'detection' 검색 결과

Collect indicators of compromise, technical clues such as suspicious domains and file hashes, from incident evidence. Add context and confidence scores, then prepare them for detection, blocking, and structured sharing with partners.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Extracting threat indicators from incident evidence
• Adding threat context and confidence scores to indicators
• Preparing indicator lists for detection and blocking

Assess forced authentication and NTLM relay, the forwarding of authentication to another service, in authorized Windows environments. Use Coercer and PetitPotam to document exposed methods and check detection coverage, signing requirements, and Extended Protection for Authentication safeguards.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Assessing exposed forced authentication methods
• Validating NTLM relay risks in authorized environments
• Generating activity to tune security detections

Build dashboards and reports for security operations teams using incident and alert data. Track detection and resolution times, false alarms, analyst workload, and detection coverage to assess operational trends and the effects of improvement initiatives.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing monthly or quarterly security operations reports
• Reviewing analyst workload and shift staffing
• Comparing performance before and after tool adoption

Plan and run authorized security exercises that simulate an attacker's actions, from reconnaissance to activities after entry. Map techniques to MITRE ATT&CK, a framework of attack behaviors, and report detection gaps and response performance.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning the scope and objectives of a red team exercise
• Designing scenarios based on a specific threat actor
• Measuring detection and response during an exercise

Set up Microsoft Sentinel to collect security logs from AWS, Azure, and GCP. Build detection queries, investigate historical activity, and create automated response workflows for a centralized security operations team.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Centralizing security monitoring across multiple clouds
• Migrating from an existing SIEM platform
• Automating responses to suspicious cloud activity

Support authorized Active Directory assessments of DCSync, which abuses directory replication rights to obtain credential data. Cover replication permission review, Golden Ticket persistence testing, detection validation, and documentation of evidence and remediation recommendations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing accounts with directory replication rights
• Testing DCSync risks in an authorized lab
• Validating detection of replication abuse and forged tickets

Analyze Windows event logs in Splunk to investigate suspicious logins, privilege changes, persistence, and movement between computers. Build detection searches and organize endpoint activity into timelines, with findings linked to MITRE ATT&CK attack techniques.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating suspicious Windows logins
• Building detection searches in Splunk
• Creating incident timelines

Investigate security incidents in Splunk by connecting authentication, endpoint, and network logs. Use SPL, Splunk’s search language, to identify suspicious activity, reconstruct event timelines, document findings, and develop detection rules.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating suspicious logins across multiple log sources
• Reconstructing an incident timeline
• Tracing suspicious processes and outbound traffic

Search public TLS certificate records through crt.sh and pycrtsh to investigate lookalike domains, unexpected certificate issuers, and untracked IT assets. Compare domain spellings and review certificate details to support phishing detection and certificate monitoring.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding domains that imitate a brand
• Reviewing unexpected certificate issuers
• Investigating untracked domains and IT assets

Research malware families through Malpedia, connecting aliases, associated threat groups, and relationships between malware that loads other malware. Collect YARA rules, patterns used to identify malware, and organize references to support investigations and detection work.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Resolving different vendor names for the same malware
• Mapping malware associated with a threat group
• Documenting chains in which malware loads other malware

Analyze malware communication with command servers to understand periodic check-ins, message formats, encoded data, and backup destinations. Produces a structured analysis report and network detection rules based on captured traffic and malware code.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating malware communication in captured traffic
• Measuring periodic check-in intervals and timing variation
• Mapping command servers and backup destinations

Analyze DNS query logs for signs of hidden data transfers and attacker command channels. This skill uses unusual name lengths, randomness, and traffic volumes, then correlates findings with endpoint processes and estimates possible data loss.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating suspected data theft through DNS
• Finding algorithmically generated domains used by malware
• Reviewing hosts with unusually high DNS query volumes

Extract web page content as Markdown from a single URL or a site crawl. When access is blocked, progressively switch from basic fetching to Chrome and Bright Data proxy services, which route requests through other IP addresses.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Converting a single web page to Markdown
• Extracting content from JavaScript-rendered pages
• Retrieving pages blocked by bot detection

Read and display CARLA object bounding boxes, then project them onto a camera image as 2D rectangles. Export an annotated PNG and box coordinates in JSON for object detection annotation work.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding vehicle boxes to a camera image
• Exporting box coordinates for detection annotations
• Checking vehicle dimensions

Fine-tune vision models on custom images using Hugging Face Jobs cloud GPUs. Covers object detection, image classification, and segmentation—identifying image regions—with dataset validation, hardware selection, cost estimates, monitoring, and saving trained models to the Hub.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Train an object detector on custom images
• Fine-tune an image classifier
• Adapt SAM/SAM2 to custom image masks

Port an existing Semgrep rule to specified programming languages, producing separate rule and test files for each. The skill checks applicability, adapts detection patterns to each language, and reports validation results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Porting an existing rule to Go or Java
• Checking whether a detection pattern applies to another language
• Creating language-specific detection and safe-code tests

Review Windows privilege escalation paths from a standard user session to Administrator or SYSTEM. Examine service permissions, token privileges, library loading, scheduled tasks, and stored credentials, with detection indicators for defensive validation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating privilege escalation in authorized Windows assessments
• Reviewing service and scheduled task permissions
• Checking detection coverage with attack and defense teams

Plan persistence testing for authorized Windows and Linux security exercises, examining how access can survive logons or restarts. The skill compares mechanisms by privilege level and environment, with validation steps, detection indicators, and cleanup considerations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning persistence tests for authorized exercises
• Comparing methods by operating system and privilege
• Reviewing detection indicators for persistence

Review how evidence can be altered during authorized security exercises on Windows and Linux. Covers logs, timestamps, memory, disk records, and network traces, alongside the signs defenders use to detect manipulation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning authorized evidence manipulation tests
• Reviewing Windows and Linux forensic artifacts
• Checking detection coverage for altered evidence

Review lateral movement, the ways access spreads between systems, during authorized security tests. Covers credential reuse, remote execution, network tunnels, prerequisites, and the logs or defensive controls associated with each technique.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compare lateral movement methods for an internal penetration test
• Plan tunnels across segmented networks
• Review detection logs and controls for lateral movement

Adapt a C/C++ vulnerability pipeline to another language, target, or detection method. The workflow gathers requirements, proposes file changes for approval, updates the implementation, and validates it against a test target containing known bugs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adapt the pipeline for web application vulnerabilities
• Plan a port for smart contract auditing
• Change detection signals and report criteria

Routes security work to specialized guides for web and API testing, code review, threat intelligence, and incident response. Helps organize assessments from both attack and defense perspectives, including coordinated testing of detection capabilities.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning a web or API security assessment
• Reviewing code for potential vulnerabilities
• Organizing detection rules and incident response

Plan explicitly permitted credential testing, from preparing password candidates and usernames to choosing a login mode. Covers breach-frequency ranking, attempt pacing, success detection, audit logs, and conditions for stopping the test.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Assess whether credential testing is permitted and practical
• Prepare target-specific candidates and usernames
• Choose a mode for the login system

Develop literature reviews on AI for medical imaging, including segmentation, detection, and classification. Organize research from multiple sources into a structured manuscript with method comparisons, evaluation metrics, supporting citations, and limitations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Drafting literature reviews on medical imaging AI
• Comparing methods for segmentation, detection, and classification
• Combining literature from ArXiv, PubMed, and Zotero