「forensic」の検索結果

Forensic financial analysis for A-share fund holdings and portfolio companies. Adapts the original break-trace skill for fund administration context and Chinese market standards. Triggers on "基金持仓核查", "持仓异常", "forensic fund analysis China", "持仓质量分析", or "investigate [fund] holdings".

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 for authorized digital forensics including memory dumps, disk timelines, PCAP investigation, artifact triage, and IR evidence preservation.

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 a GSD run failed, stalled, or produced the wrong result and the cause is unclear. Reads git history and .planning/ state and phase artifacts to diagnose root cause, then writes a report to .planning/forensics/.

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。

Cross-agent self-inspection of your AI-agent stack. Audits skills, MCP servers, hooks, plugins, commands, credentials, and memory files across Claude Code, Codex, OpenClaw, and NanoClaw. Produces a structured inventory and narrative briefing with cross-ecosystem risk analysis. Use when the user asks to audit their own setup, check what they have installed, review their agent stack security posture, or understand cross-tool interactions. Use when a user has accumulated skills/plugins/MCP servers over time and wants visibility into their attack surface. Use after installing new skills or plugins. Do NOT use for vetting external code before install (that is repo-forensics). Do NOT use for incident response during active attacks. Do NOT use for fixing or patching vulnerabilities (forensify is read-only).

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 experiment integrity against the evidence ledger. At L2 (repo + result files present) a fresh cross-model reviewer reads the eval code line-by-line for fake/derived ground truth, score self-normalization, phantom results (a paper number with no backing file/key), dead/uncalled metric code, verified-scope inflation, method-described ≠ method-evaluated drift, synthesized-looking results, placeholder/fake data still wired into a released result, code-output ≠ reported-number mismatch, and missing reproducibility artifacts (an empirical/agent/LLM paper shipping neither code nor the prompts/configs its results need) — every finding span-anchored to a ledger claim_id. At L0/L1 (PDF / source only) the same patterns are surfaced as info-level 'could-not-verify' signals where the ledger gives an anchor (observability_level_required:2) — NEVER a fraud verdict from a PDF. The reviewer PROPOSES findings; tools/adjudicate_findings.py computes the verdict. Detect-only. Triggers: "experiment forensics", "audit the results", "check the eval code", "实验诚实度".

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。

Dispute resolution, forensic investigation, and risk assessment for autonomous AI agent transactions. Reconstruct provenance chains, adjudicate fault, generate actuarial risk profiles for agent insurance. The accountability layer of the Agent Trust Stack.

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。

Digital forensics techniques for detecting device compromise, analyzing malware indicators, and investigating targeted surveillance. Based on methodologies from Citizen Lab's Pegasus Project and Predator investigations.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for DFIR chronology, cross-artifact correlation, persistence chains, and incident timeline reconstruction. Use when the user asks to build a forensic timeline, correlate EVTX, PCAP, registry, disk, memory, mailbox, or browser artifacts, explain the order of attacker actions, or pinpoint the stage where the decisive artifact appears. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed 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。

Master memory forensics techniques including memory acquisition, process analysis, and artifact extraction using Volatility and related tools. Use when analyzing memory dumps, investigating incidents, or performing malware analysis from RAM captures.

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 forensic analysis of the macOS Unified Logging System (ULS) to investigate system events, application crashes, kernel panics, and potential indicators of compromise (IoCs) such as persistence mechanisms or unauthorized access.

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。

Memory forensics playbook using Volatility 2/3. Use when analyzing memory dumps for malware analysis, credential extraction, process investigation, code injection detection, and incident response timeline reconstruction.

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 a memory image with Volatility 3 to find malware: rogue processes, injected code, suspicious network connections, loaded modules, and persistence, then extracts artifacts for further analysis. Activates for requests to do memory forensics, analyze a RAM dump, or hunt malware in memory with Volatility.

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。

Digital forensics and incident response triage skill for disk, memory, network, cloud, and endpoint artifacts. Covers Volatility 3, Velociraptor, KAPE, Plaso, Autopsy, Chainsaw, Hayabusa, Zeek, Arkime, EVTX, AWS/Azure/GCP audit logs, and timeline reconstruction. Use to extract IOCs, build incident timelines, and produce defensible analyst reports.

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。

Conduct digital forensics investigations — evidence acquisition, timeline analysis, and court-ready documentation.

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 forensically auditing a Claude Code skill/agent/command/workflow library against RULESET.md by a fixed mechanical protocol — probing every file against the mechanically-checkable rules and reporting CONFORMS / VIOLATES / UNVERIFIABLE / N-A counts with quoted evidence. It casts NO judgment and emits NO pass/fail verdict; counts are the headline. Triggers on "investigate the library", "audit against RULESET", "find every violation", "forensic library audit", "evidence-only check". Not for routing/quality/single-responsibility judgment — use skill-library-review. Not the full sharded sweep — use the audit-library command.

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 a release review needs machine-derived evidence from git history — hotspot risk and change-coupling analyzers. Triggers on 'hotspot', 'what changes together', 'release forensics'.

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 process injection techniques used by malware including classic DLL injection, process hollowing, APC injection, thread hijacking, and reflective loading. Uses memory forensics, API monitoring, and behavioral analysis to identify injection artifacts. Activates for requests involving process injection detection, code injection analysis, hollowed process investigation, or in-memory threat 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。

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.

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 AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models. Supports batch analysis of audio files, generates confidence scores, and produces forensic reports. Activates for requests involving deepfake voice detection, vishing investigation, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.

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) to recover metadata and content of deleted files by examining MFT record entries, $LogFile, $UsnJrnl, and MFT slack space using MFTECmd, analyzeMFT, and X-Ways Forensics.

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 Windows Prefetch files to determine program execution history including run counts, timestamps, and referenced files for forensic 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。

Investigate USB device connection history from Windows registry, event logs, and setupapi logs to track removable media usage and potential data exfiltration.

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 captures and flow data to identify adversary activity during security incidents, including command-and-control communications, lateral movement, data exfiltration, and exploitation attempts. Uses Wireshark, Zeek, and NetFlow analysis techniques. Activates for requests involving network traffic analysis, packet capture investigation, PCAP analysis, network forensics, C2 traffic detection, or exfiltration 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。

Traces ransomware cryptocurrency payment flows using blockchain analysis tools such as Chainalysis Reactor, WalletExplorer, and blockchain.com APIs. Identifies wallet clusters, tracks fund movement through mixers and exchanges, and supports law enforcement attribution. Activates for requests involving ransomware payment tracing, bitcoin wallet analysis, cryptocurrency forensics, or blockchain intelligence gathering.

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。