「analysis」の検索結果

Detect AWS IAM privilege escalation paths using boto3 and Cloudsplaining policy analysis to identify overly permissive policies, dangerous permission combinations, and least-privilege violations

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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. Use for requests involving fileless threat detection, in-memory malware investigation, LOLBin abuse analysis, or WMI persistence examination.

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Conducts penetration testing of iOS and Android mobile applications following the OWASP Mobile Application Security Testing Guide (MASTG) to identify vulnerabilities in data storage, network communication, authentication, cryptography, and platform-specific security controls. The tester performs static analysis of application binaries, dynamic analysis at runtime, and API security testing to evaluate the complete mobile attack surface. Activates for requests involving mobile app pentest, iOS security assessment, Android security testing, or OWASP MASTG assessment.

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Deploys anomaly detection for OT/ICS environments using machine learning on OT network baselines, physics-based process models, and Modbus/DNP3/OPC UA traffic analysis to flag deviations, rogue devices, and mismatches against historian data. Use for continuous OT monitoring, baselining deterministic SCADA polling, or investigating alerts from Nozomi Guardian/Dragos needing deeper protocol analysis.

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Conduct a defensible cybersecurity risk assessment using the NIST SP 800-30 Rev 1 methodology: prepare scope and a risk model, identify threat sources and threat events, identify vulnerabilities and predisposing conditions, determine likelihood and impact, compute risk, and communicate results as a prioritized risk register. Use when an organization needs an actual risk *assessment* (not a maturity score), when a control framework (CSF, ISO 27001, RMF, SOC 2, PCI) requires a documented risk analysis as input, when leadership asks "what are our top risks and how bad are they", when assessing risk for a new system or major change, or when building a risk register from scratch. This is the methodology that feeds framework selection, ATO packages, and treatment decisions. Keywords: risk assessment, NIST 800-30, threat modeling, likelihood and impact, risk register, risk analysis, threat sources, vulnerabilities, risk determination, qualitative risk, risk matrix, residual risk, risk treatment.

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Respond to malware infections across enterprise endpoints by identifying the malware family, determining infection vectors, assessing spread, and executing containment, analysis, eradication, and recovery procedures aligned to MITRE ATT&CK. Use when responding to a confirmed or suspected malware infection, including trojan/worm/ransomware outbreaks, malware triage, or infected endpoint remediation.

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Examine NTFS slack space, MFT entries, the USN Change Journal, and Alternate Data Streams (ADS) to recover hidden or residual data, reconstruct deleted-file metadata, and reconstruct available file-system change activity from USN records. Use during deep forensic analysis of an NTFS image when standard file recovery is insufficient, such as hunting for data hidden in ADS.

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Identifies and unpacks UPX-packed malware samples, including binaries with modified UPX magic bytes or headers that block automated decompression, to recover the original executable for static analysis. Use when a sample shows high entropy, minimal imports, or only LoadLibrary/GetProcAddress in its import table, or when preparing a packed binary for disassembly in Ghidra or IDA.

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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.

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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.

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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.

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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.

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Perform static analysis of Android APK malware using apktool for resource decompilation, jadx for Java source recovery, and androguard for manifest inspection, dangerous permission-combination detection, and identification of obfuscated code, dynamic code loading, and reflection-based API calls. Use to statically triage a suspicious APK without executing it or to build mobile malware detection rules.

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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.

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Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP consistency, malware code similarity, and timing/language artifacts into confidence-weighted attribution assessments. Use when an incident investigation needs a defensible attribution confidence level.

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Query ATT&CK data with attackcti, mitreattack-python, and stix2, then build MITRE ATT&CK Navigator layers and multi-layer heatmap overlays mapping one or more APT groups' TTPs for detection-gap analysis. Use to compare threat-actor technique coverage, find gaps in detection engineering, or produce Navigator visualizations for threat-intel reporting.

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Analyzes RAM memory dumps from compromised systems using the Volatility framework to identify malicious processes, injected code, network connections, loaded modules, and extracted credentials. Supports Windows, Linux, and macOS memory forensics. Activates for requests involving memory forensics, RAM analysis, volatile data examination, process injection detection, or memory-resident malware investigation.

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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.

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Parse and analyze email headers (Received chain, Return-Path, Message-ID) to trace the true origin of a phishing email and validate SPF, DKIM, and DMARC results to confirm or rule out sender spoofing. Use when triaging a suspicious or reported email, investigating a phishing incident, or verifying whether a message's sender domain was spoofed.

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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.

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Strategic product leadership toolkit for Head of Product including OKR cascade generation, market analysis, vision setting, and team scaling. Use for strategic planning, goal alignment, competitive analysis, and organizational design.

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Deep research skill powered by NotebookLM MCP. Conducts structured multi-source research (market analysis, competitive intel, trend analysis, prospect research) using Google NotebookLM as the research engine, then delivers formatted briefs and optional studio artifacts (slides, audio podcasts, videos, infographics, reports, mind maps).

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Use this skill when the user wants to build a financial model — 3-statement model, DCF valuation, LBO, SaaS unit economics, sensitivity / scenario analysis, debt schedule, or fundraising projections — in Excel. Trigger on: 'financial model', '3-statement model', 'P&L + BS + CF', 'DCF', 'WACC', 'NPV', 'terminal value', 'LBO', 'debt schedule', 'cash sweep', 'MOIC', 'IRR / XIRR', 'sensitivity table', 'scenario analysis', 'ARR model', 'unit economics', 'CAC / LTV', 'cap table forecast'. Output is a single formula-driven .xlsx. This skill is a scene layer on top of officecli-xlsx — it inherits every xlsx v2 rule (4-color code, visual floor, number formats, cache-drift, Known Issues, Delivery Gate minimum cycle). DO NOT invoke for a simple budget tracker, CSV dump, or operational KPI sheet — route those to officecli-xlsx base.

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Everything In Its Right Place. The universal post-work organizer. After any significant work session, EIIRP runs a 7-phase audit: (1) inventory every output, (2) walk taxonomy to decide where each lands, (3) check schema-pack consistency against the brain's actual shape, (4) file enriched brain pages, (5) audit the skill graph for DRY+MECE, (6) verify resolvability, (7) report. Named after the Radiohead song. Nothing produced during significant work lives only in chat — knowledge becomes permanent, patterns become reusable. Also carries the always-on auto-fire gate: when >=500 words of structured analysis on a user-shared document is about to be delivered, file the brain page first, then deliver the analysis with the link in that same reply.

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