
CiberIA AI Auditor
Evaluate AI safety, reasoning and behavioral risks
What it does
CiberIA AI Auditor helps organizations evaluate AI systems through cognitive cybersecurity assessments. Upload AI responses, choose a framework such as AIsecTest, CEAT or CRS, and receive a detailed audit report covering reasoning stability, operational awareness, safety perception, risk indicators, and behavioral consistency. Designed for organizations that want deeper insight into how their AI systems think and behave.
Does the same job
all alternatives →- AFA free AI risk assessment tool for LLM applications2025 · gettavo.com · ▲37
We’ve built an AI risk assessment tool designed specifically for GenAI/LLM applications. It's still early, but we’d love your feedback. Here’s what it does: 1. it performs comprehensive AI risk assessments by analyzing your codebase against different AI regulation/framework or even internal policies. It identifies potential issues and suggests fixes directly through one click PRs. 2. the first framework the platform supports is OWASP Top 10 for LLM Applications 2025, upcoming framework will be ISO 42001 as well as custom policy documents. 3. we're a small, early stage team, so the…
- LELogira – eBPF runtime auditing for AI agent runsMar 2026 · github.com · ▲26
I started using Claude Code (claude --dangerously-skip-permissions) and Codex (codex --yolo) and realized I had no reliable way to know what they actually did. The agent's own output tells you a story, but it's the agent's story. logira records exec, file, and network events at the OS level via eBPF, scoped per run. Events are saved locally in JSONL and SQLite. It ships with default detection rules for credential access, persistence changes, suspicious exec patterns, and more. Observe-only – it never blocks. https://github.com/melonattacker/logira




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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Launched alongside, June 2026
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Today, I’m proud to announce Homebrew 6.0.0. The most significant changes since 5.1.0 are a new tap trust security mechanism, the new faster, smaller, default internal Homebrew JSON API, sandboxing on Linux, better defaults informed by our user survey, many brew bundle improvements, improved performance and initial support for macOS 27 (Golden Gate). Happy to discuss any questions here!
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hope you enjoy
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- IM
Life & fun · Jun 2026 · hackernewstrends.com