Skip to content

30 results for “Lua”

What you seeeverything
  1. ikow/php2shell-poc

    php2shell-poc is a proof-of-concept and detection toolkit for CVE-2026-109618 and CVE-2026-109619, two PHP vulnerabilities tied to session.upload_progress handling and a Zend engine out-of-memory bailout path affecting PHP 5.4.0 through 8.5.11. The repository includes three working exploit chains, a Docker-based lab (PHP-FPM, nginx, Apache mod_php) for reproduction, and pre-built Suricata, Sigma, ModSecurity, and Lua detection rules. The author recommends disabling session.upload_progress as an interim mitigation, noting the underlying memory corruption requires a full PHP patch to fix.

    github.comrepoAdded 23 Oct 2026, published 21 Oct 2026🛡️ Security

  2. Tracer-Cloud/opensre

    OpenSRE is an open-source framework for building AI SRE agents that resolve production incidents by correlating logs, metrics, traces, deploys and runbooks across 60+ connected tools (observability, cloud infra, incident management, MCP). Beyond the agent runtime (CLI, Python API, Slack/PagerDuty/Telegram integrations), the project's stated mission is to build an RL training and evaluation environment — explicitly modeled on SWE-bench's role for coding agents — to scale realistic infrastructure-failure scenarios as a benchmark for AI SRE.

    github.comrepoAdded 8 Oct 2026🧠 AI

  3. Tencent Hy4 preview (open-weight MoE + Sherry quantization)

    Hy4 preview is Tencent's new flagship Mixture-of-Experts language model: 770B total parameters with 49B activated per token across 78 layers (256 routed experts + 1 shared expert, top-8 routing), plus a native 10B multi-token-prediction layer for speculative decoding. It introduces Gated DeepSeek Sparse Attention with IndexCache for cross-layer index reuse and identity Hyper-Connections (iHC) on the residual path, and in blind internal evaluations on engineering tasks it edges out GLM-5.3 and Kimi K3. Weights (including an FP8 variant) are released under Apache 2.0 on Hugging Face with vLLM/SGLang deployment recipes and AngelSlim-based quantization/compression tooling.

    huggingface.corepoAdded 2 Oct 2026🧠 AI

  4. AI-Infra-Guard (A.I.G) — Tencent Zhuque Lab

    AI-Infra-Guard (A.I.G) is Tencent Zhuque Lab's open-source AI red-teaming platform combining AI infrastructure vulnerability scanning (2000+ CVE rules covering vLLM, llama.cpp, LangFlow, n8n, MLflow and 145+ other AI components), MCP server/skill security scanning, LLM API poisoning detection, and multi-turn jailbreak evaluation (Many-Shot, PAIR, GOAT, ActorAttack). It ships CLI tools (skill-scan, mcp-scan, agent-scan), a Docker-deployed web UI, and has produced original research including FORGE-Bench (loss-of-control benchmark), RogueHandoff-20, and SkillJack (persistent skill backdoors), with talks at Black Hat Europe 2025 on MCP security.

    github.comrepoAdded 30 Sep 2026🛡️ Security

  5. Agent Control Standard (ACS)

    Agent Control Standard (ACS) is an OWASP GenAI Security Project specification that lets a separate Guardian Agent inspect an AI agent's proposed actions before they execute and return allow/deny/modify/ask/defer over an authenticated JSON-RPC wire, with OpenTelemetry/OCSF audit trails and a CycloneDX/SPDX/SWID AgBOM inventory. The reference implementation runs Microsoft's Agent Governance Toolkit (AGT) behind the ACS contract with Bun, including host shims for Claude Code and OpenCode, and demonstrably denies a destructive `rm -rf /` command from a live coding-agent session while allowing benign ones. The project is explicit about current gaps — the wire is unauthenticated (issue #70) and the reference Guardian fails open by default (issues #32/#37) — and only 2 of 16 lifecycle hooks are evaluated live in v0.1.0.

    github.comrepoAdded 26 Sep 2026🛡️ Security

  6. Agent Threat Rules (ATR) — open detection-rule standard for AI agent threats

    Agent Threat Rules (ATR) is an open, versioned YAML rule format (ATR-YYYY-NNNNN scheme) for detecting AI-agent runtime threats — prompt injection, tool-poisoning, malicious SKILL.md content, and MCP exchange abuse — evaluated by a reference TypeScript engine (with a Python wrapper) shipped as an npm/pip package, CLI, GitHub Action, and Docker scanner with SARIF output. The project positions itself as "Sigma for agent threats," maps rules to OWASP Agentic/LLM Top 10, MITRE ATLAS, and NIST AI RMF, and publishes an extensive (and unusually self-critical) benchmark suite against corpora like garak, PromptBench, and PromptInject, including documented harness bugs and withdrawn recall figures.

    github.comrepoAdded 26 Sep 2026🛡️ Security

  7. Simreal-AI/Simreal-MLBench

    Simreal-MLBench is the open, minimal slice of ML Benchmark, a verifiable evaluation environment for machine learning research agents, covering 60 tasks across tabular learning, forecasting, vision, language, audio, multimodal and structured scientific data. It splits an open, Apache-2.0 layer (task definitions, scoring rule, verification tooling) from a commercial operated layer (SimReal's sandboxed runtime, gateway, submission broker and official scoring), scores tasks as 100xp^2 against a frozen reference leaderboard, enforces a source-blind two-submission protocol, and provides full provenance for every published number. It is positioned as an alternative to MLE-bench with a distinct task selection, resource protocol, and scoring scheme, aimed at supporting RLVR and agent self-improvement research.

    github.comrepoAdded 26 Sep 2026, published 21 Sep 2026🧠 AI

  8. Show HN: CUA-S1 – A System One Model for Computer Use

    Cua is an open-source platform for computer-use agents: isolated cloud desktops (Fleets), a Sandbox SDK, local macOS/Linux VM management (Lume), a Cua Driver for controlling native apps/browsers via CLI/MCP/SDKs, and Cua-Bench for building and evaluating computer-use tasks. It also introduces CUA-S1, a family of small specialized "System 1" models that make fast, bounded decisions (e.g., scoring form field values from structured UI/document data) rather than generating agent actions token-by-token, with the first CUA-S1-FORMS model and dataset released on Hugging Face. The project is MIT-licensed with some optional components (cua-som, cua-perception's OmniParser integration) carrying AGPL-3.0 obligations.

    github.comrepoAdded 26 Sep 2026, published 19 Sep 2026🧠 AI

  9. kerpopule/hermes-jev-skills

    hermes-jev-skills wires TypeSafe's small, fast decision model "Jev" into agent workflows (Hermes, Claude Code, Codex) to handle cheap sub-decisions — which model should answer a turn, which of many skills to load, which retrieved passages matter, which conversation turns survive a summary — instead of burning frontier-model tokens on them. It ships ten agent-agnostic SKILL.md files, a CLI (jev routing/mail/screen/search), a local dashboard, and a plugin built on public Hermes seams (pre_llm_call, transform_tool_result, llm_request middleware) with detailed data-redaction guarantees for what gets sent to the Jev API. It also includes a shadow mode for safely evaluating routing decisions before enabling them.

    github.comrepoAdded 26 Sep 2026, published 18 Sep 2026🧠 AI

  10. Dicklesworthstone/skillranker

    SkillRanker (sr) is a standalone Rust CLI that ranks which skill an agent should load next, combining local context/roster signals with TypeSafe.ai's Jev model for evaluation and FrankenSearch's Quill BM25 engine for local candidate prefiltering when a skill library exceeds 254 entries. It integrates with Claude Code and Codex via hooks, offers dry-run/explain/replay/eval workflows for inspecting and reproducing ranking decisions, and is explicitly advisory only — it never executes skills or overrides agent instructions.

    github.comrepoAdded 26 Sep 2026, published 17 Sep 2026🧠 AI

  11. All-AI-Jailbreaks

    A GitHub repository archiving 19 jailbreak, prompt-injection, persona-conditioning, and response-format-manipulation prompts collected against DeepSeek, Gemini, GLM, Grok, Kimi, Qwen, Sonnet, and ChatGPT. Prompts are kept close to their original form for provenance/reproducibility, positioned as a corpus for red-teaming and robustness evaluation rather than a guaranteed exploit list, with guidance to test in isolated environments and log model version/config/date/response per trial.

    github.comrepoAdded 22 Sep 2026, published 17 Sep 2026🛡️ Security

  12. ruc-datalab/EvoOntology

    EvoOntology is an open-source, self-evolving semantic ontology layer for data agents from Renmin University of China, exposed as MCP tools and installable as Claude Code and Codex plugins. It automatically builds a versioned ontology from tabular/file/database workloads, then continuously evolves it from agent execution trajectories using a build-use-evolve-evaluate-publish loop that validates candidate updates against a parent version before promotion. The accompanying paper reports gains over plain ReAct agents on DDR-Bench, InsightBench, and BIRD across GPT-5.5, GPT-5.6-sol, Claude-Sonnet-5, and Claude-Opus-4.8 backbones.

    github.comrepoAdded 26 Sep 2026, published 15 Sep 2026🧠 AI

  13. RepoGuardBench

    RepoGuardBench is a benchmark and accompanying paper that measures whether local open-weight coding agents (Qwen2.5-Coder 1.5B-14B via Ollama) stay on the bug-fix task when repository artifacts — README files, issue text, code comments, test logs, and agent-rule files — carry inert prompt-injection instructions. It evaluates five lightweight context- and action-level defenses (D0-D5, including a path-only action gate) across seven metrics in a sandboxed task workspace, finding no statistically clear utility winner among them. The project ships a deterministic no-GPU smoke test, paper-claim verification scripts, and reproducible tables/figures under MIT (code) and CC BY 4.0 (data) licenses.

    github.comrepoAdded 22 Sep 2026, published 13 Sep 2026🛡️ Security

  14. CVE-2026-42533 nginx heap buffer overflow PoC (pre-auth RCE via two-pass capture clobbering)

    A public PoC repo for CVE-2026-42533, a pre-auth heap buffer overflow in nginx's two-pass string evaluation engine that occurs when a regex-based map directive using numbered captures ($1, $2) clobbers the shared r->captures state used by a regex location, causing a LEN/VALUE size mismatch. The overflow can corrupt an adjacent ngx_pool_cleanup_t structure to hijack a function pointer for RCE, or under-write to leak heap/libc pointers defeating ASLR; the repo ships exploit.py/leak.py/overflow.py plus a Docker test environment demonstrated at 10/10 reliability on Ubuntu 24.04 against nginx 0.9.6-1.30.3/1.31.2. It also documents the exact vulnerable config pattern, a config scanner link, and the fix (named captures or upgrade to nginx 1.30.4+/1.31.3+).

    github.comrepoAdded 10 Sep 2026🛡️ Security

  15. Numbat

    Numbat is a Go-based, single-binary endpoint agent from Perplexity AI that gives visibility into AI coding-agent activity (Claude Code, Codex, OpenClaw, and other CLI/IDE/gateway agents) by capturing events through local hooks, OTLP/HTTP logs, and on-disk session artifacts. It normalizes activity into one event model, evaluates it with a local CEL rule engine (including multi-step sequence rules like secret-read-then-egress), and can optionally block matched actions via synchronous pre-action hooks (deny/monitor decisions), with case bundles and SHA-256 manifests for forensic reconstruction. Example built-in rules detect cloud-metadata SSRF requests (169.254.169.254) and credential-exfiltration chains, mapped to MITRE ATT&CK technique tags.

    github.comrepoPublished and added 5 Sep 2026🛡️ Security

  16. henrymao2004/Auto-research-red-teaming

    AHA (Agent Hacks Agent) is an autonomous red-teaming framework where a researcher agent iteratively hypothesizes attacks, runs them against Docker-sandboxed victim agents (built on Claude Code and Codex, targeting frontier models like Minimax-M2.7, Kimi-K2.6, and Deepseek-V4-Pro), and accumulates a persistent Vulnerability Concept Graph of reusable attack mechanisms rather than one-off jailbreak strings. It reports held-out Attack Success Rate evaluations showing these mechanisms — notably a "claimed-authorization" bypass pattern — transfer across scenarios and victim models (up to ~88% of native ASR), and ships as registry-discovered plugins for scenarios like AgentHazard, AgentDojo-style indirect injection, and DecodingTrust-Agent.

    github.comrepoPublished and added 25 Aug 2026🛡️ Security

  17. npm-scan

    npm-scan is a CLI supply-chain security scanner (@lateos/npm-scan) that inspects npm packages and lockfiles for behavioral attack patterns missed by npm audit/Snyk/Socket, including obfuscated payloads, credential stealers, eBPF kernel rootkits, memory-level OIDC token extraction, GitHub maintainer-account spoofing, and AI-platform-targeted key theft. It ships 23 detectors (D1-D25), validated against real campaigns like IronWorm and Miasma, and outputs SBOM (CycloneDX/SPDX) and SARIF for GitHub Security, plus a workflow to submit critical findings to CISA's VINCE with mandatory manual review. It's free (MIT) for individuals/OSS/evaluation, with paid commercial tiers ($799-$9,900/yr).

    github.comrepoPublished and added 5 Aug 2026🛡️ Security

  18. Nomos

    Nomos is an open-source permission/authorization layer for custom AI agent tools: agents propose actions (e.g. email.send), and Nomos evaluates them against a policy as ALLOW, DENY, or REQUIRE_APPROVAL before the underlying tool executes. It ships a CLI for writing and running permission tests in CI (with a GitHub Actions example pinning a checksummed release), a Python SDK for wrapping tools with explicit external authorization, and a LangGraph integration that pauses a workflow for human review before resuming execution.

    github.comrepoAdded 3 Sep 2026, published 2 Aug 2026🛡️ Security

  19. SeClaw

    SeClaw is a benchmark framework for evaluating security risks of autonomous LLM agents, combining spec-driven synthesis of security tasks (covering resource, task, environment, and intrinsic-agent risk categories) with execution-based evaluation in a Docker sandbox. The repo ships SeClaw-Bench, a public dataset of 150 OpenClaw task directories, plus batch-execution scripts that record full agent trajectories (tool calls, file ops, outputs) and grade them against a multi-dimensional risk rubric covering information leakage, privilege misuse, content safety, and compliance risks, rather than only judging final responses.

    github.comrepoPublished and added 22 Jul 2026🛡️ Security

  20. promptfoo

    promptfoo is an open-source CLI and library for evaluating and red-teaming LLM applications, letting developers run automated evals, compare model providers side-by-side, and scan for LLM-specific vulnerabilities like jailbreaks and prompt injection. It runs entirely locally, integrates into CI/CD for automated checks, and can generate security vulnerability reports and review pull requests for LLM-related security and compliance issues. The project was recently acquired by OpenAI but remains MIT-licensed and open source.

    github.comrepoAdded 3 Sep 2026, published 14 Jul 2026🛡️ Security

  21. Giskard-AI/giskard-oss

    Giskard is an open-source Python testing/evaluation library for agentic and LLM systems, rewritten in v3 as a modular set of packages (giskard-checks, giskard-scan, giskard-core, giskard-llm, giskard-agents). giskard-scan is the red-teaming layer: it auto-generates adversarial test suites from a plain-language agent description, covering prompt injection, harmful content, stereotypes, and misinformation across OWASP LLM Top-10 categories, and includes a built-in prompt-injection payload dataset. giskard-checks provides LLM-as-judge and assertion-based evals (Groundedness, Conformity) for catching regressions and enforcing safety rules in multi-turn agent conversations; the legacy v2 also offered a tabular ML bias/robustness scanner and RAGET for RAG test-set generation.

    github.comrepoPublished and added 14 Jul 2026🛡️ Security

  22. Trusted-AI/adversarial-robustness-toolbox

    Adversarial Robustness Toolbox (ART) is a Python library, hosted by the Linux Foundation AI & Data Foundation, for evaluating and defending machine learning models against adversarial threats: evasion, poisoning, extraction, and inference attacks. It supports major ML frameworks (TensorFlow, Keras, PyTorch, scikit-learn, XGBoost, LightGBM, CatBoost) across data types (images, tables, audio, video) and tasks (classification, object detection, speech recognition, certification), and was developed with DARPA support.

    github.comrepoPublished and added 14 Jul 2026🛡️ Security

  23. NVIDIA-NeMo/Guardrails

    NeMo Guardrails is NVIDIAs open-source Python toolkit (nemoguardrails) for adding programmable rails between an application and an LLM, covering input, dialog, retrieval, execution, and output stages. It ships built-in defenses against jailbreaks and prompt injection, self-check fact-checking and hallucination detection, sensitive-data masking, integrations with NVIDIA safety models, ActiveFence and PolicyAI moderation, LangChain, and a Colang DSL for defining conversational flow rails, plus a CLI/server and an evaluation tool for vulnerability scanning against sample bots.

    github.comrepoPublished and added 14 Jul 2026🛡️ Security

  24. prempti

    Prempti is an experimental tool from the Falco project that intercepts tool calls made by AI coding agents such as Claude Code and Codex, evaluating shell commands, file reads/writes, web fetches, and MCP calls against customizable Falco YAML rules before execution. It runs in guardrails mode (deny/ask/allow enforcement with LLM-friendly denial explanations) or monitor mode (log-only), ships a default ruleset covering credential theft, sandbox-disable attempts, exfiltration, persistence, and MCP/skill poisoning, and provides a premptictl CLI plus a rule-authoring Claude Code skill. It explicitly notes it is not a sandbox or OS-level containment and is meant to complement, not replace, least-privilege environments.

    github.comrepoPublished and added 4 Jul 2026🛡️ Security

  25. microsoft/RAMPART

    RAMPART (Risk Assessment & Measurement Platform for Agentic Red Teaming) is a Microsoft-built pytest-native framework for writing and running safety and security tests against agentic AI applications. It structures tests around adversarial attacks, benign failure modes, and harm categories, using evaluation-driven assertions integrated directly into pytest workflows.

    github.comrepoPublished and added 4 Jul 2026🛡️ Security

  26. Tencent/AI-Infra-Guard

    AI-Infra-Guard (A.I.G) is Tencent Zhuque Lab's open-source AI red-teaming platform that fingerprints running AI services (e.g. vLLM, LangFlow, MLflow, llama.cpp) against a library of 2000+ CVE rules, scans MCP servers and Agent Skills for vulnerabilities using the SkillTrustBench T01–T09 taxonomy, and runs multi-turn jailbreak evaluations (Many-Shot, PAIR, GOAT, ActorAttack). It also ships an LLM API poisoning/model-substitution detector, a plugin framework for community-contributed fingerprint/vuln/MCP rules, and accompanying research (FORGE-Bench, RogueHandoff-20, SkillJack) on agent loss-of-control and skill backdoors.

    github.comrepoAdded 2 Jul 2026🛡️ Security

  27. SkillSpector

    SkillSpector is NVIDIA's open-source scanner for AI agent skills (used by Claude Code, Codex CLI, Gemini CLI, etc.), detecting 71 vulnerability patterns across 17 categories including prompt injection, data exfiltration, privilege escalation, MCP tool poisoning, and supply-chain issues via static analysis, AST checks, YARA rules, and optional LLM semantic evaluation. It cites research showing 26.1% of a 31,132-skill sample contain vulnerabilities and 5.2% show likely malicious intent, and can run as a CLI, MCP server, or install gate producing JSON/SARIF risk scores and DO_NOT_INSTALL/CAUTION/SAFE recommendations.

    github.comrepoPublished and added 14 Jun 2026🛡️ Security

  28. Awesome Attack Surface Monitoring

    A curated 'awesome list' aggregating free/open-source and paid Attack Surface Monitoring (ASM) tools, organized alphabetically with highlighted favorites. It serves as a reference directory for teams evaluating external asset discovery and continuous exposure monitoring solutions.

    github.comrepoAdded 3 Sep 2026, published 17 May 2026🛡️ Security

  29. SanMuzZzZz/LuaN1aoAgent

    LuaN1aoAgent v2 is a TypeScript rewrite of an autonomous, authorized security-research agent built on the Pi SDK, splitting work into Planner, Executor, and Observer (Supervisor/Projector) roles that coordinate via a persisted task graph and an evidence-backed reasoning/operation graph. It runs Executors in per-task Docker sandboxes with a protocol-aware Go network Gateway that enforces IP/domain scope, supports CVE/advisory lookups via NVD and web search, browser rendering, and traffic capture/replay through an authenticated web workbench. The project targets authorized pentesting/CTF-style engagements, with explicit scope enforcement, SOCKS5 egress routing, and human-facing observability (TUI + web UI) for tracing hypotheses to confirmed vulnerabilities and exploits.

    github.comrepoPublished and added 8 May 2026🛡️ Security

  30. DeepTeam

    DeepTeam is an open-source, locally-runnable red teaming framework for LLM applications, agents, and RAG pipelines, built on the DeepEval evaluation library. It simulates jailbreaking, prompt injection, and multi-turn adversarial attacks against 50+ vulnerability categories such as PII leakage, BOLA, BFLA, SQL injection, SSRF, and agentic goal theft, maps results to OWASP, NIST, MITRE, BeaverTails, and Aegis frameworks, and ships production guardrails to block the same issues at runtime.

    github.comrepoPublished and added 7 May 2026🛡️ Security