「cve」の検索結果

Run a focused STRIDE-based security review using Bug Hunter-native artifacts. Use whenever the user asks for a full security audit, repository security review, weekly security scan, PR security review with deeper validation, or wants dependency CVEs and threat-model context combined into one workflow.

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Security-first SOP for multi-tenant RAG systems. Activate when a calling agent is building, reviewing, or debugging any retrieval pipeline whose vector store is shared across more than one user, organisation, workspace, customer, or permission scope. Encodes the single non-negotiable rule — **filter at the vector store query, never after retrieval / never after rerank** — together with the per-vendor query-time filter APIs (Pinecone namespaces + `$eq`/`$in`, Weaviate `multiTenancyConfig` + tenant handle, Qdrant `is_tenant` payload index + `Filter.must`, Chroma `where`, pgvector RLS), and the cross-framework adapters (LlamaIndex `MetadataFilters`, LangChain `filter=` dict). Frame the work as preventing CVE-2024-41892 / EchoLeak / Slack-AI-class cross-tenant leakage, not as "adding a filter for relevance".

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Use when breaking out of a container or escalating inside Kubernetes — runc/BuildKit CVEs, privileged/capability/cgroup misconfig escapes, NVIDIA GPU toolkit escape, K8s RBAC abuse, kubelet RCE, ingress/admission-controller RCE, node-to-cluster pivot

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Use when escalating privileges on a Windows host — SeImpersonate Potato chains (GodPotato/PrintNotifyPotato), service & DLL hijacking, UAC bypass (fodhelper/ICMLuaUtil), kernel EoP + BYOVD (CVE-2025-29824), token-rights abuse, LSASS/SAM/DPAPI credential harvesting

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Use when mapping a target's external attack surface or gathering OSINT — subdomain enumeration, attack-surface mapping (httpx/katana/JS secrets), subdomain takeover, multi-cloud/Azure tenant recon, GitHub secret dorking, breach/infostealer credential intel, CVE prioritization (EPSS/KEV)

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Annotated matrices for single-cell genomics. Stores X with obs/var metadata, layers, embeddings (obsm/varm), graphs (obsp/varp), uns. Use for .h5ad/.zarr I/O, concatenation, scverse integration. For analysis use scanpy; for probabilistic models use scvi-tools.

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Provides security review capability for TypeScript/Node.js applications, validates code against XSS, injection, CSRF, JWT/OAuth2 flaws, dependency CVEs, and secrets exposure. Use when performing security audits, before deployment, reviewing authentication/authorization implementations, or ensuring OWASP compliance for Express, NestJS, and Next.js. Triggers on "security review", "check for security issues", "TypeScript security audit".

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Use to run real static analysis over a diff or repo before shipping — Semgrep, CodeQL, secret scanning, dependency CVEs — and triage the findings into what must be fixed now versus noise. Trigger before a release or PR merge, during a security review, or when the user asks to scan the code for vulnerabilities.

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Use DocArray for multimodal Pydantic-style documents, typed DocList and DocVec batches, serialization and local storage, FastAPI payloads, and vector retrieval indexes.

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Ingest a CVE writeup, blog post, advisory, or GitHub repo into the wiki - fetch, dedup via sources:, update the right technique/tool page(s), re-index. Generic knowledge only; never client data.

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N-day / patch-diff workflow - given a CVE/advisory or a suspicious patch, diff pre- vs post-patch to locate the fixed bug, build a PoC for the unpatched version, and run variant analysis for a fresh bug. Triggers - "n-day", "patch diff", "diff the patch", "bindiff".

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Wiki-first "what do I use" lookup - pick the automated TOOL (wiki/tools/), then the PAYLOAD/technique (wiki/payloads/ + wiki/cheatsheets/), for a surface/service/vuln-class BEFORE hand-rolling or working from memory. Use for "tool for <service>", "automated tools for web/<service>", "what should I run on <surface>", "which tool for <X>", "payloads for <X>", "payload arsenal", "cheatsheet for <X>", "how do I exploit <tech/class>", "exploit/attack chain for <X>", "arsenal", any SSRF/XSS/SQLi/SSTI/LFI/JWT/XXE/IDOR/NoSQL/deserialization/CSRF/CORS/CRLF/GraphQL/smuggling/web-cache/OAuth/SAML/MFA/crypto/LDAP/XPath/WebAuthn/file-upload/IMDS/prompt-injection/Modbus ask, plus "privesc arsenal", "CVE arsenal", "default creds", "nuclei templates", "sqlmap/hydra/nmap/bloodhound", "password attacks".

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Enterprise SSL VPN attack - vendor fingerprinting, CVE matrix (Cisco, Fortinet, Citrix, Palo Alto, Pulse/Ivanti), default credentials, pre-auth exploit commands. Wiki-first, FIND schema output.

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Use when scanning code for security vulnerabilities. Use when user says "scan security", "kiểm tra bảo mật", "security audit", "review security", or invokes `/vbs-scan-security`. For large scans (>20 main-language files OR >30 total OR >14 days) processes chunks sequentially. Outputs bilingual reports (vi/en). Optional `--auto-fix` (agentic patch + verify loop) and `--sca` (live CVE lookup via OSV.dev).

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Use when scanning code for security vulnerabilities. Use when user says "scan security", "kiểm tra bảo mật", "security audit", "review security", or invokes `/vbs-scan-security`. Auto-delegates to sub-agents for large scans (>20 main-language files OR >30 total OR >14 days). Outputs bilingual reports (vi/en). Optional `--auto-fix` (agentic patch + verify loop) and `--sca` (live CVE lookup via OSV.dev).

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Detect known malicious npm package versions and install-time supply-chain indicators in repositories, lockfiles, and node_modules. Use when a user mentions an npm compromise, Shai-Hulud, the Keyv/cacheable incident, suspicious preinstall scripts, credential-stealing packages, or asks whether a JavaScript project was exposed to a package supply-chain attack. Do not use as a general CVE or license audit.

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Analyze vulnerable code to identify underlying root causes such as violated assumptions, incorrect invariants, missing validation checks, or unsafe component interactions. Use when investigating security vulnerabilities, CVEs, exploit code, or security audit findings. Infers why the vulnerability exists beyond surface symptoms, identifies systemic issues, and explains the chain of failures that enable exploitation.

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Detects security vulnerabilities by matching code against known vulnerability patterns, insecure coding idioms, and CVE-style patterns. Explains why patterns are risky and under what conditions they are exploitable. Use when analyzing code for security issues, reviewing for common vulnerabilities, or assessing exploitability of suspicious code patterns.

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Automated security scanning for dependencies, code, containers with Trivy, Snyk, npm audit. Use for CI/CD security gates, pre-deployment audits, compliance requirements, or encountering CVE detection, outdated packages, license compliance, SBOM generation errors.

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Think and work like an expert Computer Security Researcher. Use when a task calls for Computer Security Researcher judgment. Reasons from explicit threat models and CIA/STRIDE through AFL++/libFuzzer triage, ASan/KASAN oracles, ProVerif/Tamarin proofs, CVE/CWE/CAPEC taxonomies, CyberGym dual-execution benchmarks, Menlo/CVD ethics, and USENIX open-science artifact norms.

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Security forensics for git repos, AI skills, and MCP servers. Audits dependencies, detects prompt injection, credential theft, runtime dynamism, manifest drift, known CVEs, CISA KEV (actively exploited) vulns, and 2026 attack patterns. Not for fixing vulnerabilities or pentesting.

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Optimize Docker images with multi-stage builds, distroless bases, BuildKit cache mounts, multi-arch builds, compose watch, security hardening (non-root, seccomp, capabilities drop), and vulnerability scanning via docker scout/trivy. Use when user asks to write a Dockerfile, optimize image size, set up docker-compose, debug containers, harden container security, or scan for CVEs. Do NOT use for Kubernetes deployments (use kubernetes), CI/CD pipeline design (use ci-cd), or Terraform (use terraform).

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Analyzing code statically for security flaws: hardcoded secrets, SQL injection, input validation, security headers, dependency CVEs. Not for runtime exploit checks (Probe) or code review (Judge).

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This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.

日本語の概要は準備中です。原文の説明を表示しています。