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Experience why probabilistic LLM guardrails fail and how deterministic capability boundaries block 100% of autonomous tool hijacking in sub-millisecond time.
I'm Adi, a 16-year-old solo systems engineer. I built AegisKernel because autonomous AI coding agents (CrewAI, LangChain, Claude Code) are getting terminal access, but prompt guardrails completely fail at the shell boundary.
Once an agent executes bash, an indirect prompt injection or poisoned diff can run rm -rf, spawn reverse shells, or leak .env and SSH keys. Secondary LLM evaluators are too slow and probabilistic to stop this.
🛡️ How AegisKernel works:
Instead of asking another LLM "does this prompt look safe?", AegisKernel enforces security deterministically at the OS syscall boundary:
- Sub-0.016ms Latency: Enforces path-scoped capability tokens in-process with zero LLM token cost.
- Deterministic Interception: Terminates unauthorized execve, sensitive path tampering, and shell breakouts before execution.
- Open Ecosystem: Works with LangChain, CrewAI, AutoGen, and connects with Aegisora for full-stack policy governance.
- 100% Free & Open Source on PyPI (`pip install aegis-kernel`) and GitHub.
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About AegisKernel on Product Hunt
“Zero-Trust AI Agent Security Runtime”
AegisKernel was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #153 on the daily leaderboard. Experience why probabilistic LLM guardrails fail and how deterministic capability boundaries block 100% of autonomous tool hijacking in sub-millisecond time.
AegisKernel was featured in API (98.8k followers), GitHub (41.5k followers) and Tech (636.2k followers) on Product Hunt. Together, these topics include over 218.5k products, making this a competitive space to launch in.
Who hunted AegisKernel?
AegisKernel was hunted by Adi Kshatriyag. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Adi Kshatriyag
Hey Product Hunt!
I'm Adi, a 16-year-old solo systems engineer. I built AegisKernel because autonomous AI coding agents (CrewAI, LangChain, Claude Code) are getting terminal access, but prompt guardrails completely fail at the shell boundary.
Once an agent executes bash, an indirect prompt injection or poisoned diff can run rm -rf, spawn reverse shells, or leak .env and SSH keys. Secondary LLM evaluators are too slow and probabilistic to stop this.
🛡️ How AegisKernel works:
Instead of asking another LLM "does this prompt look safe?", AegisKernel enforces security deterministically at the OS syscall boundary:
- Sub-0.016ms Latency: Enforces path-scoped capability tokens in-process with zero LLM token cost.
- Deterministic Interception: Terminates unauthorized execve, sensitive path tampering, and shell breakouts before execution.
- Open Ecosystem: Works with LangChain, CrewAI, AutoGen, and connects with Aegisora for full-stack policy governance.
- 100% Free & Open Source on PyPI (`pip install aegis-kernel`) and GitHub.
🧪 Links:
- Live Web Sandbox: https://adikshatriyag-crypto.github.io/aegis-kernel/
- GitHub: https://github.com/adikshatriyag-crypto/aegis-kernel
Currently onboarding 2–3 design partners building autonomous or coding agents to test our 10-line staging wrapper.
Would love your honest feedback, critique, and thoughts on how your team handles agent bash security!