149 件 ・ 関連度順
概要と使いどころ
Enable, record, query, summarize, or verify the opt-in PWDEV Flow semantic audit trail. Use when the user asks what Flow actions occurred, wants audit integrity checked, or needs a portable JSONL record of workflow gates and artifacts.
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医療アプリの患者・職員の機密情報を分類し、施設単位のアクセス制御や監査記録を設計するとともに、ログ・URL・ブラウザー保存からの情報漏えいを点検するスキル。
Audit trail register: timestamp, user, module, record, action, field changed, old and new value, and the reason for the change. Use for change history and control evidence.
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。
Respond to security incidents in AWS, Azure, and GCP via identity-based containment, cloud-native log analysis (CloudTrail, Azure Activity Logs, GCP Audit Logs), resource isolation, and forensic evidence acquisition adapted for ephemeral cloud infrastructure. Use when CSPM alerts or audit logs show compromised cloud credentials, unauthorized IAM changes, or a breach spanning cloud services.
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 abnormal access in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics for after-hours bulk downloads, new-IP access, and API-call spikes (e.g. GetObject) via statistical baselines and time-series anomaly detection. Use when investigating suspected cloud data exfiltration or building related detection rules.
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Detects missing zeroization of sensitive data in source code and identifies zeroization removed by compiler optimizations, with assembly-level analysis, and control-flow verification. Use for auditing C/C++/Rust code handling secrets, keys, passwords, or other sensitive data.
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。
Compares Trailmark code graphs at two source code snapshots (git commits, tags, or directories) to surface security-relevant structural changes. Detects new attack paths, complexity shifts, blast radius growth, taint propagation changes, and privilege boundary modifications that text diffs miss. Use when comparing code between commits or tags, analyzing structural evolution, detecting attack surface growth, reviewing what changed between audit snapshots, or finding security-relevant changes that text diffs miss.
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。
Understand a codebase before looking for bugs in it - what each function assumes, what it guarantees, and what it depends on elsewhere. Use when starting an audit, threat model, or architecture review on unfamiliar code, and before any vulnerability-hunting pass.
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。
Systematic code maturity assessment using Trail of Bits' 9-category framework. Analyzes codebase for arithmetic safety, auditing practices, access controls, complexity, decentralization, documentation, MEV risks, low-level code, and testing, then produces a scorecard with evidence-based ratings and a priority-ordered roadmap. Use when assessing or scoring the maturity of a smart contract or blockchain codebase, producing a maturity scorecard or evaluation, or judging how mature, well-tested, or well-documented such a project is against a rubric.
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。
Token integration and implementation analyzer based on Trail of Bits' token integration checklist. Analyzes token implementations for ERC20/ERC721 conformity, checks for 20+ weird token patterns, assesses contract composition and owner privileges, performs on-chain scarcity analysis, and evaluates how protocols handle non-standard tokens. Use when integrating or accepting arbitrary ERC20/ERC721 tokens, auditing a token implementation for standards conformity, or assessing risk from weird tokens such as fee-on-transfer, rebasing, missing return values, or blocklists.
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。
Systematic false positive verification for security findings. Provides structured methodology to confirm or dismiss scanner results, manual audit findings, and automated alerts. Adapted from Trail of Bits. Use when triaging security scan results or verifying audit findings.
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 trail register: timestamp, user, module, record, action, field changed, old and new value, and the reason for the change. Use for change history and control evidence.
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。
Guide for building a consent record-keeping system to demonstrate valid consent per GDPR Article 7(1). Covers required fields including timestamp, version, purpose, mechanism, and identity. Implements audit-ready consent receipts per the Kantara Initiative Consent Receipt Specification and supervisory authority expectations.
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。
Provides compliance, governance, and supply chain security guidance for cloud-native systems. Covers OPA Rego policies, Kyverno cluster policies, SBOM generation, SLSA provenance, audit trail design, and regulatory framework mapping. Use when user mentions 'compliance', 'governance', 'OPA', 'kyverno', 'SBOM', 'SLSA', 'audit', 'policy-as-code', 'SOC2', 'HIPAA', 'PCI-DSS', 'artifact signing'.
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, classify, and selectively forget stored memories. Covers memory enumeration and classification by type/age/access frequency, staleness detection for outdated references, fidelity checks using external anchors, a decision tree for selective withdrawal, tombstoned deaccession so removed content stays recoverable, counter-memory inoculation for failed strategies that would otherwise be re-derived, preemptive filtering rules for what should never become memories, and an audit trail so forgetting itself is reviewable. Use when memory has grown large and uncurated, when project state has shifted significantly since memories were written, when retrieval quality has degraded, or as periodic maintenance alongside manage-memory.
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Sets up safe working habits and a change log so you always know what Cowork has done to your files — and can undo anything. Use when setting up file protection guardrails, for establishing safe automation habits, during initial access configuration, when granting file permissions for the first time, or when the user says "is cowork safe", "file safety", "what if it deletes my files", "audit trail", "safety setup", "I'm nervous about file access", "how do I trust cowork with my files", "can cowork mess up my computer", "I heard someone lost files", or "how do I stay in control".
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。
Redact PII in your own code before it reaches Agentforce prompts, models, and logs. Trigger keywords: agentforce pii, pii redaction, data masking llm, prompt pii filter, audit pii leakage. NOT for turning on the platform's own masking, zero-retention and audit-trail controls — use agentforce/einstein-trust-layer. NOT for masking PII in a refreshed sandbox — use security/sandbox-data-masking.
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。
Use this skill when building or maintaining a Requirements Traceability Matrix (RTM) on a Salesforce project: one row per requirement, columns for source, user-story id(s), test-case id(s), defect id(s), sprint, release, and status. Covers forward traceability (req → story → code → test) and backward traceability (test → req). Trigger keywords: RTM, requirements traceability matrix, audit trail for salesforce delivery, traceability for steerco, deferred requirement tracking, regulatory traceability. NOT for eliciting the requirements in the first place — use admin/requirements-gathering-for-sf. NOT for user-story authoring — use admin/user-story-writing-for-salesforce. NOT for UAT test design — use admin/uat-test-case-design. NOT for Apex test design — use apex/test-class-standards. NOT for backlog prioritization — use admin/moscow-prioritization-for-sf-backlog. More triggers: traceability.md, build-layer traceability, REQ-XXX and FG-XXX id mapping, artefact-to-requirement orphan report, coverage-gap report, check_rtm.py --manifest-dir, owning run-time agent column, design decision ref column, metadata API name in a traceability row.
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。
Troubleshooting Connected App OAuth flows — IP relaxation vs IP restriction, refresh token policy traps (default kills the connection on first refresh), session-revocation semantics, the OAuth error-code catalog (`invalid_grant`, `invalid_client_id`, `unsupported_grant_type`), per-user vs admin-pre-approved flows, and the user-policy check (Connected App must be assigned to the user via profile / permset). Covers the Login History debug trail. NOT for designing the OAuth flow itself — use integration/oauth-flows-and-connected-apps. NOT for a SAML / SSO login failure — use security/sso-saml-troubleshooting. Trigger keywords: 'invalid_grant', 'OAUTH_APP_BLOCKED', 'redirect_uri_mismatch', 'LoginHistory Status', 'LoginSubType', 'OauthRefreshToken', 'ForwardedForIp', 'SetupAuditTrail connected app', 'refreshTokenPolicy zero', 'isSecretRequiredForRefreshToken', 'works once then fails', 'diagnosis record'.
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。
Detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API calls (GetObject spikes), and potential data exfiltration using statistical baselines and time-series anomaly detection.
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 trail register: timestamp, user, module, record, action, field changed, old and new value, and the reason for the change. Use for change history and control evidence.
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。
Use when working with Adobe Sign — adobe Acrobat Sign (formerly Adobe Sign) eSignature platform management covering agreements, templates, workflows, users, and audit trails. Use when monitoring agreement status, analyzing signing completion rates, reviewing workflow performance, managing Adobe Sign users, or auditing document signing activity.
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。