「threat」の検索結果

Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.

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。

Focused Signals scout for PostHog projects running A/B experiments. Watches running experiments for validity threats (sample ratio mismatch, multi-variant contamination, exposure stalls, mid-run flag mutations) and lifecycle drift (zombie experiments running long past their useful life, decided-but-still-running experiments, ended experiments whose flags still serve multiple variants). 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 — no dependencies on other skills.

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。

Hunt for adversary techniques in telemetry you are authorized to query. Hypothesis-driven, evidence-first, no live offensive operations.

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。

Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.

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。

Runtime security for agent skills — prevents state corruption, skill overwrite attacks, denial of service, and enforces provenance tracking and no-go repo management. Load as part of the secure-* skill sequence whenever an agent processes external content or writes to the skill store. Also load when the user asks to check for state corruption, prevent skill overwrite, manage no-go repos, check provenance, audit runtime security, detect DoS patterns, or protect the skill store. Covers Issues 6, 9, 10 from the agent security threat model: instruction hierarchy enforcement, state corruption and skill overwrite, and denial of service prevention.

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 checks for repository ingestion — scans repos for poisoned examples, dependency and supply-chain attacks, file/path traversal, format-based attacks, and enforces quarantine-before-commit. Load as part of the secure-* skill sequence whenever an agent reads, ingests, or learns from a GitHub repository. Also load when the user asks to check a repo for poisoned code, scan dependencies, verify supply chain safety, check for path traversal, scan repo files for attacks, or audit a repo before ingestion. Covers Issues 3, 4, 7, 8 from the agent security threat model: poisoned training data, dependency attacks, file/path attacks, and format-based 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。

Write a rigorous, decision-grade experiment spec — falsifiable hypothesis, primary metric, guardrails, randomisation unit, exposure definition, method (A/B, holdout, switchback, quasi-experiment, MAB), MDE/duration plan, peek policy, validity threats, and pre-committed decision rule. Platform-agnostic. Load when the user has a candidate experiment and needs to spec it before launch, or says "spec this experiment", "write the test plan", "design this A/B test", "what's the hypothesis", "how big a sample do we need", "how long should we run this", "define the metrics for this test", or when the experimentation orchestrator routes here.

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。

Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.

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 the user asks about CDL classes (A, B, C), endorsements (H, N, P, S, T, X), required for hazmat / passenger / school bus / tank / triple-trailer operations, what each class is permitted to operate, the TSA Security Threat Assessment for hazmat, and ELDT (Entry-Level Driver Training) requirements. Cite 49 CFR 383.

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。

Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.

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。

Framework-directable information security risk assessment. Identifies threats, evaluates likelihood/impact via a 3x3 matrix, maps findings to any compliance framework, and recommends risk treatment options with prioritization guidance.

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。

Enterprise-grade security vetting protocol for AI agent skills. Automated threat detection, quantified risk scoring, and zero-trust code analysis.

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。

Adopt a virtual Hedgehog exotic animal at animalhouse.ai. Curls up when threatened. Opens slowly. Literally a trust metaphor. Feeding every 6 hours. Common tier animal.

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。

Expert security auditor specializing in DevSecOps, comprehensive cybersecurity, and compliance frameworks. Masters vulnerability assessment, threat modeling, secure authentication (OAuth2/OIDC), OWASP standards, cloud security, and security automation. Handles DevSecOps integration, compliance (GDPR/HIPAA/SOC2), and incident response. Use PROACTIVELY for security audits, DevSecOps, or compliance implementation.

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。

Retroactively verify threat mitigations for a completed phase

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 process injection techniques (T1055) including classic DLL injection, process hollowing, and APC injection by analyzing Sysmon events for cross-process memory operations, remote thread creation, and anomalous DLL loading patterns.

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 suspicious PowerShell execution patterns including encoded commands, download cradles, AMSI bypass attempts, and constrained language mode evasion.

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 WMI event subscription persistence by analyzing Sysmon Event IDs 19, 20, and 21 for malicious EventFilter, EventConsumer, and FilterToConsumerBinding creation.

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 abuse of elevation control mechanisms including UAC bypass, sudo exploitation, and setuid/setgid manipulation by monitoring registry modifications, process elevation flags, and unusual parent-child process relationships.

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。

Red team engagement planning is the foundational phase that defines scope, objectives, rules of engagement (ROE), threat model selection, and operational timelines before any offensive testing begins.

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 OS credential dumping techniques targeting LSASS memory, SAM database, NTDS.dit, and cached credentials using EDR telemetry, Sysmon process access monitoring, and Windows security event correlation.

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 typosquatting attacks in npm and PyPI package registries by analyzing package name similarity using Levenshtein distance and other string metrics, examining publish date heuristics to identify recently created packages mimicking established ones, and flagging download count anomalies where suspicious packages have disproportionately low usage compared to their legitimate targets. The analyst queries the PyPI JSON API and npm registry API to gather package metadata for automated comparison. Activates for requests involving package typosquatting detection, dependency confusion analysis, malicious package identification, or software supply chain threat hunting in package registries.

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 Kerberoasting attacks by monitoring for anomalous Kerberos TGS requests targeting service accounts with SPNs for offline password cracking.

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 adversary lateral movement across networks using Splunk SPL queries against Windows authentication logs, SMB traffic, and remote service abuse.

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。