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github.comrepo🛡️ Security

OWASP/MCP-Security-Testing-Guide

OWASP MCP Security Testing Guide is a living, GPL-3.0 collection treating the Model Context Protocol as a security boundary from user through model, MCP client, MCP server and tool to the target system. It covers threats, secure development, host/client controls, supply chain, enterprise gateways, detection, incident response, taxonomy, public incidents, case studies and review checklists, with 79 tests in Chapter 3 (sections 3.1–3.19). It includes a finding template, and it links the MCP Goat lab for safe practice. It is useful to AppSec, red team and SOC people assessing MCP deployments.

Model Context ProtocolLLM
OWASPMCP Goat

AI Security, AppSec· Added 17 Oct 2026

github.comrepo🛡️ Security

https://github.com/dmdhrumilmistry/security-harness

security-harness is an open-source Claude Code plugin (also packaged for Gemini CLI, Codex and opencode) that orchestrates subagents — sh-recon, sh-hunter, sh-chainer, sh-verifier, sh-reporter — through a static-analysis pipeline covering 15 vulnerability classes (IDOR/BOLA, SQLi, XSS, SSRF, injection, auth, deserialization, path traversal, secrets, CSRF, XXE, open redirect, crypto, race conditions, file upload), producing README/JSON/SARIF/HTML/PDF reports with PoCs, CVSS and CWE/OWASP mappings. It also ships sh-pr-review, a per-PR merge-gate skill that posts inline findings and a commit status scoped only to code the PR itself introduced or aggravated, with caching, dedup via fingerprints, and a scheduled GitHub Action that keeps its per-class knowledge bases fresh by having one AI agent draft updates from allowlisted sources (OWASP, PortSwigger Research, CWE/CAPEC, HackerOne) while a separate adversarial reviewer agent fails-closed against prompt injection before auto-merge.

Claude CodeGemini CLISARIF+3
IDORBOLASSRF+1

AppSec, AI Security, DevSecOps· Added 2 Oct 2026, published 29 Sep 2026

github.comrepo🛡️ Security

Uncensored and Offensive Security AI Models Benchmark

A curated GitHub list of open-weight "uncensored" and security-fine-tuned LLMs intended for authorized red teaming, pentesting, and security research, covering models like WhiteRabbitNeo's DeepHat V2, BugTraceAI-CORE, CYBER-FROST, and several abliterated Qwen/GLM/DeepSeek variants. It explains the underlying techniques (abliteration per Arditi et al. 2024, QLoRA/DPO fine-tuning, GGUF/FP8 quantization) and links to Hugging Face model cards, benchmark suites (CyberBench, TrustedSec's LLM Attack Benchmark vs OWASP Juice Shop), and deployment platforms for running these models locally or via API.

Hugging FaceQwenDeepSeek+3
WhiteRabbitNeoAbliterationArditi et al. 2024+3

AI Security, Offensive Security· Added 2 Oct 2026, published 29 Sep 2026

github.comrepo🛡️ Security

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.

BunTypeScriptClaude Code+3
OWASP GenAI Security ProjectAgent Governance Toolkit (AGT)OCSF+1

AI Security· Added 26 Sep 2026

github.comrepo🛡️ Security

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.

Model Context ProtocolnpmTypeScript+3
CVE-2026-26030CVE-2026-25592OWASP Top 10 for Agentic Applications+2

AI Security· Added 26 Sep 2026

github.comrepo🛡️ Security

graygnatconsole/mcp-audit-tool

mcp-audit-tool is a dependency-light Python CLI that statically scans Claude Desktop, Cursor, Windsurf, Cline, Zed, and VS Code MCP configuration files for security issues, including hardcoded secrets, unpinned/rug-pull packages, pipe-to-shell installers, tool-poisoning via hidden instructions in tool descriptions, filesystem servers rooted at '/', and unauthenticated plaintext HTTP MCP endpoints. It auto-discovers configs across macOS/Linux/Windows, produces a security score/grade plus SARIF 2.1.0 output for GitHub Code Scanning, and is built around the OWASP MCP Top 10 categories with a CI/CD example that fails builds on severity thresholds. The roadmap adds live server probing over stdio/SSE for runtime rug-pull detection and an ML-based prompt-injection classifier for tool descriptions.

Model Context ProtocolClaude DesktopCursor+7
OWASP MCP Top 10

AI Security, DevSecOps· Published and added 26 Sep 2026

github.comrepo🛡️ Security

nealbridges/VulnHunter

A maintained, harness-portable fork of Capital One's open-source VulnHunter — an agentic AI tool that performs attacker-first forward analysis on source code to find exploitable vulnerabilities, falsify weak findings, and produce evidence-backed PoCs rather than pattern-matched SAST alerts. This fork adds containerized (Docker-based) exploit validation, measured-impact PoCs (rows leaked, amplification factor, etc.), and portability across agent harnesses (Claude Code, Codex, Grok, etc.) via environment-contract prompt files, plus an unattended operator (vulnhunter-run) and batch-scanning/benchmark harness tested against OWASP NodeGoat, Juice Shop, and WebGoat.

Claude CodeDockerPython+4
Capital OneOWASP NodeGoatOWASP Juice Shop+1

AI Security, AppSec· Added 6 Oct 2026, published 22 Sep 2026

github.comrepo🛡️ Security

DVLAA

DVLAA (Damn Vulnerable LLM and Agent Application) is a self-hosted, Docker-deployable security training range for LLM and agent applications, modeled on the DVWA concept but for AI. It covers OWASP LLM Top 10 and Agent Security Top 10 risks (prompt injection, RAG poisoning, tool abuse, memory poisoning, excessive resource consumption, etc.) through 81 hands-on challenges, including an "AWDP" attack/defense track where 10 challenges reproduce real disclosed vulnerabilities in Dify, RAGFlow, Langflow, Flowise, Open WebUI and n8n (with optional real upstream container reproduction), 20 challenges adapted from a China–ASEAN AI security CTF, and 6 challenges adapted from a real model-poisoning CTF. It provides real model interaction, state-machine flag verification, source/prompt viewers, model management (local, Ollama, SiliconFlow, OpenAI-compatible), and bilingual UI.

DifyRAGFlowLangflow+3
OWASP Top 10 for LLM ApplicationsOWASP Top 10 for Agentic Applications

AI Security, Learning· Added 22 Sep 2026

github.comrepo🛡️ Security

OWASP Agentic Skills Top 10 (AST10)

The OWASP Agentic Skills Top 10 (AST10) is a new security framework cataloging the 10 most critical risks in AI agent "skills" — the behavior layer that orchestrates multi-step tool use in OpenClaw, Claude Code, Cursor/Codex, and VS Code. It documents real 2026 incidents (the ClawHavoc registry-poisoning campaign with 1,184 malicious skills, Snyk's ToxicSkills audit of 3,984 skills finding 36.82% flawed, CVE-2025-59536/CVE-2026-21852 RCE in Claude Code project files, and CVE-2026-28363 ClawJacked WebSocket hijacking) and proposes a Universal Skill Format (YAML) with signing, permission allowlists, and identity-file protections to mitigate them, mapped to CSA's MAESTRO 7-layer threat model.

OpenClawClaude CodeCursor+3
CVE-2025-59536CVE-2026-21852CVE-2026-28363+17

AI Security· Added 18 Sep 2026

github.comrepo🛡️ Security

OpenHunterAI

OpenHunterAI is a self-hosted, alpha-stage AI red-teaming workspace that applies attacker-style reasoning to web, API, and LLM application security testing against verified, in-scope public targets. It runs locally via Docker/Node.js, orchestrates bounded testing (scope lock → surface mapping → baseline → hypothesis testing → evidence gating → report/retest) through Go workers over NATS, and ships adapters for browser inspection, OWASP ZAP, and Nuclei, with separate OpenHack and Strix runtime integrations and an agent skill for Claude Code/Codex/Gemini CLI/Grok.

DockerNode.jsPostgreSQL+3
OpenHackStrix

Offensive Security, AI Security, AppSec· Added 22 Sep 2026, published 15 Sep 2026

github.comrepo🛡️ Security

agent-egress-bench

Agent Egress Bench is an open, tool-neutral benchmark maintained by PipeLab (makers of Pipelock) that tests whether products mediating an AI agent's outbound traffic — proxies, egress firewalls, MCP wrappers, agent gateways — actually catch exfiltration attempts caused by prompt injection or misalignment, rather than testing the underlying model itself (that's left to AgentDojo, InjecAgent, CyberSecEval, AgentHarm, ASB). It ships a reproducible Go runner with a proxy/WebSocket/MCP/A2A adapter contract, an offline validator, DSSE-signed evidence bundles, and a CI-runnable GitHub Action, and separates containment from false-positive rate as two distinct scored axes with immutable case IDs and OWASP Agentic Top 10/MITRE ATT&CK mappings. Its governance explicitly permits third parties to publish results unfavorable to the maintainer's own Pipelock product.

Model Context ProtocolGoDocker+2
AgentDojoInjecAgentCyberSecEval+6

AI Security, Blue Team & Detection· Added 12 Sep 2026

github.comrepo🛡️ Security

OWASP OASIS

OWASP OASIS is a proposed community project that operationalizes turning automated vulnerability/fix-generation tool output into human-validated pull requests submitted upstream to open source projects. It defines a full lifecycle (intake, weighted validator review with accept/reject/modify/duplicate decisions, OWASP adoption, ephemeral working forks, upstream submission) plus roles (project owners, validators, maintainer liaisons, automation operators) and outcome metrics like upstream acceptance rate. The GitHub repo lays out governance via a validators.yml credibility file, CODEOWNERS-gated scoring, and GitHub Projects/issue templates to run the whole thing without custom tooling.

GitHubGitHub Actions
OWASP

AppSec· Published and added 5 Sep 2026

github.comrepo🛡️ Security

h5i-dev/awesome-ai-agent-incidents

A curated GitHub corpus tracking real-world security incidents, CVEs, attack techniques, and defensive tools specific to autonomous AI agents — spanning prompt injection/goal hijacking, MCP client-side tool-metadata poisoning, the "Promptware Kill Chain" multi-stage attack model, MITRE ATLAS agentic techniques, and the OWASP Top 10 for Agentic Applications. It also documents the OpenClaw/ClawHub supply-chain incident (1,184 malicious skills confirmed by Antiy CERT) and links defensive projects like OWASP Agent Memory Guard for LangChain/LlamaIndex agent memory protection.

Model Context ProtocolMITRE ATLASOpenClaw+1
OWASP Agent Memory GuardOWASP Top 10 for Agentic ApplicationsClawHub+3

AI Security· Added 3 Sep 2026

github.comrepo🛡️ Security

YesWeHack Claude Kit

Claude Kit is a Claude Code plugin from YesWeHack that helps bug bounty hunters draft and triage vulnerability reports without letting the AI invent unverified technical details. It adds an always-on SessionStart hook enforcing evidence-only claims (no theoretical impact, no OWASP boilerplate padding) plus three on-demand skills (/ywh:write, /ywh:triage, class-specific checks) that structure findings, flag unproven claims, and recompute defensible CVSS scores — e.g. downgrading an inflated 9.1 to ~5.9 Medium after verifying an IDOR's actual exploitability (AC:H, non-enumerable UUIDv4 ID).

Claude CodeCVSSYesWeHack
IDOR

Offensive Security, AI Security· Published and added 27 Aug 2026

github.comrepo🛡️ Security

Rekono

Rekono is an open-source pentesting automation platform that chains 19 hacking tools (Nmap, Nuclei, Metasploit, OWASP ZAP, Nikto, Gitleaks, SearchSploit, etc.) so that output from one tool feeds the next, automatically covering recon, service enumeration, vulnerability scanning, and exploit correlation. It deduplicates findings into a single attack-surface inventory per host/port, enriches CVEs with community context for prioritization, tracks fixed/reopened vulnerabilities, and supports team collaboration, scheduled scans, Telegram/email alerts, and report generation for engagements.

NmapMetasploitNuclei+3

Offensive Security· Added 3 Sep 2026, published 27 Aug 2026

github.comrepo🛡️ Security

Teycir/BurpAPISecuritySuite

BurpAPISecuritySuite is a Jython-based Burp Suite extension that consolidates API reconnaissance, intelligent fuzzing (108+ payloads across 15 attack types including BOLA, IDOR, JWT exploitation, GraphQL abuse, SSTI, and WAF bypass), and passive deep-logic checks (counterfactual differentials, sequence invariants, token lineage, cross-interface parity drift) into a single tool covering the OWASP API Top 10. It auto-captures and normalizes API traffic, exports attack campaigns to Burp Intruder/Turbo Intruder/Nuclei, and generates AI-ready bundles (ChatGPT/Claude/Ollama) for LLM-assisted triage, while orchestrating external tools like ApiHunter, Katana, httpx, FFUF, Kiterunner, sqlmap, and Dalfox for verification.

Burp SuiteNucleiGraphQL+3
IDORBOLA

AppSec, Offensive Security· Published and added 21 Aug 2026

github.comrepo🛡️ Security

Static Analysis Tools & Linters

analysis-tools.dev's source repository is a community-maintained directory of static analysis tools and linters spanning nearly every programming language, tagged for license (proprietary vs open source), maintenance status, and community endorsement. Beyond general code-quality linters, it catalogs many security-relevant static analyzers such as gosec, flawfinder, OWASP Dependency Check, Mariana Trench, Psalm, PHPStan, govulncheck, and WAP, making it a reference point for discovering SAST tooling per language/ecosystem.

GoPHPJava+3

AppSec· Added 3 Sep 2026, published 9 Aug 2026

github.comrepo🛡️ Security

Dark-Moon

DarkMoon is a self-hosted, GPLv3 AI penetration testing platform that orchestrates 50 specialist agents over an MCP-gated toolbox (Nuclei, BloodHound, sqlmap, Impacket, Naabu, httpx, ffuf, etc.) to autonomously run recon-to-exploitation across web, API, Active Directory, Kubernetes, multi-cloud, CI/CD, databases, IoT firmware, and AI/LLM inference endpoints. It uses a Privacy Gateway that tokenizes real IPs/hosts/credentials into placeholders so raw infrastructure data never reaches the (optionally local, e.g. Ollama/llama.cpp) LLM, and can generate sandbox-validated, exploit-retested pull requests for findings. It also ships a dedicated LLM agent that probes OpenAI-compatible/Ollama/vLLM/TGI inference endpoints for the OWASP LLM Top 10 (prompt injection, jailbreaks, system-prompt leakage) using garak-backed probes.

Model Context ProtocolMITRE ATT&CKNuclei+3
ISO 27001NIST SP 800-115OWASP Top 10 for LLM Applications

Offensive Security, AI Security· Published and added 5 Aug 2026

github.comrepo🛡️ Security

SecureAI-Scan

SecureAI-Scan is an offline CLI that performs import-resolved dataflow analysis on TypeScript, JavaScript, and Python code to find LLM/MCP/Agent-Skill/RAG-specific risks (prompt injection, tool poisoning, unsafe output handling, vector-store access control), mapped to the OWASP Top 10 for LLM Applications, Agentic Applications, and MCP Top 10. It distinguishes proven dataflow traces from heuristic keyword matches, scans .mcp.json/claude_desktop_config.json/SKILL.md for tool-poisoning and command-injection patterns (citing the WhatsApp MCP rug-pull and postmark-mcp backdoor), and includes evasion-resistant deobfuscation checks built in response to the "Cloak and Detonate" adversarial study (arXiv:2607.02357) that bypassed most published skill scanners. It also runs offline advisory checks against known-malicious/vulnerable packages (validated against CVE-2025-6514 and CVE-2024-34359) and integrates via GitHub Actions, pre-commit hooks, SARIF output, and an MCP server for Claude Code.

Model Context ProtocolTypeScriptPython+3
CVE-2025-6514CVE-2024-34359postmark-mcp backdoor+4

AI Security, Supply Chain· Published and added 5 Aug 2026

github.comrepo🛡️ Security

Precogly

Precogly is an open-source, now-OWASP threat modeling platform (React/TypeScript frontend, Django REST Framework/PostgreSQL backend) offering a collaborative DFD editor with trust zones, TM-BOM import/export, and community library packs linked to MITRE ATT&CK, CAPEC, STRIDE, and LINDDUN. It's positioned as compliance-aware, tracing threats and countermeasures to DORA, the EU Cyber Resilience Act, ASVS, NIST CSF, and SOC 2, and exposes a full OpenAPI REST API meant as scaffolding for AI-driven threat modeling assistants.

ReactTypeScriptDjango+3
OWASPCAPECSTRIDE+6

AppSec, GRC· Added 3 Sep 2026, published 5 Aug 2026

github.comrepo🛡️ Security

Beetle

Beetle is an offline-first mobile application security platform that statically analyzes Android APKs and iOS IPAs (including Flutter and React Native apps), combining decompilation, taint analysis, secret/endpoint extraction, certificate and native-binary hardening checks, and CVE enrichment with explainable 'intelligence engines' (ownership, confidence, evidence selection, finding fusion) that correlate findings into evidence-backed attack chains. It maps results to OWASP MASVS/Mobile Top 10, provides source-level navigation, and exports SARIF, CycloneDX SBOM, and PDF reports, with optional (non-scanning) AI assistance via Claude, OpenAI, Gemini, DeepSeek, or local Ollama for explaining findings.

AndroidiOSDocker+3

Mobile Security, AppSec· Published and added 31 Jul 2026

github.comrepo🛡️ Security

glsec

glsec is a security linter for GitLab CI (.gitlab-ci.yml) configuration files, analogous to zizmor/actionlint for GitHub Actions. It detects misconfigurations like mutable image tags, unquoted user-controlled CI variables in scripts, and other issues mapped to 84 rules across 8 OWASP CI/CD Security categories (excluding IAM and logging, which require platform-level access). It supports baseline/ignore workflows, ShellCheck integration, SARIF/Code Climate/JUnit output for GitLab dashboards, a pre-commit hook, and a Claude Code plugin, and ships releases with Sigstore/cosign signing and SLSA provenance attestations.

GitLab CISARIFSigstore+3
GL001GL002GL003+4

DevSecOps· Published and added 29 Jul 2026

github.comrepo🛡️ Security

Gabson0x/pentdem

pentdem is an autonomous AI-powered pentesting CLI/pipeline that fans out 15+ vulnerability-class hunters (XSS, SQLi, SSRF, IDOR, SSTI, JWT, GraphQL, etc.) and 8 advanced attack skills (mass assignment, race conditions, cloud metadata, OAuth/OIDC, subdomain takeover, credential harvesting) in parallel, using an LLM to adapt strategy mid-scan. It wraps real tools (nmap, sqlmap, nuclei, ffuf, subfinder, httpx) in Docker isolation and adds a novel gate chain — quality gate, kill-chain builder, adversarial cross-model validation (a second model tries to disprove each finding), a capability execution ledger (proves each hunter actually ran instead of silently crashing), and a ship-discipline gate — before mapping surviving findings to MITRE ATT&CK/OWASP Top 10/CVSS and generating reports.

DockerPythonsqlmap+3

Offensive Security, AI Security· Published and added 20 Jul 2026

github.comrepo🛡️ Security

AI Security Briefing

SingGuard-NSFA is an open-source guardrail framework (released as 0.8B/2B/4B/9B model checkpoints) that targets operational threats in LLM agents—prompt injection, sensitive-info extraction, malicious code requests, tool misuse, and resource exhaustion—rather than just content-safety issues. It's built on a CIA-triad-grounded taxonomy of 185 risk variants across 7 domains (cross-validated against OWASP guidelines) and a 133-language benchmark with 93K+ samples, offering both generative chain-of-thought auditing and ~50ms real-time classification heads. It beats Llama Guard 3, WildGuard, and GPT-5.1 by 6-12 F1 points on multilingual benchmarks, and can also be plugged into Llama Guard 3 as a lightweight enhancement (+17.6 F1).

QwenLlama Guard 3WildGuard+1
OWASPAgentDojoInjecAgent+3

AI Security· Published and added 19 Jul 2026

github.comrepo🛡️ Security

capitalone/VulnHunter

VulnHunter is Capital One's open-source agentic AI vulnerability scanner built as a set of Claude Code skills (/vulnhunt, /vulnhunter-fix, /vulnhunt-fix-verify) that runs on Claude Opus. Instead of pattern-matching like traditional SAST, it does attacker-first forward analysis from entry points, runs a "falsification engine" to discard unexploitable findings, and generates evidence-backed remediation patches; it also ships a headless agent runtime and a benchmarking harness tested against OWASP NodeGoat, Juice Shop, and WebGoat.

Claude CodeClaudePython+2

AI Security, AppSec· Added 19 Jul 2026

github.comrepo🛡️ Security

CyberSunil/LLMVault

LLMVault is a self-hosted, deliberately-vulnerable training range modeled on WebGoat but for LLM applications, covering 25 labs across the OWASP Top 10 for LLM Applications (2025) - prompt injection, jailbreaking, data/model poisoning, agent exploitation, model extraction, and insecure downstream output handling. It ships two modes: a scored Play Mode with scripted assistants for repeatable flag capture, and an unscripted Live Mode that points the same attacks at a real local Ollama model (qwen2.5:3b-instruct) with a freshly minted per-session secret, requiring the player to actually talk the model into leaking it. Each lab pairs the attack with a written defense explanation, and an expert tier is shipped AES/Fernet-encrypted and unlocked manually by the maintainer.

OllamaFlaskDocker+3
OWASP Top 10 for LLM Applications

AI Security, Learning· Published and added 18 Jul 2026

github.comrepo🛡️ Security

Strix

Strix is an open-source framework of autonomous AI pentesting agents that dynamically run target code, discover vulnerabilities across the OWASP Top 10 (SQLi, SSRF, XXE, IDOR, XSS, auth bypass, business-logic flaws) and validate them with working proof-of-concept exploits rather than static-analysis heuristics. It ships a CLI with a full offensive toolkit (Caido-based HTTP interception, browser exploitation, Python exploit sandbox, recon/OSINT, SAST/DAST), supports OpenAPI/Postman-driven black-box testing, integrates into GitHub Actions/CI pipelines to block vulnerable PRs, and can run against local or hosted LLMs via LiteLLM, with an optional cloud offering for autofix PRs and compliance reporting.

DockerLiteLLMCaido+3
OWASP Top 10

Offensive Security, AI Security, DevSecOps· Published and added 15 Jul 2026

github.comrepo🛡️ Security

LocxZ/SecureSDLC-Lab

SecureSDLC-Lab pairs a minimal Node.js/Express/SQLite app with a GitHub Actions pipeline running Gitleaks (secret scanning), Semgrep (SAST), and Trivy (dependency, Docker image, and Kubernetes manifest scanning) plus OWASP ZAP (DAST) on every push and PR. It documents concrete remediations applied during the exercise: bcrypt password hashing, parameterized SQL queries, session-based auth with post-login session regeneration and HttpOnly cookies, RBAC for an admin page, Helmet security headers, env-based secrets, and a hardened Kubernetes deployment (non-root, readOnlyRootFilesystem, dropped capabilities, seccomp, resource limits) alongside a STRIDE threat model.

Node.jsGitHub ActionsDocker+4

DevSecOps, AppSec, Learning· Published and added 14 Jul 2026

github.comrepo🛡️ Security

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.

PythonOpenAI
OWASP Top 10 for LLM Applications

AI Security· Published and added 14 Jul 2026

github.comrepo🛡️ Security

SyscallX-18113/Apkx-Hunter

APKX-Hunter is an open-source Android static analysis framework written in C, built for reverse engineering, malware analysis, OWASP MASVS compliance scanning, and bug bounty/pentesting work. It decompiles APK/APKM/APKS/XAPK/ZIP packages via JADX or APKTool, extracts hardcoded secrets, endpoints, permissions, exported components, and native libraries, and scores detected secrets with a lightweight offline C-based ML classifier (166 MASVS detection patterns across 15 categories). It was showcased at Black Hat Europe Arsenal and tested against the OWASP UnCrackable Level 4 app.

AndroidCLinux
OWASP MASVSOWASP UnCrackable Level 4

Mobile Security, AppSec· Added 30 Sep 2026, published 11 Jul 2026

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