「owasp」の検索結果

Security audit, hardening, threat modeling (STRIDE/PASTA), Red/Blue Team, OWASP checks, code review, incident response, and infrastructure security for any project.

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。

Security audit, hardening, threat modeling (STRIDE/PASTA), Red/Blue Team, OWASP checks, code review, incident response, and infrastructure security for any project.

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。

Audit codebases, infrastructure, AND agentic AI systems for security issues. Covers traditional security (dependencies, secrets, OWASP web top 10, SSL/TLS, file permissions) PLUS agentic security (prompt injection scanning, identity spoofing detection, memory poisoning checks, multi-agent communication audit, OWASP Agentic Top 10). Use when scanning for vulnerabilities, detecting hardcoded secrets, reviewing agent workspace configuration, checking prompt injection vectors, or auditing agent permissions and boundaries.

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。

Hardens .NET apps per OWASP Top 10 -- injection, auth, XSS, deprecated security APIs.

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。

Security hardening and best practices for .NET applications. Navigation skill covering OWASP Top 10, authentication, authorization, cryptography, secrets management, and secure coding. For building secure applications. Keywords: security, owasp, authentication, authorization, cryptography, jwt, oauth, secrets, hardening

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。

Tests APIs for excessive data exposure where endpoints return more data than the client application needs, relying on the frontend to filter sensitive fields. The tester intercepts API responses and analyzes them for leaked PII, internal identifiers, debug information, or sensitive business data that the UI does not display but the API transmits. This maps to OWASP API3:2023 Broken Object Property Level Authorization. Activates for requests involving API data leakage testing, excessive data exposure, response filtering bypass, or API over-fetching.

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。

Tests APIs for Broken Function Level Authorization (BFLA) vulnerabilities where regular users can invoke administrative functions or access privileged API endpoints by directly calling them. The tester identifies admin and privileged endpoints, then attempts to access them with regular user credentials by manipulating HTTP methods, URL paths, and request parameters. Maps to OWASP API5:2023 Broken Function Level Authorization. Activates for requests involving BFLA testing, admin endpoint bypass, function-level access control testing, or API privilege escalation.

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。

Identifies and exploits insecure local data storage vulnerabilities in Android and iOS mobile applications including unencrypted databases, world-readable files, insecure SharedPreferences, plaintext credential storage, and improper keychain/keystore usage. Use when performing mobile penetration testing focused on OWASP M9 (Insecure Data Storage) or assessing compliance with MASVS-STORAGE requirements. Activates for requests involving mobile data storage security, local storage exploitation, SharedPreferences analysis, or mobile data leakage assessment.

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。

Tests APIs for injection vulnerabilities including SQL injection, NoSQL injection, OS command injection, LDAP injection, and Server-Side Request Forgery (SSRF) through API parameters, headers, and request bodies. The tester crafts malicious payloads targeting different backend technologies and injection contexts to extract data, execute commands, or access internal services. Maps to OWASP API8:2023 Security Misconfiguration and API7:2023 SSRF. Activates for requests involving API injection testing, SQLi in APIs, NoSQL injection, SSRF testing, or API input validation assessment.

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。

Detect and test for OWASP API3:2023 Broken Object Property Level Authorization vulnerabilities including excessive data exposure and mass assignment attacks.

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。

Detects prompt injection attacks targeting LLM-based applications using a multi-layered defense combining regex pattern matching for known attack signatures, heuristic scoring for structural anomalies, and transformer-based classification with DeBERTa models. The detector analyzes user inputs before they reach the LLM, flagging direct injections (system prompt overrides, role-play escapes, instruction hijacking) and indirect injections (encoded payloads, multi-language obfuscation, delimiter-based escapes). Based on the OWASP LLM Top 10 (LLM01:2025 Prompt Injection) and Simon Willison's prompt injection taxonomy. Activates for requests involving prompt injection detection, LLM input sanitization, AI security scanning, or prompt attack classification.

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。

Conducts security testing of REST, GraphQL, and gRPC APIs to identify vulnerabilities in authentication, authorization, rate limiting, input validation, and business logic. The tester uses the OWASP API Security Top 10 as the testing framework, combining Burp Suite interception with Postman collections and custom scripts to test endpoint security at every privilege level. Activates for requests involving API security testing, REST API pentest, GraphQL security assessment, or API vulnerability testing.

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。

JavaのSpring Bootサービスで、認証やアクセス権、入力検証などの安全対策を見直すスキル。秘密情報の管理からAPIの呼び出し制限、依存関係まで確認します。

• 認証とアクセス権を追加したいとき
• APIの入力検証とSQLを見直したいとき
• CSRFやCORSの設定確認

Quarkusサービスの変更後や公開前に、ビルド、コード解析、テスト、脆弱性検査を順に確認するスキル。ネイティブ実行形式やコンテナ、環境設定の検証も扱います。

• QuarkusのPR前チェック
• リファクタリングや依存更新の検証
• ネイティブ実行形式の互換性確認

許可されたWebアプリを対象に、公開ページの調査から脆弱性の再現確認まで進め、証拠・影響・修正案をまとめたセキュリティ報告書を作るスキル。

• ステージングの脆弱性を調べたいとき
• 疑わしい脆弱性を再現確認したいとき
• 証拠と修正案を報告書にまとめたいとき

Hardens code against vulnerabilities. Use when auditing an input handler for vulnerabilities, when handling user input, authentication, data storage, or external integrations, or when checking a login flow is safe against the OWASP Top Ten. Use when building any feature that accepts untrusted data, manages user sessions, or interacts with third-party services. Use when auditing dependencies for known vulnerabilities, triaging package-manager audit findings, or assessing supply-chain risk in a new package. Use when personal data or privacy compliance (GDPR, CCPA) is involved.

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。

Pentest a web app, API, codebase, repository, URL, domain, or IP with Strix — autonomous AI penetration testing that exploits and proves vulnerabilities (OWASP Top 10 and beyond — injection, XSS, SSRF, auth/access-control flaws, IDOR, business logic) instead of just flagging them. Runs self-hosted with the open-source CLI or via the managed app.strix.ai cloud, and returns validated findings with proof-of-concept exploits (Markdown, JSON, CSV, SARIF). Use when the user asks to pentest, hack, security-scan, security-audit, or find vulnerabilities in an app, API, website, or repo.

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。

Security-test a REST, GraphQL, or gRPC API with Strix — autonomous agents that enumerate endpoints from an OpenAPI/GraphQL schema (or by crawling), then actually exploit the API-specific vulnerability classes in the OWASP API Security Top 10 (2023) — broken object-level authorization (BOLA/IDOR), broken object property level authorization (excessive data exposure and mass assignment), broken function-level authorization, unrestricted resource consumption, SSRF, injection, and auth/token flaws. Every finding comes with a working proof-of-concept request. Use when the user asks to pentest, security-test, audit, or find vulnerabilities in an API, endpoint, or backend service.

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。

固件 / IoT 渗透链。从拿到一坨 .bin / .img 开始，闭环走完逆向 → 提取 → 模拟 → 利用。 方法论遵循 OWASP FSTM 九阶段；工具链以 binwalk v3、unblob、EMBA、Firmadyne、AFL++ 为主。 适用场景：路由器/摄像头/智能家居固件审计、固件升级包逆向、IoT CVE 复现、嵌入式 0day 挖掘。 触发关键词：固件、firmware、IoT、binwalk、unblob、UART、JTAG、squashfs、UBI、JFFS2、Firmadyne、QEMU 全系统仿真、EMBA、固件渗透、路由器固件、嵌入式漏洞利用、bootloader、NVRAM、FAT、firmware analysis toolkit。

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。

Detects and prevents code injection attacks targeting serverless functions (AWS Lambda, Azure Functions, Google Cloud Functions) through event source poisoning, malicious layer injection, runtime command execution, and IAM privilege escalation via function modification. The analyst combines static analysis of function code, CloudTrail event correlation, runtime behavior monitoring, and IAM policy auditing to identify injection vectors across the expanded serverless attack surface including API Gateway, S3, SQS, DynamoDB Streams, and CloudWatch event triggers. Activates for requests involving Lambda security assessment, serverless injection detection, function event poisoning analysis, or serverless privilege escalation investigation.

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。

Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app investigation.

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。

Analyze WAF (ModSecurity/AWS WAF/Cloudflare) logs to detect SQL injection attack campaigns. Parses ModSecurity audit logs and JSON WAF event logs to identify SQLi patterns (UNION SELECT, OR 1=1, SLEEP(), BENCHMARK()), tracks attack sources, correlates multi-stage injection attempts, and generates incident reports with OWASP classification.

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。

Detect and prevent dependency confusion (public-over-private package name resolution) in npm, PyPI, and Maven by enumerating claimable internal package names with tools like `confused` and OWASP `dep-scan`, then enforcing source restrictions via `.npmrc`, `pip.conf`/`pyproject.toml`, and Maven `settings.xml`. Use when onboarding a repo to a supply-chain security program, auditing lockfiles/manifests for confusable dependencies, or after an incident that may have leaked internal package names.

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。

Detect and defend against indirect prompt injection hidden in web pages, documents, and images consumed by an agent, via content extraction (HTML/PDF/OCR), normalization, and scanning with LLM Guard's PromptInjection scanner or Hugging Face Prompt Guard 2. Use when an agent ingests untrusted external content and you need to screen it for injected instructions before the LLM processes it.

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。