「anthropic」の検索結果

Parse Office 365 Unified Audit Logs via Microsoft Graph API to detect email forwarding rule creation, inbox delegation, suspicious OAuth app grants, and other indicators of account compromise.

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。

Investigate compromised Docker containers by analyzing images, layers, volumes, logs, and runtime artifacts to identify malicious activity and evidence.

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Analyzes malware C2 communication over HTTP, HTTPS, DNS, and custom protocols to reverse-engineer beacon patterns, command structures, data encoding, and infrastructure (primary servers, fallback domains, dead drops). Use after reverse engineering reveals network traffic needing protocol analysis or when building detection signatures for a framework like Cobalt Strike, Metasploit, or Sliver.

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。

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。

Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys) online or offline using SharpDPAPI, SharpChrome, Mimikatz, or Impacket's dpapi.py, including domain-wide decryption via the DPAPI backup key. Use during authorized red-team credential-access engagements after gaining a foothold or when triaging DPAPI blobs pulled from a host.

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 analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.

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 malicious Linux ELF binaries — botnets, cryptominers, ransomware, and rootkits targeting Linux servers, containers, and cloud infrastructure — through static analysis, dynamic tracing, and reverse engineering of x86_64 and ARM samples. Use when investigating Linux malware, triaging a suspicious ELF binary, assessing a compromised Linux server, or analyzing container-targeted malware.

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。

Analyzes network traffic generated by malware during sandbox execution or live incident response to identify C2 protocols, data exfiltration channels, payload downloads, and lateral movement patterns using Wireshark, Zeek, and Suricata. Activates for requests involving malware network analysis, C2 traffic decoding, malware PCAP analysis, or network-based malware 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。

Parse Chromium-based browser databases with Hindsight to extract and correlate browsing history, downloads, cookies, cached content, autofill data, saved passwords, and extensions from Chrome, Edge, Brave, Opera, and Vivaldi into a unified timeline (XLSX, JSON, or SQLite output). Use during incident response, insider-threat investigations, or criminal cases when you need to reconstruct a user's web activity from a browser profile.

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。

Reverse engineer Go-compiled malware in Ghidra by parsing Go buildinfo and pclntab structures, recovering stripped/obfuscated function names (e.g. via GoResolver), and extracting embedded module/dependency strings and types from Go binaries. Use when analyzing a Go-language malware sample, deobfuscating a garble-packed Go binary, or recovering function names and third-party dependencies from a stripped Go executable.

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。

Analyzes intrusion activity against the Lockheed Martin Cyber Kill Chain framework to identify which phases an adversary has completed, where defenses succeeded or failed, and what controls would have interrupted the attack at earlier phases. Use when conducting post-incident analysis, building prevention-focused security controls, or mapping detection gaps to kill chain phases. Activates for requests involving kill chain analysis, intrusion kill chain, attack phase mapping, or Lockheed Martin kill chain framework.

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Analyzes bootkit and advanced rootkit malware infecting the Master Boot Record (MBR), Volume Boot Record (VBR), or UEFI firmware for below-OS persistence, covering boot sector analysis, UEFI module inspection, and anti-rootkit detection. Use when compromise survives OS reinstallation or antivirus/EDR fails to detect malware despite clear infection signs.

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。

Parses Kubernetes API server audit logs (JSON lines) to detect exec-into-pod, secret access, RBAC modifications, privileged pod creation, and anonymous API access, and builds SIEM detection rules from the event patterns. Use when investigating a suspected cluster compromise, reconstructing what an attacker did through the API server, or writing Kubernetes-specific detection content. Keywords: audit policy, audit log, kube-apiserver, exec into pod, RBAC change, anonymous access, detection rules. Do not use for syscall-level detection inside a running container - use detecting-container-runtime-threats-with-falco. '

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。

Extract and analyze Cobalt Strike beacon configuration from PE files and memory dumps to identify C2 infrastructure, malleable profiles, and operator tradecraft.

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URLScan.io is a free service for scanning and analyzing suspicious URLs. It captures screenshots, DOM content, HTTP transactions, JavaScript behavior, and network connections of web pages in an isolat

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Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns. Uses the Python netflow library to decode flow records, builds traffic baselines, and applies statistical analysis to identify flows with abnormal byte counts, connection durations, and periodic timing 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。

Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations on authorized network segments.

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。

Perform static and symbolic analysis of Solidity smart contracts using Slither and Mythril to detect reentrancy, integer overflow, access control, and other vulnerability classes before deployment to Ethereum mainnet.

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 analyze covert communication channels used by malware, including DNS tunneling, ICMP exfiltration, steganographic HTTP, and other protocol abuse used for C2 and data exfiltration. Use when investigating suspicious DNS/ICMP/HTTP traffic patterns, hunting for hidden C2 channels in network captures, or attributing exfiltration traffic to a known tunneling toolset.

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 kernel-level rootkits in Linux memory dumps using Volatility3 linux plugins (check_syscall, lsmod, hidden_modules), rkhunter system scanning, and /proc vs /sys discrepancy analysis to identify hooked syscalls, hidden kernel modules, and tampered system structures.

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。

Performs Linux memory acquisition using LiME (Linux Memory Extractor) kernel module and analysis with Volatility 3 framework. Extracts process lists, network connections, bash history, loaded kernel modules, and injected code from Linux memory images. Use when performing incident response on compromised Linux systems.

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Analyzes malicious VBA macros embedded in Microsoft Office documents (Word, Excel, PowerPoint) to identify download cradles, payload execution, persistence mechanisms, and anti-analysis techniques. Uses olevba, oledump, and VBA deobfuscation to extract the attack chain. Activates for requests involving Office macro analysis, VBA malware investigation, maldoc analysis, or document-based threat examination.

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 the NTFS Master File Table ($MFT) with MFTECmd, analyzeMFT, and X-Ways Forensics to recover metadata and content of deleted files by examining MFT record entries, $LogFile, $UsnJrnl, and MFT slack space. Use when recovering evidence of deleted files, reconstructing NTFS file-system timelines, or detecting anti-forensic timestomping during a Windows forensic examination.

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Analyze Windows LNK shortcut files and Jump List artifacts with LECmd, JLECmd, and manual Shell Link Binary Format parsing to establish evidence of file access, program execution, and user activity that persists even after the target file is deleted. Use when investigating Windows user activity, reconstructing file-access or program-execution timelines, or examining recent/frequently-used file evidence in a forensic exam.

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。