Symfrog-512: High-Capacity Sponge-Based AEAD Cipher (1024-bit State)
- URL: http://arxiv.org/abs/2602.17900v1
- Date: Thu, 19 Feb 2026 23:39:54 GMT
- Title: Symfrog-512: High-Capacity Sponge-Based AEAD Cipher (1024-bit State)
- Abstract summary: This submission includes a complete reference implementation together with deterministic test vectors and a reproducible benchmark suite.<n>The AEAD construction is fully specified, including domain separation, rate and capacity choices, tag generation, and the exact file format used by the reference CLI.<n>Reported performance numbers are produced by the built in benchmark tool under documented hardware and compiler settings.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This submission includes a complete reference implementation together with deterministic test vectors and a reproducible benchmark suite. All source code, build instructions, and regression artifacts are publicly available in the project repository, enabling independent verification and reimplementation of the scheme. The AEAD construction is fully specified, including domain separation, rate and capacity choices, tag generation, and the exact file format used by the reference CLI. Reported performance numbers are produced by the built in benchmark tool under documented hardware and compiler settings. All security claims are made strictly within the ideal permutation model following standard sponge and duplex bounds, and no stronger guarantees are asserted for the concrete permutation beyond the documented analysis and empirical behavior. The implementation aims for constant time behavior with respect to secret dependent operations, although no formal side channel proof is provided. The project is released under the MIT license, and external cryptanalysis, feedback, and reproducibility checks are explicitly encouraged.
Related papers
- Flower Hub: A Reproducible Benchmarking Platform for Federated Learning in Simulation and Deployment [51.83961778298564]
We present Flower Hub, a platform for publishing, discovering, and executing decentralized and federated applications.<n>We show how it enables reproducible benchmarking by packaging benchmarks as executable, versioned applications with standardized metadata, pinned dependencies, and explicit evaluation.
arXiv Detail & Related papers (2026-08-25T20:09:44Z) - Vero: Can AI Agents Build Formally Verified Software Repositories? [45.09790101960906]
Vero is the first benchmark to evaluate joint implementation and proof at the repository level.<n>It contains 43 multi-module instances from real-world repositories spanning Python, Dafny, Verus, and Coq.<n>To improve benchmark reliability, Vero also includes an audit mechanism where agents are allowed to formally prove unsatisfiability of provided specification.
arXiv Detail & Related papers (2026-08-13T17:41:27Z) - Granite: A Modular Methodology for Foundational Verification of Hardware-Software Leakage Contracts [2.76228438275135]
Granite is a methodology for modular verification of both functional correctness and nonleakage of RTL processors against ISA contracts.<n>We prove that the cycle-by-cycle timing of a pipelined RISC design--with speculation, precise interrupts, and I/O--is determined solely by observables specified in an ISA leakage contract.
arXiv Detail & Related papers (2026-07-29T21:44:57Z) - SCDBench: A Benchmark for LLM-Based Smart Contract Decompilers [55.39407031861402]
We introduce SCDBench, a dataset and benchmark methodology for smart contract decompilation.<n>The dataset contains 600 real-world Solidity contracts with paired bytecode inputs, ground-truth source code, and replayable semantic checkpoints.<n>We evaluate Claude Opus 4.7, GPT-5.3-Codex, and GLM-5 in a zero-shot decompilation setting, including GLM-5 variants with and without extended reasoning.
arXiv Detail & Related papers (2026-05-27T20:08:47Z) - Reversa: A Reverse Documentation Engineering Framework for Converting Legacy Software into Operational Specifications for AI Agents [0.0]
This paper presents Reversa, a reverse documentation engineering framework for converting legacy software into traceable operational specifications for AI agents.<n> specialized agents map the project surface, analyze modules, extract implicit rules, synthesize architecture, write unit-level specifications, and review generated claims.<n>The proposal emphasizes three mechanisms: traceability between code and specification, explicit confidence marking, and preservation of gaps for human validation.
arXiv Detail & Related papers (2026-05-18T17:23:13Z) - Benchmarks for Trajectory Safety Evaluation and Diagnosis in OpenClaw and Codex: ATBench-Claw and ATBench-CodeX [54.138213405601896]
ATBench is a diverse and realistic agent trajectory benchmark for safety evaluation and diagnosis.<n>This report presents ATBench-Claw and ATBench-CodeX, two domain-customized extensions that carry ATBench into the OpenClaw and OpenAI Codex / Codex-runtime settings.
arXiv Detail & Related papers (2026-04-16T10:45:13Z) - CUBE: A Standard for Unifying Agent Benchmarks [138.9831263189749]
We propose CUBE (Common Unified Benchmark Environments), a universal protocol standard built on MCP and Gym.<n>CUBE enables any compliant platform to access any compliant benchmark for evaluation, RL training, or data generation without custom integration.
arXiv Detail & Related papers (2026-03-16T18:31:37Z) - DEP: A Decentralized Large Language Model Evaluation Protocol [51.3646001384887]
Decentralized Evaluation Protocol (DEP) is a decentralized yet unified and standardized evaluation framework.<n>By decoupling users, LLMs, and benchmarks, DEP enables modular, plug-and-play evaluation.<n>We develop DEP Toolkit, a protocol-compatible toolkit that supports features such as breakpoint resume, concurrent requests, and congestion control.
arXiv Detail & Related papers (2026-03-01T16:10:16Z) - RepoMod-Bench: A Benchmark for Code Repository Modernization via Implementation-Agnostic Testing [1.4069797812477614]
We introduce a benchmarking framework for repository-level code modernization built on an implementation-agnostic evaluation paradigm.<n>RepoMod-Bench is a benchmark of 21 real-world repositories with standardized interfaces, spanning 8 languages.<n>The benchmark contains 1.6M lines of code (LOC) and 11,616 tests, with repository sizes ranging from 14 to 211K LOC.
arXiv Detail & Related papers (2026-02-26T01:25:00Z) - VeriSoftBench: Repository-Scale Formal Verification Benchmarks for Lean [34.16542476896347]
We introduce a benchmark of 500 Lean 4 proof obligations drawn from open-source formal-methods developments.<n>We find that provers tuned for Mathlib-style mathematics transfer poorly to this repository-centric setting.<n>Providing curated context restricted to a proof's dependency closure improves performance relative to exposing the full repository.
arXiv Detail & Related papers (2026-02-20T16:05:06Z) - SecCodeBench-V2 Technical Report [43.10947096543533]
We introduce SecCodeBench-V2, a benchmark for evaluating Large Language Model (LLM) copilots' capabilities of generating secure code.<n>SecCodeBench-V2 comprises 98 generation and fix scenarios derived from Alibaba Group's industrial productions.<n>For each scenario, SecCodeBench-V2 provides executable proof-of-concept (PoC) test cases for both functional validation and security verification.
arXiv Detail & Related papers (2026-02-17T10:47:06Z) - RealSec-bench: A Benchmark for Evaluating Secure Code Generation in Real-World Repositories [58.32028251925354]
Large Language Models (LLMs) have demonstrated remarkable capabilities in code generation, but their proficiency in producing secure code remains a critical, under-explored area.<n>We introduce RealSec-bench, a new benchmark for secure code generation meticulously constructed from real-world, high-risk Java repositories.
arXiv Detail & Related papers (2026-01-30T08:29:01Z) - EigenAI: Deterministic Inference, Verifiable Results [3.231493128964671]
EigenAI is a verifiable AI platform built on top of the EigenLayer restaking ecosystem.<n>It combines a deterministic large-language model (LLM) inference engine with a cryptoeconomically secured optimistic re-execution protocol.
arXiv Detail & Related papers (2026-01-30T04:46:22Z) - Exposing Hidden Interfaces: LLM-Guided Type Inference for Reverse Engineering macOS Private Frameworks [7.370020034607549]
MOTIF is an agentic framework that integrates tool-augmented analysis with a large language model specialized for Objective-C type inference.<n>By transforming binaries into analyzable interfaces, MOTIF establishes a scalable foundation for systematic auditing of runtime internals.
arXiv Detail & Related papers (2026-01-04T21:44:55Z) - DUALGUAGE: Automated Joint Security-Functionality Benchmarking for Secure Code Generation [18.208257676875586]
Large language models (LLMs) and autonomous coding agents are increasingly used to generate software across a wide range of unmet domains.<n>Existing benchmarks and evaluations for secure code generation fall short-many measure only vulnerability reduction, disregard correctness preservation, or evaluate security and functionality on separate datasets.<n>We present GAUGE, the first fully automated benchmarking framework designed to rigorously evaluate the security and correctness of LLM-generated code in unison.
arXiv Detail & Related papers (2025-11-24T22:26:14Z) - CompassVerifier: A Unified and Robust Verifier for LLMs Evaluation and Outcome Reward [50.97588334916863]
We develop CompassVerifier, an accurate and robust lightweight verifier model for evaluation and outcome reward.<n>It demonstrates multi-domain competency spanning math, knowledge, and diverse reasoning tasks, with the capability to process various answer types.<n>We introduce VerifierBench benchmark comprising model outputs collected from multiple data sources, augmented through manual analysis of metaerror patterns to enhance CompassVerifier.
arXiv Detail & Related papers (2025-08-05T17:55:24Z) - VERINA: Benchmarking Verifiable Code Generation [46.582574591358735]
Large language models (LLMs) are increasingly integrated in software development.<n> Ensuring correctness in LLM-generated code remains challenging.<n>Verifiable code generation offers a promising path to address this limitation.
arXiv Detail & Related papers (2025-05-29T06:12:52Z) - Commit0: Library Generation from Scratch [77.38414688148006]
Commit0 is a benchmark that challenges AI agents to write libraries from scratch.<n>Agents are provided with a specification document outlining the library's API as well as a suite of interactive unit tests.<n> Commit0 also offers an interactive environment where models receive static analysis and execution feedback on the code they generate.
arXiv Detail & Related papers (2024-12-02T18:11:30Z) - Codev-Bench: How Do LLMs Understand Developer-Centric Code Completion? [60.84912551069379]
We present the Code-Development Benchmark (Codev-Bench), a fine-grained, real-world, repository-level, and developer-centric evaluation framework.
Codev-Agent is an agent-based system that automates repository crawling, constructs execution environments, extracts dynamic calling chains from existing unit tests, and generates new test samples to avoid data leakage.
arXiv Detail & Related papers (2024-10-02T09:11:10Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.