vol-rs

Reverify is an AI-agent verification toolkit for reverse engineering and related code analysis. It places deterministic tools between an agent and its claims: the model proposes hypotheses about a binary or candidate implementation, while parsers, disassemblers, pattern scanners, emulators, equivalence checks, and optional analysis engines compare them with ground truth and return evidence-backed VERIFIED, REFUTED, INCONCLUSIVE, OBSERVED, or INVALIDATED results. Its pure-Python core handles PE, ELF, and Mach-O parsing, x86/x64 and ARM/ARM64 disassembly, byte and pattern inspection, CPU micro-emulation, Protobuf/TLV dissection, and Frida hook generation; optional installations add Capstone, Unicorn, LIEF, Z3, or angr for deeper analysis. The project exposes the verification loop through a command-line interface and an MCP server that agents such as Claude Code and Cursor can call. It also records verified, observed, proved, and refuted results in a content-keyed local ledger, allowing grounded facts and negative findings to survive context resets, compaction, and new sessions. A rollover and orchestration system hands sessions off through files rather than model-written summaries, keeping verified facts separate from unverified notes. Reverify includes claim types for bytes, typed reads, instructions, patterns, emulation, behavioral or formal equivalence, imports, exports, sections, and—when angr is installed—functions, calls, references, and reachability. It is distributed from PyPI and licensed under the MIT License. The repository states that it is intended for authorized reverse engineering, malware analysis, CTF work, interoperability research, and software the user owns or is permitted to analyze.

Rust is a systems programming language and toolchain developed by the Rust project. Its compiler, standard library, documentation, package manager and build tool Cargo, formatter rustfmt, linter Clippy, and editor support are maintained in the main repository. The language uses a rich type system and ownership model to enforce memory and thread safety at compile time, while targeting fast, memory-efficient software for critical services, embedded devices, and integration with other languages. Rust is primarily distributed under the MIT and Apache 2.0 licenses, with portions under BSD-like licenses.

Rerun is an open-source SDK and data layer for recording, querying, visualizing, transforming, and streaming multimodal physical-robotics data. It ingests multi-rate data such as images, point clouds, transforms, time series, joint states, tensors, and video from robot logs, human-data rigs, simulation, and web video, using formats including MCAP, RRD, and LeRobot. Its built-in viewer synchronizes and renders the data in real time for episode scrubbing, sensor comparison, and live computer-vision pipelines; the same data can be queried with dataframes or SQL and streamed directly into training. Rerun is built in Rust on column-chunk storage designed for multi-rate physical data, with Python, Rust, and C++ SDKs and a separate Viewer binary for network streaming and RRD files. The repository describes the project as being in active development, with an evolving API and possible breaking changes.

jc-rs is a command-line parser that converts command output, file formats, and strings into JSON from a single static Rust binary with no runtime dependency. It provides 237 parsers and follows jc's JSON schemas, with the repository reporting 100% compatibility across 934 of 934 oracle-valid fixture pairs. It supports both ordinary JSON output and line-by-line NDJSON streaming as input arrives, including for growing logs. The project is distributed as static binaries for five targets, as five Rust crates, through npm and Homebrew, and as a scratch Docker image. Its compatibility tests compare against fixtures from jc and fail CI if compatibility falls below 100%; the repository also documents a published startup comparison of 4 ms for jc-rs versus 109 ms for jc.

NIGHTRUN is a local LLM runtime written in Rust that boots directly from a USB stick on ordinary x86_64 PCs or from an SD card on a Raspberry Pi 5, without a conventional operating system underneath. Its UEFI application loads a quantized model into RAM, renders a chat terminal through the framebuffer, and runs inference locally and offline without a network stack, host process, or kernel. The installer builds and flashes a bootable image, guides model selection and verified downloads, and supports GGUF inspection and conversion into NIGHTRUN's .nrm container. During boot, the model is streamed into RAM with checksummed sections; storage is then sealed so generation cannot read from disk. The runtime includes custom framebuffer rendering, USB keyboard input, multi-core inference, serial diagnostics, hand-written quantized kernels for x86_64 and Raspberry Pi architectures, and Q8_0, Q4_K, and Q6_K weight formats. It requires Linux, Rust, and approximately 6 GB of free disk space for the model and image.