Skip to content
Drix10 Blog

kiban built LSM storage engine with 0.96µs reads

, 8 items in AI Professionals and Community, 4 min read

In this digest (8 items)

kiban is an embedded LSM storage engine written in Rust that achieves 0.96µs median point reads on warm 1M-record workloads. Benchmarks show over 1M point-read calls per second and 2.2-2.7× faster reads than tuned RocksDB. Group commit pushes fully durable writes to 5,379 /s at 16 writers, a 7.5× improvement.

Key points

  • Median point reads: 0.96 µs on warm 1M-record workloads.

  • Point-read throughput: 1M calls/s, 2.2-2.7× faster than tuned RocksDB.

  • Group commit writes: 5,379 /s at 16 writers, 7.5× improvement.

Sources

Binance security issue investigation, funds safe

Binance reports a potential security issue and says user funds are completely safe. Security teams are reviewing information urgently and will update via official channels.

Key points

  • Potential security issue being investigated

  • User funds are completely safe

Sources

lightpanda headless browser library saves time and RAM

lightpanda is a headless browser library that does not graphically render pages. It claims to save a lot of time and RAM.

Key points

  • Library: lightpanda does not graphically render pages.

  • Benefit: saves a ton of time and RAM.

Sources

Better Auth security release scheduled for Tuesday November 3 2026

Better Auth announced a security release scheduled for Tuesday, November 3 2026, with related advisories to appear on GitHub Security Advisories at the same time. The post warns that pre-announced patches can attract attackers.

Key points

  • Security release scheduled for Tuesday, November 3 2026.

  • Related advisories will be published on GitHub Security Advisories at the same time.

Sources

SAFU_Score formula defines metric for SAFU claim

SAFU_Score is calculated as a weighted sum of Coverage_Ratio, Time_to_Full_Restoration, Hot_Wallet_Exposure, and Claim_Frequency_Penalty. The final score ranges from 0 to 100, where higher values make the “SAFU” claim look more ridiculous.

Key points

  • SAFU_Score = (Coverage_Ratio × 0.4) + (Time_to_Full_Restoration × 0.3) + (Hot_Wallet_Exposure × 0.2) + (Claim_Frequency_Penalty × 0.1)

  • Coverage_Ratio = (amount actually recovered or reimbursed) / (amount that left labeled exchange wallets) → 1.0 = full make-whole; lower is worse

Sources

OpenAI eyes on everything system monitors every rollout

OpenAI built an “eyes on everything” system that monitors nearly every single rollout from frontier models across RL training, evals, and internal codex usage. The author warns that such monitoring may not suffice for multi-agent systems where context is distributed across agents.

Key points

  • Coverage: monitors nearly every single rollout from frontier models across RL training, evals, and internal codex usage

  • Method: uses layers of chain-of-thought monitors and investigator agents to dig through a model’s work, run code to

Sources

Simlock in T3 Code gateway announced for Android and iOS testing

Simlock is now usable in T3 Code as a gateway that lets multiple machines connect to a unified API for lease requests. It supports both Android and iOS and is positioned as an alternative to EAS Simulators.

Key points

  • Simlock is a gateway that lets you connect multiple machines to a unified API for lease requests.

  • Works for both Android and iOS and is a great alternative to EAS Simulators.

Sources

neurastream adds interactive architecture explanation

neurastream adds interactive architecture explanation feature that lets you click on unclear parts, send feedback, and receive an explanation. Future versions will require explicit approval before implementing complex plans, currently this behavior is implicit.

Key points

  • Interactive explanation: click on a place you do not understand, send feedback, receive explanation moments later

  • Planned control: next versions will force approval of architecture before implementing complex plans, currently only implicit

Sources