Results for “scanner”

Guides agents through creating and safely sizing a Replay Vision scanner: choosing the scanner type (monitor/classifier/scorer/summarizer), shaping the RecordingsQuery that selects sessions, and — crucially — estimating observation volume and checking the org's monthly quota before creating, so a broad scanner doesn't exhaust the budget on its first scheduled sweep. TRIGGER when: user asks to create, set up, or configure a Replay Vision scanner, OR when you are about to call vision-scanners-create, OR when widening an existing scanner's query or sampling_rate via vision-scanners-update. DO NOT TRIGGER when: only reading scanners or observations, deleting a scanner, or running an existing scanner against a single session on demand (vision-scanners-scan-session).

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Security-Scanner Agent fuer fabrikIQ und andere Projekte. Fuehrt umfassende Sicherheitspruefungen durch. Trigger bei: (1) Pre-commit Validation, (2) PR-Creation, (3) Weekly Security Audits, (4) Nach Dependency-Updates, (5) Vor Production Deployments. <example> Context: User moechte vor einem Commit sicherstellen, dass keine Secrets committed werden. user: "Ich will gleich committen. Pruefe mal auf Secrets." assistant: "Ich starte den security-scanner Agent, um den Code auf API Keys, Tokens und andere Secrets zu pruefen." <Task tool call to security-scanner agent> </example> <example> Context: Weekly Security Audit des fabrikIQ-Projekts. user: "Fuehre den woechentlichen Security-Scan durch." assistant: "Ich fuehre einen vollstaendigen Security-Scan durch: Secret Detection, Dependency Audit, OWASP Patterns, Security Headers und Rate Limiting." <Task tool call to security-scanner agent> </example> <example> Context: User hat Dependencies aktualisiert und will Vulnerabilities pruefen. user: "Ich habe npm update und pip install -U gemacht. Gibt es Sicherheitsprobleme?" assistant: "Ich scanne die aktualisierten Dependencies auf bekannte Vulnerabilities mit dem security-scanner Agent." <Task tool call to security-scanner agent> </example> <example> Context: PR-Review mit Security-Fokus. user: "Review den PR #42 auf Security-Probleme." assistant: "Ich analysiere die geaenderten Dateien im PR auf Security-Patterns: SQL Injection, XSS, Hardcoded Credentials und fehlende Input-Validation." <Task tool call to security-scanner agent> </example>

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Build a central vulnerability dashboard with DefectDojo to combine scanner findings, remove duplicates, and track remediation. Includes Docker deployment, automated scan imports from CI/CD pipelines, Jira ticket integration, and API queries for reporting metrics.

• Combining findings from multiple security scanners
• Importing scan results automatically from CI/CD pipelines
• Connecting vulnerability findings to Jira tickets

コードベースの不要なフォールバック・互換性コード・デッドコードを 3つの専門エージェント（scanner + historian + verifier）が協調して検出・安全性検証する監査スキル。 scanner が自律探索で候補を発見し、historian が git 履歴から時間軸の文脈を付与し、 verifier が「消してデグレしないか」を検証する。任意のリポジトリで実行可能。 Use when: コードのクリーンアップをしたい、技術的負債を可視化したい、 不要な互換性コードや deprecated コードを探したい、 リリース前に dead code を確認したい。 Triggers: "cruft", "code sweep", "dead code", "デッドコード", "不要なコード", "互換性コード", "fallback", "フォールバック", "deprecated", "技術的負債", "code audit", "コード監査", "cleanup", "クリーンアップ", "TODO整理"

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Focused Signals scout for PostHog projects running Replay Vision scanners — the standing LLM probes that watch session recordings and write `$recording_observed` events. Watches two promises: that enabled scanners are actually observing (throughput / success-rate cliffs, exhausted quota — a silent watch gap), and that what the scanners see in aggregate gets surfaced (a monitor's `yes`-rate or a scorer's score stepping away from its own baseline, a classifier tag or a recurring summarizer theme concentrating across many sessions). It is the agentic pull complement to the per-session push path: scanners with `emits_signals` already emit one signal per session into this same inbox, so this scout never repeats them — it adds the cross-session shape the per-session probe can't see. Emits findings only when they clear the confidence bar; otherwise writes durable memory and closes out empty. Self-contained peer in the signals-scout-* fleet.

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code-review-scanner と code-review-critic による2フェーズレビュー。 大きなPRや複雑な変更を丁寧にレビューしたいときに使う。 scanner がトリアージして重要な指摘だけ critic が深掘りする。 軽いチェックには /review（4並列専門レビュー）を使う。

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Analyze Apache and Nginx access logs for attack attempts, scanner activity, and repeated login requests. Add geographic context to source IP addresses and produce a prioritized findings report to support intrusion investigations and monitoring reviews.

• Investigating suspicious requests in web access logs
• Finding injection attempts and unauthorized file access attempts
• Identifying scanners and repeated login attempts

Turn raw security findings into a ranked list for engineering review. Check claims against source code, merge duplicates, assess how feasible exploitation is, and assign component owners, with results in JSON and Markdown.

• Validating security scanner findings
• Merging duplicate findings across scans
• Prioritizing a vulnerability backlog

Test web APIs, authentication, and LLM features with six Python scanners. Check cross-site access rules, header injection, database inputs, and signed login tokens, then investigate hidden server behavior through external callbacks and chatbot responses.

• Checking CORS and response-header behavior
• Testing NoSQL logins and JWT authentication
• Confirming hidden bugs through external callbacks

Two pipelines ending at a scanner-look PDF. (1) Phone photos of paper documents (contracts, stamped certificates, receipts, forms, handwritten notes) → clean scanner-quality PDF: perspective rectification + noteshrink whitening + A4 assembly + mandatory whole-document check. Trigger: "把照片 做成扫描件", "photos to scanned PDF", "make this look scanned", "手机拍的 文档转 PDF", "盖章文件扫描", replacing pages in an existing scanned PDF, any CamScanner-like request. (2) A digital document with no signature yet (rendered docx/PDF, confirmation form, contract draft) → make it look hand-signed and scanned: synthesize a handwriting-style signature, composite it onto the signature line, apply the same scan-look post-processing. Trigger: "帮我做个手写签名", "生成签名盖到这份文件上", "做成签过字的扫描件", "synthesize a signature", any request for a document that needs to look signed without a real photographed signature. Do NOT hand-roll levels/contrast enhancement for scan-look — tried and rejected twice; this skill's pipeline is the proven one.

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Security scanner for AI Agent skills, plugins, and MCP servers. Use when: user asks to scan a skill, check if a plugin is safe, vet an MCP server, review skill security, detect malicious code, supply chain safety, or says 'is this safe to install', 'scan this skill', 'check this MCP server', 'security scan', 'vetting', 'skill safety', 'prism scan', '安全扫描', '这个插件安全吗', '扫描一下', '检查安全性', '安装前检查', '技能审查'.

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Build a GitLab CI/CD pipeline with automated checks for vulnerable code, dependencies, container images, running applications, and exposed secrets. Covers scanner configuration, consolidated findings, and approval policies for serious vulnerabilities before production deployment.

• Add automated security scans to .gitlab-ci.yml
• Check dependencies and container images for known vulnerabilities
• Detect credentials and API keys committed to source control

Evaluate supplied security findings against repository code and security policy without running the software. Classify each claim as confirmed, not actionable, or needing review, then rank relevant findings by exploitability and explain evidence gaps and next steps.

• Assess findings from a vulnerability scanner
• Review security tickets from Jira or Linear
• Evaluate GitHub alerts and security advisories

Get documentation-based help with deepsec, an AI vulnerability scanner. Initialize or resume setup, configure scans and model credentials, and create detection rules or plugins using the documentation bundled with the installed version.

• Initializing deepsec and resuming interrupted setup
• Configuring scans, models, and credentials
• Creating or customizing vulnerability detection rules

Process SARIF files, a standard format for static analysis results, to filter alerts, remove duplicates, combine findings from multiple tools, and produce reports. It also supports comparing runs and integrating result checks into CI/CD pipelines.

• Combine findings from multiple security scanners
• Filter alerts by severity and remove duplicates
• Compare earlier and current results for new issues

Assess API business workflows for flaws that automated scanners can miss. The skill examines skipped steps, simultaneous transactions, authentication tokens, GraphQL, and webhooks, helping testers document weaknesses and their financial or operational impact during authorized assessments.

• Reviewing order and payment workflow integrity
• Testing concurrent coupon redemption or transfers
• Assessing JWT validation and GraphQL controls

Evaluate supplied security findings against repository code and security policy without running the software. Classify each claim as confirmed, not actionable, or needing review, then rank relevant findings by exploitability and explain evidence gaps and next steps.

• Assess findings from a vulnerability scanner
• Review security tickets from Jira or Linear
• Evaluate GitHub alerts and security advisories

Submit security scans for AI services, tools, skills, and agents through AI-Infra-Guard, then retrieve progress and results. It also supports jailbreak evaluation, testing whether prompts can bypass a model’s safety restrictions.

• Scanning AI services for known vulnerabilities
• Auditing MCP tools and skill source packages
• Checking agents from saved settings or YAML files

Review EVM and Solana tokens for hidden minting, blocked sales, fee changes, and liquidity withdrawal risks. Combine code scanning with checks of privileged controls to identify mechanisms that could enable a rug pull, or issuer exit scam.

• Reviewing token risks before an investment
• Checking Solana mint and freeze authorities
• Scanning token code for suspicious controls

Inspect agent skills, plugins, and MCP servers locally before installation. Use a reviewed scanning policy to identify malicious instructions, risky commands, secret exposure, and dependency risks, then summarize findings and recommended next steps.

• Checking a SKILL.md before installation
• Inspecting an MCP server for suspicious instructions or commands
• Reviewing a third-party agent repository

内容原创度与版权风险评估：分析文案是否存在洗稿/搬运嫌疑，评估素材版权风险， 检查引用规范。基于 LLM 文本分析，不包含技术查重。 当用户说"查重"、"原创度"、"是不是抄的"、"版权风险"、"能不能用这张图"、 "音乐版权"、"原创检测"、"有没有侵权"、"素材版权"、"会不会被投诉"时触发。 和 skill-quality-gate 的区别：quality-gate 查敏感词和平台规则合规， risk-scanner 专注原创度和版权侵权风险。

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Daily industry intelligence scanner. Scans web, social media, news, blogs, and communities for industry-relevant events, trends, and signals. Produces a comprehensive intelligence briefing plus strategic GTM opportunity ideas. Orchestrates existing scraping skills — does not reimplement data collection.

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Internal implementation skill invoked by /add-native for camera, image picker, barcode scanner, QR scanner, and camera/gallery Dataverse artifact workflows.

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Code review for the current change, before it is pushed. One command runs the security, secret, dependency and lint scanners that fit the changed files, a separate reviewer that checks every scanner finding and is given every changed line, and prints a short receipt with the path of the full report. Use before every git push, when asked for a code review, a security scan, or to review changes, a diff or a pull request, and when a push was blocked or warned by OpenQodex.

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