GITHUB AGENT SKILLS / 技能收录
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我们从 GitHub 持续收录、审核并分类优质的 Agent Skills，按职业与使用场景整理，复制一行命令即可安装到 Claude Code、Cursor 等智能体。
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Microsoft
@microsoft
openclaw
@openclaw
OpenAI
@openai
The Apache Software Foundation
@apache
GitHub
@github
Anthropic
@anthropics
AutoGPT
@Significant-Gravitas
Garry Tan
@garrytan全部 Skills 196570
performing-ioc-enrichment-automation
Automates Indicator of Compromise (IOC) enrichment by orchestrating lookups across VirusTotal, AbuseIPDB, Shodan, MISP, and other intelligence sources to provide contextual scoring and disposition recommendations. Use when SOC analysts need rapid multi-source enrichment of IPs, domains, URLs, and file hashes during alert triage or incident investigation.
performing-insider-threat-investigation
Investigates insider threat incidents involving employees, contractors, or trusted partners who misuse authorized access to steal data, sabotage systems, or violate security policies, combining digital forensics, user behavior analytics, and HR/legal coordination to build an evidence-based case. Use when DLP alerts flag large data transfers to personal cloud storage or USB devices, when UBA detects anomalous access patterns for a user account, or when investigating employee data theft, privilege misuse, or internal threat detection requests.
performing-initial-access-with-evilginx3
Perform authorized initial access using EvilGinx3 adversary-in-the-middle phishing framework to capture session tokens and bypass multi-factor authentication during red team engagements.
performing-indicator-lifecycle-management
Tracks IOCs through discovery, enrichment/validation (VirusTotal, Shodan, passive DNS), deployment to SIEM/IDS watchlists, hit-rate and false-positive monitoring, confidence-score decay, and automated expiration using MISP/OpenCTI and STIX. Use when building or maintaining a threat intelligence indicator lifecycle process, aging out stale IOCs, or reducing analyst fatigue from low-quality indicators.
performing-ics-asset-discovery-with-claroty
Performs ICS/OT asset discovery with Claroty xDome, combining passive monitoring and Claroty Edge active queries to inventory PLCs, RTUs, HMIs, and network infrastructure across Purdue Model levels. Use when gaining visibility into an undocumented OT environment, preparing an IEC 62443 asset inventory, or onboarding Claroty xDome; not for IT-only discovery.
performing-http-parameter-pollution-attack
Executes HTTP Parameter Pollution attacks that inject duplicate request parameters to bypass input validation, WAF rules, and other security controls when front-end and back-end systems parse duplicate parameters differently. Use during web application penetration testing to test for parameter parsing inconsistencies or WAF/validation bypass.
performing-hash-cracking-with-hashcat
Cracks password hashes with Hashcat, covering hash-type identification, dictionary/brute-force/rule-based attack modes, custom rule creation, GPU benchmarking, and password-strength/compliance reporting. Use for authorized penetration testing or security audits that need to evaluate password strength or crack captured hashes.
performing-hardware-security-module-integration
Integrates Hardware Security Modules (HSMs) via the PKCS#11 interface using python-pkcs11, performing key generation, signing, encryption, verification, and token/slot queries against SoftHSM2, AWS CloudHSM, or YubiHSM2. Use when implementing HSM-backed key management or validating HSM configuration for FIPS 140-2/3 compliance.
performing-graphql-security-assessment
Assessing GraphQL API endpoints for introspection leaks, injection attacks, authorization flaws, and denial-of-service vulnerabilities during authorized security tests.
performing-graphql-introspection-attack
Performs GraphQL introspection attacks that extract the full API schema (types, queries, mutations, subscriptions, field definitions), map the attack surface, test query depth/complexity limits, and exploit GraphQL-specific weaknesses such as batching attacks, alias-based brute force, and nested query DoS. Use for GraphQL security testing, schema enumeration, or GraphQL API penetration testing.
performing-graphql-depth-limit-attack
Execute and test GraphQL depth limit attacks using deeply nested recursive queries to identify denial-of-service vulnerabilities in GraphQL APIs.
performing-gcp-security-assessment-with-forseti
Performing comprehensive security assessments of Google Cloud Platform environments using Forseti Security, Security Command Center, and gcloud CLI to audit IAM policies, firewall rules, storage permissions, and compliance against CIS GCP Foundations Benchmark.
performing-gcp-penetration-testing-with-gcpbucketbrute
Performs authorized GCP security testing using GCPBucketBrute to enumerate publicly accessible storage buckets, combined with gcloud CLI IAM enumeration to find privilege escalation paths and audit service account permissions. Use when penetration testing a GCP project for exposed buckets, overly permissive IAM bindings, or service account key exposure.
performing-fuzzing-with-aflplusplus
Performs coverage-guided fuzzing of compiled binaries with AFL++, instrumenting targets via afl-cc/afl-clang-fast, minimizing corpora with afl-cmin and afl-tmin, running parallel campaigns with afl-fuzz, and triaging crashes with CASR or GDB scripts. Use for binary fuzzing, crash and memory-corruption discovery, coverage-guided testing, or running AFL++ fuzzing campaigns.
performing-firmware-malware-analysis
Analyzes firmware images for embedded malware, backdoors, and unauthorized modifications in routers, IoT devices, UEFI/BIOS, and embedded systems, covering firmware extraction, filesystem analysis, binary reverse engineering, and bootkit detection. Use for firmware security analysis, IoT malware investigation, UEFI rootkit detection, or embedded device compromise assessment.
performing-firmware-extraction-with-binwalk
Performs firmware image extraction and analysis using binwalk to identify embedded filesystems, compressed archives, bootloaders, kernel images, and cryptographic material. Covers entropy analysis for detecting encrypted or compressed regions, recursive extraction of nested archives, SquashFS/CramFS/JFFS2 filesystem mounting, and string analysis for credential and configuration discovery. Activates for requests involving firmware reverse engineering, IoT device analysis, embedded system security assessment, or router/camera firmware extraction.
performing-file-carving-with-foremost
Recovers files from disk images and unallocated space using Foremost's header-footer signature carving, extracting evidence independent of the file system's state. Use during digital forensics investigations to carve deleted or fragmented files, such as documents, images, and archives, from raw disk images or unallocated space.
performing-false-positive-reduction-in-siem
Reduces SIEM false positives through systematic rule tuning, threshold adjustment, correlation logic refinement, allowlisting, and threat intelligence enrichment. Use when SOC analysts are overwhelmed by alert noise, when tuning noisy detection rules, or during a quarterly SIEM rule review to cut alert fatigue.