「net」の検索結果

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。

Testing WebSocket implementations for authentication bypass, cross-site hijacking, injection attacks, and insecure message handling during authorized security assessments.

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Identifying and exploiting Insecure Direct Object Reference vulnerabilities to access unauthorized resources by manipulating object identifiers in API requests and URLs.

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Tests and exploits deep link (URL scheme and App Link) vulnerabilities in Android and iOS mobile applications to identify unauthorized access, data injection, intent hijacking, and redirect manipulation. Use when assessing mobile app attack surface through custom URI schemes, Android App Links, iOS Universal Links, or intent-based navigation. Activates for requests involving deep link security testing, URL scheme exploitation, mobile intent abuse, or link hijacking.

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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.

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Detects and analyzes fileless malware that operates entirely in memory using PowerShell, WMI, .NET reflection, registry-resident payloads, and living-off-the-land binaries (LOLBins) without writing traditional executable files to disk. Activates for requests involving fileless threat detection, in-memory malware investigation, LOLBin abuse analysis, or WMI persistence examination.

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Detecting misconfigured Azure Storage accounts including publicly accessible blob containers, missing encryption settings, overly permissive SAS tokens, disabled logging, and network access violations using Azure CLI, PowerShell, and Microsoft Defender for Storage.

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Detect data exfiltration through DNS tunneling by analyzing query entropy, subdomain length, query volume, TXT record abuse, and response payload sizes using passive DNS monitoring.

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Detect anomalies in DNP3 (Distributed Network Protocol 3) communications used in SCADA systems by monitoring for unauthorized control commands, firmware update attempts, protocol violations, and deviations from baseline traffic patterns using deep packet inspection and machine learning approaches.

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Detects rootkit presence on compromised systems by identifying hidden processes, hooked system calls, modified kernel structures, hidden files, and covert network connections using memory forensics, cross-view detection, and integrity checking techniques. Activates for requests involving rootkit detection, hidden process discovery, kernel integrity checking, or system call hook analysis.

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Detect container escape attempts in real-time using Falco runtime security rules that monitor syscalls, file access, and privilege escalation.

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

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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.

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Detect cyber attacks targeting OT historian servers (OSIsoft PI, Ignition, Wonderware) that sit at the IT/OT boundary and serve as pivot points for lateral movement between enterprise and control networks, including data manipulation, unauthorized queries, and exploitation of historian-specific vulnerabilities.

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TLS 1.3 (RFC 8446) is the latest version of the Transport Layer Security protocol, providing significant improvements over TLS 1.2 in both security and performance. It reduces handshake latency to 1-R

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Detect unauthorized modifications to running containers by monitoring for binary execution drift, file system changes, and configuration deviations from the original container image.

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Detects command-and-control (C2) communications tunneled through DNS protocol including DNS tunneling tools (Iodine, dnscat2, dns2tcp, Cobalt Strike DNS beacon), domain generation algorithms (DGA), encoded payload delivery via TXT/CNAME records, and DNS beaconing patterns. Covers Shannon entropy analysis of query subdomains, statistical anomaly detection, ML-based DGA classification, passive DNS correlation, and Zeek/Suricata signature development. Activates for requests involving DNS-based C2 detection, DNS tunnel identification, suspicious DNS traffic investigation, or DGA domain classification.

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

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Detects and analyzes Bluetooth Low Energy (BLE) security attacks including sniffing, replay attacks, GATT enumeration abuse, and Man-in-the-Middle interception. Uses Ubertooth One and nRF52840 sniffers for packet capture, the bleak Python library for GATT service enumeration, and crackle for BLE encryption cracking. Use when assessing IoT device BLE security, monitoring for BLE-based attacks on wireless infrastructure, or performing authorized BLE penetration testing. Activates for requests involving BLE security assessment, Ubertooth sniffing, GATT enumeration, or BLE replay detection.

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Performs statistical analysis of Zeek conn.log connection intervals to detect C2 beaconing patterns. Uses the ZAT library to load Zeek logs into Pandas DataFrames, calculates inter-arrival time standard deviation, and flags periodic connections with low jitter. Use when hunting for command-and-control callbacks in network data.

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Correlates security events in IBM QRadar SIEM using AQL (Ariel Query Language), custom rules, building blocks, and offense management to detect multi-stage attacks across network, endpoint, and application log sources. Use when SOC analysts need to investigate QRadar offenses, build correlation rules, or tune detection logic for reducing false positives.

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Configuring Zscaler Private Access (ZPA) to replace traditional VPN with zero trust network access by deploying App Connectors, defining application segments, configuring access policies based on user identity and device posture, and integrating with IdPs.

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Container escape is a critical attack technique where an adversary breaks out of container isolation to access the host system or other containers. Detection involves monitoring for escape indicators

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Configures Microsoft Defender for Endpoint (MDE) advanced protection settings including attack surface reduction rules, controlled folder access, network protection, and exploit protection. Use when hardening Windows endpoints beyond default Defender settings, deploying enterprise-grade endpoint protection, or meeting compliance requirements for advanced malware defense. Activates for requests involving Windows Defender configuration, ASR rules, MDE tuning, or Microsoft endpoint security.

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。