Skill
7 entries mention it. All skills →
Proposed connecting privately hosted models to the development environments, so code stayed private and people had less reason to use unapproved AI tools.
Private LLMs, GPU inference, IDE integration, AI security, Developer enablement
Pointed out injection risks in an approach that let a model query data, especially where untrusted input reaches templates and tools.
Prompt injection, SQL injection, AI security
Suggested using language models to make honeypots more convincing and more useful for studying attackers.
Honeypots, Adaptive security, AI security
Tried building fine-tuning data that spells out the reasoning steps, including steps meant to resist misuse.
NER, Training-data engineering, JSONL, Prompt workflows, AI security
Worked on AI-system security research and submitted a vulnerability report through a responsible-disclosure channel.
AI security, Responsible disclosure, Protocol analysis
Looked at how voice-AI pipelines handle personal information in streaming audio and voice tokens.
Voice AI, Privacy, PII handling, AI security
Studied the sandbox boundaries of AI execution environments through protocol and systems analysis. Unpublished findings are not listed here.
Sandbox forensics, Protocol analysis, AI security, Execution-boundary analysis