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github.comrepo🛡️ Security

Spectrmachina/Ztrust

ZTrust is a Python supply-chain scanner that checks manifests, lockfiles, source and GitHub workflows for vulnerable or malicious dependencies (via OSV.dev), typosquats, leaked secrets, unsafe lockfiles and risky CI patterns such as pwn requests and script injection. It outputs console, JSON and SARIF 2.1.0 and ships as a GitHub Action. It also includes a FastAPI bounty service using commit-reveal and shielded Zcash payouts for researchers.

PythonGitHub ActionsOSV+3
xz-utilstj-actions/changed-filesevent-stream+3

Supply Chain, DevSecOps· Added 27 Oct 2026, published 22 Oct 2026

github.comrepo🛡️ Security

Show HN: VoidAccess – open-source dark web OSINT, from query to a graph

VoidAccess is a self-hosted, MIT-licensed dark web OSINT platform that runs a 13-step pipeline from a research query to a relationship graph. It collects from Tor indexes, paste sites, code forges, security feeds and .onion seeds, applies content-safety filters, and exports STIX 2.1, MISP, Sigma, YARA, Snort, Suricata, CSV and JSON. It runs as a CLI with SQLite or as a Docker Compose stack with PostgreSQL, FastAPI and Next.js.

TorPythonDocker+3
LockBitSTIX 2.1MISP+6

OSINT, Threat Intel· Added 21 Oct 2026, published 20 Oct 2026

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

AikidoSec/safe-chain

Aikido Safe Chain is an open-source local proxy and shell-alias wrapper for npm, yarn, pnpm, bun, pip, uv, poetry, pipx and pdm. It checks every package download, including deep dependencies, against the Aikido Intel malware feed and blocks malicious packages before install. It also enforces a configurable 48-hour minimum package age by suppressing too-new versions in registry metadata. It supports custom registries and a self-hosted malware-list mirror, and has CI/CD install recipes for GitHub Actions, Azure Pipelines, CircleCI, Jenkins, Bitbucket and GitLab.

Aikido SecuritynpmPyPI+3
Aikido IntelSafe Chain

Supply Chain, DevSecOps· Added 17 Oct 2026

huggingface.corepo🧠 AI

Meta Muse Spark Open (816B-A42B) open-weights model card

Model card for Meta Superintelligence Labs' Muse Spark Open, an open-weights, natively multimodal model with 816B total and 42B active parameters and a 1M-token context window. It targets coding and agentic work (tool use, long-horizon tasks, multimodal reasoning, synthetic data generation, LLM-as-judge). It ships in BF16 and NVFP4, needs about 700GB VRAM (NVFP4) or 2TB (BF16), runs on SGLang, vLLM, Transformers, TensorRT-LLM, Unsloth, llama.cpp and MLX, and supports a reasoning_effort setting. The Muse Model License requires "Built with Muse Spark Open" attribution and a separate agreement for Model-as-a-Service above $20M revenue. The card reports safety results against Kimi K3 on cyber, chem/bio and loss-of-control evals.

Hugging FaceTransformersvLLM+8
Muse Spark OpenMetaMeta Superintelligence Labs+15

models, multimodal, inference· Added 17 Oct 2026

github.comrepo🧠 AI

Llama.cpp on a jailbroken PS5: run any GGUF model natively on the console

PS5LM is a homebrew app for jailbroken PS5s (firmware 7.00–13.60). It runs llama.cpp with the ggml-vulkan backend on the console's RDNA 2 GPU, using 11.4 GB of shared memory, and loads any GGUF model. It serves OpenAI /v1/chat/completions, Anthropic /v1/messages (usable from Claude Code, Codex and opencode) and a browser chat page on port 8081. It also supports image-projector vision models and TypeSafe-style decision models through a /v1/systemone endpoint. A planner picks the longest context and best cache that fit the free memory, and the app downloads models from Hugging Face.

llama.cppGGUFVulkan+9
TypeSafeClefGemma 4+2

inference, models· Added 17 Oct 2026, published 16 Oct 2026

github.comrepo🧠 AI

Microsoft Agent Framework python-1.20.0 release

Release notes for python-1.20.0 of Microsoft's Agent Framework, an open-source agent/workflow orchestration library. This release adds native vector-store connectors for DuckDB, SQL Server and MongoDB plus a TypeSafe AI connector, redesigns Foundry hosting around request-scoped agent factories and sandbox-isolated sessions, adds computer-use support to Responses clients, and ships Magentic manager and handoff-routing improvements for multi-agent orchestrations alongside a large batch of MCP, Bedrock, Gemini, Anthropic and Ollama provider fixes.

Model Context ProtocolPythonDocker+7
MicrosoftMicrosoft Agent FrameworkDuckDB+4

agents· Added 6 Oct 2026

github.comrepo🧠 AI

browser-use/jev-ultrafast

jev-ultrafast is an open-source browser automation agent (from Browser Use) that represents each page as an indexed element table and uses a 'TypeSafe' policy to speculatively predict both the next operation (CLICK, TYPE_TEXT, SELECT, SCROLL, WAIT, DONE, BLOCKED) and its target in a single network round trip, only invoking a small LLM (e.g. inception/mercury-2.5 via OpenRouter) to generate text when the operation is TYPE_TEXT. The repo includes a local inspector UI, Chrome automation via a 'Browser Harness' tool, offline tests, and published before/after benchmarks showing a Google Flights search dropping from a median 9.45s to 7.09s and browser protocol calls from 1,092 to 101 across repeated runs.

PythonOpenRouterGemini+2
Browser UseJevTypeSafe+2

agents· Added 6 Oct 2026

github.comrepo🧠 AI

OKX Agent Trade Kit (okx-trade-mcp / okx-trade-cli)

OKX Agent Trade Kit is an open-source MCP server (okx-trade-mcp) and CLI (okx-trade-cli) that let AI assistants like Claude Desktop, Cursor, Claude Code and VS Code place trades and query account data on the OKX exchange via natural-language commands. It runs locally with API keys never leaving the machine, supports module scoping (market, spot, swap, account, earn), a read-only mode for safe querying, multiple profiles, and includes pre-built skill files for agent frameworks plus structured JSON error reporting for debugging failed tool calls.

Model Context ProtocolNode.jsClaude Code+1
OKXClaude DesktopVS Code+1

mcp· Added 2 Oct 2026

github.comrepo🧠 AI

Show HN: Made an open-source Lego AI generator

ldraw-nova is an open-source agentic pipeline where an LLM agent (tested with models like Claude Opus 5.5 and GPT-6 Astra) takes a build prompt, reads LDraw-building instructions, and produces a plan.json describing a model's geometry. From that plan it writes a Python generator script that, when executed, outputs an LDraw (.mpd) 3D CAD source file, viewable in 3D/VR (Meta Quest 3) or exportable to Blender-editable glTF. The agent uses jev-rerank, a semantic search tool with reranking backed by TypeSafe's Jev System One model, to find suitable LEGO parts and example models, falling back to full-text search without an API key; it also uses headless rendering and collision/gap detection to self-inspect and iterate on designs.

DockerPythonBlender+2
TypeSafeJev System Onejev-rerank+13

agents, multimodal· Added 3 Oct 2026, published 2 Oct 2026

github.comrepo🛡️ Security

NVIDIA/OpenShell — sandboxed runtime for autonomous AI agents

OpenShell is NVIDIA's open-source runtime for safely running fleets of autonomous AI agents: each agent runs in an isolated sandbox where kernel-level controls enforce a declared policy over file access, syscalls, and network connections, and credentials are injected only for approved endpoints rather than exposed to the agent directly. Policy changes are checked with formal verification to flag risky new access (new hosts, new API methods) before they're approved, and the project ships a CLI, gateway, Kubernetes/Helm deployment, and a tutorial running OpenCode against an OpenRouter model.

DockerKubernetesLinux+2

AI Security· Added 1 Oct 2026

github.comrepo🧠 AI

OpenShell — safe, private runtime for autonomous AI agent fleets

OpenShell is NVIDIA's open-source runtime for running fleets of autonomous AI agents inside isolated sandboxes. Declarative policies cover filesystem, syscall, process and network access. These are enforced at the kernel level, and credentials are injected only into requests bound for approved endpoints. Policy changes are checked with formal verification so risky new access waits for human review. It ships a CLI, a gateway control plane (Helm deployment on Kubernetes), SDKs, extensibility hooks (middleware, interceptors, compute drivers) and installable agent skills, and it can run agents such as OpenCode.

OpenShellDockerPodman+5
NVIDIA

agents, ai-infra· Added 1 Oct 2026

github.comrepo🧠 AI

dzhng/jevgrep

Jevgrep (the `jg` CLI) lets a coding agent ask a natural-language question about a repository and get back relevant files, reading leads, and verbatim source excerpts in one response, using an LLM (Jev) to judge relevance across folders, files, and declarations instead of relying on grep/ripgrep alone. It ships an installable "skill" for Claude Code, Codex, OpenCode and other agents that teaches them when to call jg versus their normal tools, and requires a key for Vercel AI Gateway, TypeSafe, OpenRouter, or OpenCode Zen. A reported ten-task SWE-bench repeat found ~40% lower coding-agent cost ($7.62 to $4.52) but a lower solve rate (7/10 vs 8/10 baseline), explicitly framed as a cost/quality tradeoff rather than a win.

Node.jsTypeScriptBun+4
JevTypeSafeVercel AI Gateway+7

coding-agents· Added 27 Sep 2026, published 26 Sep 2026

github.comrepo🛡️ Security

rewanthtammana/Who-Let-The-Agents-Act

who-let-the-agents-act is a self-hostable lab suite (Docker/Python, Groq-backed LLM agent) with nine isolated scenarios — overpowered data tools, IDOR-style cross-account access, unsafe agent handoffs, refund-limit bypass, indirect prompt injection via poisoned invoices, multi-tenant RAG leakage, secret leakage through debugging, fail-open approval outages, and a multi-hop confused-deputy agent chain. Each scenario runs in multiple modes (vulnerable vs. application-enforced) against the same prompt, recording model plan, policy decision, tool calls, and DB access as JSON so a reader can directly compare what changes when authorization is enforced outside the system prompt.

PythonDocker
IDOR

AI Security, AppSec· Added 26 Sep 2026

github.comrepo🛡️ Security

shai-hulud-detect: multi-ecosystem npm/PyPI/Composer/Crates/Go/Hex/RubyGems supply-chain worm scanner

shai-hulud-detect is a dependency-free Bash scanner that checks projects against a 5,782-entry list of compromised npm, PyPI, Composer, Crates, Go, Hex, and RubyGems package versions, plus content-pattern indicators of compromise (malicious file hashes, C2 domains, dead-man's-switch artifacts, forged commits, suspicious lifecycle hooks) tied to the Shai-Hulud supply-chain attack waves. It supports single-project and bulk scanning, CI-friendly exit codes, JSON/log output for pipeline gating, and a --check-host mode to detect the May 2026 gh-token-monitor/kitty-monitor persistence daemons that wipe hosts if their monitored GitHub token is revoked (with a documented safe remediation order). Detection is read-only; new package entries are sourced from named threat-research firms (Socket, StepSecurity, Aikido, Snyk, JFrog, Wiz, Semgrep, SafeDep, GitGuardian, OX Security) and cited in PRs.

npmPyPIComposer+3
Shai-Huludgh-token-monitorkitty-monitor

Supply Chain, DevSecOps· Added 23 Sep 2026

github.comrepo🧠 AI

yibie/jev-engineering-zh

A Chinese translation (with original source notes) of a design essay synthesizing TypeSafe founder Diogo Almeida's notes on 'Jev,' a typed decision model that drives a coding-agent harness. It argues coding agents are simple loops whose real leverage lies in how context is assembled each turn, and works through six problems inherited from KV-cache-driven, append-only context design: costly model routing, tool-schema bloat, lossy compaction, rare sub-agents, destructive session restarts, and the built-in-capabilities tradeoff. It proposes fixes including query-aware context scoring/visibility tiers, cost-aware routing that accounts for cache reprocessing, tiered tool disclosure, conditional AGENTS.md loading, and shared read-only background retrieval.

Claude CodeCodex
TypeSafeJevDiogo Almeida+4

coding-agents, llm-apps· Added 26 Sep 2026, published 22 Sep 2026

github.comrepo🛡️ Security

Shor

Shor is a source-available, multi-tenant autonomous pentesting platform where a ~17-agent LLM pipeline (discovery, hypothesis, adversarial screening jury, exploitation, proof replay) attacks a target URL and optionally its connected source repo. It wields 30+ real offensive tools (sqlmap, dalfox, nuclei, jwt_tool, hydra, ffuf, etc.) plus SAST/secret/SCA tools (Semgrep, Gitleaks, TruffleHog, OSV-Scanner, Trivy) in white-box mode, and only reports findings whose PoC is deterministically re-executed and confirmed by a code-enforced safety layer under a signed Rules of Engagement, with scan authorization gated behind single-use human-minted tokens on its MCP/automation surface.

SemgrepGitleaksTruffleHog+3
MITRE CAPECPolyForm Noncommercial License 1.0.0

Offensive Security, AppSec, AI Security· Added 22 Sep 2026, published 19 Sep 2026

github.comrepo🧠 AI

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.

Claude CodeCodexPython+4
JevTypeSafeHermes+2

coding-agents, agents, ai-infra, mcp· Added 26 Sep 2026, published 18 Sep 2026

github.comrepo🧠 AI

vinilana/jev-gateway

jev-gateway is a local proxy that sits between coding agents (Codex, Claude Code, OpenCode, Kilo, Gemini CLI, Devin) and their LLM backend, intercepting only the tool-selection decision and routing it to TypeSafe's small, fast "Jev" model instead of the main reasoning model, while forwarding everything else untouched. It supports forced tool_choice, hint-based suggestions (for APIs like Anthropic's that can't force a tool mid-turn), a live dashboard for cost/latency/routing metrics, and a companion benchmark repo (jev-gateway-bench) showing routing helps most on debugging tasks but can hurt some models on feature-building tasks.

Claude CodeCodexOpenCode+4
jev-gatewayTypeSafeJev+4

ai-infra, coding-agents, mcp· Added 26 Sep 2026, published 18 Sep 2026

github.comrepo🧠 AI

coldteadotai/abide

Abide is a CLI (npx @coldtea/abide) that hooks into Claude Code, Codex and OpenCode to check every agent edit or turn against project rules written in AGENTS.md/CLAUDE.md that a linter can't enforce (e.g. 'never let a raw error reach a user', 'no premature abstractions'). It uses Jev, TypeSafe's calibrated decision model, to answer a typed yes/no probability per rule per diff instead of a full LLM call, making it cheap (~300ms, fractions of a cent per turn) enough to check every edit; violations above a threshold are fed back to the agent to repair in the same turn.

Claude CodeCodexOpenCode+1
TypeSafeJevVercel AI Gateway

coding-agents· Added 26 Sep 2026, published 18 Sep 2026

github.comrepo🧠 AI

OmniJev/awesome-jev-gallery

An extensive, actively maintained GitHub "awesome list" cataloging the ecosystem that has grown around TypeSafe's Jev and its "System One" typed decision models — a non-generative alternative to chat LLMs that returns calibrated probabilities per option (Choice/Score/Noul primitives) via RLCD training and single-pass constrained decoding. It indexes dozens of open-weight reproductions (OneJev, Rizzo Flow, Laya, Jebadiah, kev), benchmarks and leaderboards (JevBench, Jev Decision Index, JevAdvBench, DecisionBench), downstream tools (browser/robot/trading agents built on the typed API), and the research lineage the design draws on (zero-shot entailment classifiers, InstructGPT's reward model, GLiNER/GLiClass, monoBERT, LLaDA, vLLM, DSPy, RouteLLM, Constitutional Classifiers). It also links commentary auditing TypeSafe's claims (accuracy vs. frontier LLM baselines, security issues found in community tools).

vLLMDSPyOutlines+13
JevTypeSafeDiogo Almeida+31

models, evals, research· Added 29 Sep 2026, published 17 Sep 2026

github.comrepo🧠 AI

AnotiaWang/awesome-decision-models

A community-maintained GitHub list cataloging "decision models" (also called System One models): small/fast models that take a state plus caller-declared questions (Noul/true-false, Choice/multi-option, Score/rubric) and return a probability per answer in one forward pass, rather than generating text. It tracks the originating TypeSafe AI Jev model and its /v1/systemone API alongside competing hosted models (Upstage Solar Decide, Liquid AI's d1, OpenAI's Decisions API, Inception's Mercury Decide, Respan's Span-01), dozens of open-weight fine-tunes (Cloudflare's Clef, Perplexity's pplx-decider, AWS Strands Decider, Together AI's Tev1, and many Qwen3.5-based community models), zero-training logit-reading approaches, local runtimes (Ollama, Ollaya, llama.cpp-based servers), SDKs across a dozen languages, and a very long list of agent/coding-tool/MCP integrations (browser agents, code review, routing, game-playing demos) that use these models for fast, typed, in-the-loop decisions. The page is truncated at 40k of ~51k characters, so later sections (further toys, demos, and possibly benchmarks) are not reflected here.

Qwen3.5Qwen3.8-27Bllama.cpp+15
TypeSafe AIJevJevBench+33

models, mcp, agents· Added 2 Oct 2026, published 17 Sep 2026

github.comrepo🧠 AI

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.

RustClaude CodeCodex
JevTypeSafe.aiQuill+1

coding-agents, prompting· Added 26 Sep 2026, published 17 Sep 2026

github.comrepo🧠 AI

Mapika/decider

Decider is an open reproduction of TypeSafe AI's System One (Jev) model class: instead of generating text, it reads a state plus a set of typed questions (Choice, Score, or Noul/yes-probability) and returns a calibrated probability distribution for each in one forward pass, with no decoding or parsing. The repo ships 2B/4B/12B and a 35B mixture-of-experts checkpoint (built on Qwen3.5 and Gemma-4 base models), trained on roughly 95 public datasets plus teacher-labelled data, with per-type temperature calibration, GGUF/llama.cpp and vLLM serving paths, an MPS/Apple Silicon port, and a community Snapdragon X Elite NPU port. It benchmarks against TypeSafe's Jev on JevBench and the Decision Index, documenting where it closes the gap (language, tools, retrieval) and where it lags (knowledge-heavy MMLU/GSM8K/GPQA tasks and calibration on hard items).

PythonCUDAMetal+9
TypeSafe AIJevMark Marosi+14

models, inference, training· Added 2 Oct 2026, published 16 Sep 2026

github.comrepo🛡️ Security

y0usaf/pi-jev

pi-jev is an npm extension (@y0usaf/pi-jev) that adds a typed decision layer to the Pi coding agent: a gate scores pending bash/write/edit tool calls on destructiveness, exfiltration risk, scope, and impact before they run, while an output judge scans bash results for leaked secrets and classifies command failures (retry/environment/code_bug/permission/user_error). Answers come back as probabilities or choice distributions rather than prose, are batched into one API round trip to api.typesafe.ai, cached per input, and fail open on any error so a dead endpoint never blocks the agent. The README documents calibration work behind the thresholds (e.g. destructive=0.90, leak=0.90) derived from repeated fixture runs, and details argument/output truncation and key redaction to limit what leaves the machine.

npmTypeScriptNode.js
TypeSafe

AI Security· Added 26 Sep 2026, published 16 Sep 2026

github.comrepo🧠 AI

y0usaf/pi-jev

pi-jev is a decision-layer extension for the Pi coding agent that asks a separate model (Jev/TypeSafe) typed yes/no, choice, or score questions about pending tool calls and their outputs, returning probabilities and confidence scores instead of prose. It gates bash/write/edit calls for destructive, exfiltration, and out-of-scope risk, judges bash output for leaked secrets and failure classification, and exposes a jev_ask tool for the model to request the same structured judgements itself. The README documents empirically calibrated thresholds (e.g. destructive=0.90, leak=0.90) derived from repeated test runs rather than arbitrary defaults.

Node.jsTypeScript
PiTypeSafeJev

coding-agents· Added 26 Sep 2026, published 16 Sep 2026

github.comrepo🛡️ Security

Cloudflare security-audit-skill

security-audit-skill is a Cloudflare open-source coding-agent skill that turns an AI coding agent into a structured vulnerability hunter, running six phases: reconnaissance into architecture.md/coverage-ledger.json, coverage-led hunting by isolated sub-agent "hunters," adversarial candidate validation, structured findings.json output validated against a report-schema.json, independent re-verification of claims, and target-neutral report generation (REPORT.md, FINDINGS-DETAIL.md, NEEDS-VALIDATION.md). It is installed via the Skills CLI (`npx skills add`), uses Node.js validators (validate-coverage-ledger.cjs, validate-findings.cjs), requires a sandboxed environment for safely executing target code/tests/fuzzers, and is the single-repo seed for Cloudflare's larger fleet-wide vulnerability discovery harness described in a companion blog post.

Claude CodeNode.jsCloudflare

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

github.comrepo🛡️ Security

AWSHound — AWS BloodHound OpenGraph Collector

AWSHound is a Go CLI/container tool that collects AWS IAM and authorization data across profiles, config-file opt-ins, or an entire AWS Organization (via cross-account role assumption), and outputs a BloodHound OpenGraph for attack-path analysis. It supports phased collection with on-disk artifacts, offline graph building from previously collected data, and safeguards like --max-api-requests and --max-api-requests-per-minute to bound AWS API traffic during collection.

AWSAWS IAMBloodHound+2

Cloud & Infra, Offensive Security· Added 8 Sep 2026

github.comrepo🛡️ Security

vet (SafeDep)

vet is an open-source CLI (from SafeDep) that scans package manifests, SBOMs, container images, and source repos across npm, PyPI, Maven, Go, RubyGems, Cargo, and Packagist to surface vulnerabilities, malicious packages, and license/quality issues. It cuts through CVE noise by analyzing actual code-usage evidence, queries SafeDep Cloud's threat-intelligence database for real-time malware detection (e.g. flagged packages like express-cookie-parser, eslint-config-airbnb-compat), and lets teams enforce security/license/OpenSSF-Scorecard policies as CEL expressions in CI/CD via SARIF/JSON/Markdown reporting.

npmPyPIMaven+3
MAL-2025-3541MAL-2025-4339MAL-2025-4029+2

Supply Chain, DevSecOps· Published and added 7 Sep 2026

github.comrepo🛡️ Security

The React Native Developer's Security Guide

A GitHub-hosted book focused entirely on securing the React Native developer's workstation and toolchain rather than the shipped app — covering the polyglot execution surface triggered by a single git clone/yarn/pod install (Ruby, CocoaPods, Xcode build phases/XCSSET, Gradle, gradle-wrapper.jar, keystores), CVE-2025-11953 (exposed Metro/RN dev server), ClickFix-style social engineering of developers, CI-as-extended-workstation risks, and Expo/EAS-specific supply-chain concerns. It ships alongside a separate companion repo of 119 Opengrep detection rules, each mapped to a specific chapter's attack technique, plus practical appendices like a safe-clone runbook and a file risk atlas for hardening teams.

React NativeExpoCocoaPods+3
CVE-2025-11953ClickFixXCSSET

Mobile Security, Supply Chain, DevSecOps· Published and added 5 Sep 2026

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