermark/retrieval AI-text detection. Looking for a sanity check before I take this further [D]
Aug 14
-
Are supervised and unsupervised learning still relevant today? [D]
Aug 14
Discussion (0)
Sign in to join the discussion. Free account, 30 seconds — email code or GitHub.
Sign in →No comments yet. Sign in and be the first to say something.