「sec」の検索結果

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。

Review source files changed during a phase for bugs, security issues, and code quality problems

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 SMB protocol vulnerabilities using Metasploit Framework during authorized penetration tests to demonstrate risks from unpatched Windows systems, misconfigured shares, and weak authentication in enterprise networks.

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。

Detecting and exploiting Server-Side Template Injection (SSTI) vulnerabilities across Jinja2, Twig, Freemarker, and other template engines to achieve remote code execution.

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。

Discover and exploit mass assignment vulnerabilities in REST APIs to escalate privileges, modify restricted fields, and bypass authorization controls by injecting unexpected parameters in API requests.

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。

Detecting and exploiting HTTP request smuggling vulnerabilities caused by Content-Length and Transfer-Encoding parsing discrepancies between front-end and back-end servers.

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。

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。

Executes comprehensive red team exercises that simulate real-world adversary operations against an organization's people, processes, and technology. The red team operates with stealth as a primary objective, employing the full attack lifecycle from initial reconnaissance through objective completion while testing the organization's detection and response capabilities. This differs from penetration testing by focusing on adversary emulation rather than vulnerability identification. Activates for requests involving red team exercise, adversary simulation, adversary emulation, or full-scope offensive security 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。

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 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。

Scans GitHub Actions workflows and CI/CD pipeline configurations for supply chain attack vectors including unpinned actions, script injection via expressions, dependency confusion, and secrets exposure. Uses PyGithub and YAML parsing for automated audit. Use when hardening CI/CD pipelines or investigating compromised build systems.

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 risky OAuth application consent grants in Azure AD / Microsoft Entra ID using Microsoft Graph API, audit logs, and permission analysis to identify illicit consent grant 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。

Detect unauthorized SaaS and cloud service usage (shadow IT) by analyzing proxy logs, DNS query logs, and netflow data using Python pandas for traffic pattern analysis and domain 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。

Discover and inventory shadow API endpoints that operate outside documented specifications using traffic analysis, code scanning, and API discovery platforms.

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。

This skill covers detecting sophisticated cyber-physical attacks that follow the Stuxnet attack pattern of modifying PLC logic while spoofing sensor readings to hide the manipulation from operators. It addresses PLC logic integrity monitoring, physics-based process anomaly detection, engineering workstation compromise indicators, USB-borne attack vectors, and multi-stage attack chain detection spanning IT-to-OT lateral movement through to process manipulation.

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 network reconnaissance and port scanning using Suricata and Snort IDS signatures, threshold-based detection rules, and traffic anomaly analysis to identify Nmap, Masscan, and custom scanning 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。

Detect command injection attacks against Modbus TCP/RTU protocol in ICS environments by monitoring for unauthorized write operations, anomalous function codes, malformed frames, and deviations from established communication baselines using ICS-aware IDS and protocol deep packet inspection.

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。

Detects early-stage ransomware indicators in network traffic before encryption begins, including initial access broker activity, command-and-control beaconing, credential harvesting, reconnaissance scanning, and staging behavior. Uses network detection tools (Zeek, Suricata, Arkime), SIEM correlation rules, and threat intelligence feeds to identify ransomware precursor patterns such as Cobalt Strike beacons, Mimikatz network signatures, and RDP brute-force attempts. Activates for requests involving pre-ransomware detection, network-based ransomware indicators, or early warning ransomware monitoring.

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 RDP brute force attacks by analyzing Windows Security Event Logs for failed authentication patterns (Event ID 4625), successful logons after failures (Event ID 4624), NLA failures, and source IP frequency 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。

This skill teaches security teams how to detect and respond to unauthorized cryptocurrency mining operations in cloud environments. It covers identifying cryptomining indicators through compute usage anomalies, network traffic patterns to mining pools, GuardDuty CryptoCurrency findings, and runtime process monitoring on EC2, ECS, EKS, and Azure Automation workloads.

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 Kerberos Pass-the-Ticket (PtT) attacks by analyzing Windows Event IDs 4768, 4769, and 4771 for anomalous ticket usage patterns in Splunk and Elastic SIEM

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 lateral movement techniques in enterprise networks by analyzing authentication logs, network flows, SMB traffic, and RDP sessions using Zeek, Velociraptor, and SIEM correlation rules to detect attackers moving between systems.

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。