» Tag
python
115 postsEpistemic Engine verifies AI code and predicts what will break
Epistemic Engine is an open-source Python tool that verifies AI-generated code and forecasts future failures using deterministic git-history analysis.
voidguard: A Static Scanner That Catches Tests That Verify Nothing
voidguard is an open-source static scanner that flags tests, type checks, and CI conditions that pass while verifying nothing.
agent-gate: keep your AI agents from having unchecked power
agent-gate is a dependency-free MIT Python layer that gates AI agent actions behind deterministic checks and one-time tokens, blocking prompt injection and irreversible mistakes.
CommitBrief — AI code reviews, right in your terminal
A provider-agnostic, local-first CLI that reviews your staged changes, a historic range, or a whole GitHub pull request. Zero telemetry, no server. Free and open source.
commitbrief.comPython library verifies OpenAI's signed AI agent traffic (RFC 9421)
regent-httpsig is an open-source Python library that verifies and signs OpenAI-style AI agent HTTP traffic per RFC 9421 and Web Bot Auth drafts.
CVE-2026-69243 PoC: aiohttp Request Smuggling via Rejected WebSocket Upgrade
First public PoC for CVE-2026-69243, an aiohttp request smuggling flaw via rejected WebSocket upgrades causing blind handler invocation behind Nginx.
CVE-Bench: A Sandbox Benchmark for LLM Agents Fixing Real CVEs
CVE-Bench is an open-source benchmark testing LLM agents' ability to fix real Python CVEs inside sandboxed Docker containers.
data2prompt: CLI Tool Fits Data-Heavy Projects into LLM Context Windows
data2prompt CLI profiles and samples CSVs, Excel files, and SQLite databases to fit data-heavy projects into any LLM context window.
State-harness detects LLM agent instability using control theory
Open-source state-harness library uses a Lyapunov energy function to catch token spirals in multi-turn LLM agents and explain failures without extra LLM calls.
Post-quantum cryptography lands in Python with a single pip install
pyca/cryptography 48 now ships ML-KEM and ML-DSA, bringing NIST-standard post-quantum algorithms to Python. Trail of Bits explains what changes for developers and protocols.
LLM Agent Performance Is a Distributed Systems Problem
FixBugs's team shows how token math, parallel chunking, and queues cut LLM agent latency: file analysis dropped from 10 minutes to 40 seconds.