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تعداد دوره های برگزار شده : 4 دوره
سطح دوره
میانی
نام مدرک
SIEM with Tactical Analytics
مدت دوره
40 ساعت
پیشنیاز
بازرس قانونی جرایم رایانه ای
توضیحات دوره
پیش نیاز
مخاطبین
سرفصل دوره

در این دوره افراد با ساختار و معماری SIEM آشنا می شوند و با تجزیه  تحلیل داده هایی که به عنوان ورودی به SIEMهای ارسال می گردند و SIEMهای مختلف مانند Splunk , EIK , Tripwiveبررسی می شوند.


پیش نیاز دوره
  • بازرس قانونی جرایم رایانه ای
  • مانیتورینگ و پالایش ترافیک شبکه
مخاطبین دوره
  • تجزیه و تحلیل Log
  • کارشناسان SOC

سرفصل دوره

Section1: SIEM Architecture

  • State of the SOC/SIEM
  • Industry statistics
  • Industry problems
  • Log Monitoring
  • Assets
  • Windows/Linux
  • Network devices
  • Security devices
  • Data gathering strategies
  • Pre-planning
  • Logging architecture
  • Log inconsistencies
  • Log collection and normalization
  • Log retention strategies
  • Correlation and gaining context
  • Reporting and analytics
  • Alerting
  • SIEM platforms
  • Commercial solutions
  • Home-grown solutions
  • Planning a SIEM
  • Ingestion control
  • What to collect
  • Mission
  • SIEM Architecture
  • Ingestion techniques and nodes
  • Acceptance and manipulation for value
  • Augmentation of logs for detection
  • Data queuing and resiliency
  • Storage and speed
  • Analytical reporting
  • Visualizations
  • Detection Dashboards

Section 2: Service Profiling with SIEM

  • Detection methods and relevance to log analysis
  • Attacker patterns
  • Attacker behaviors
  • Abnormalities
  • Analyzing common application logs that generate tremendous amounts of data
  • DNS
  • Finding new domains being accessed
  • Pulling in addition information such as domain age
  • Finding randomly named domains
  • Discover domain shadowing techniques
  • Identifying recon
  • Find DNS C2 channels
  • HTTP
  • Use large datasets to find attacks
  • Identify bot traffic hiding in the clear
  • Discover requests that users do not make
  • Find ways to filter out legitimate noise
  • Use attacker randomness against them
  • Identify automated activity vs user activity
  • Filter approved web clients vs unauthorized
  • Find HTTP C2 channels
  • HTTPS
  • Alter information for large scale analysis
  • Analyze certificate fields to identify attack vectors
  • Track certificate validity
  • Apply techniques that overlap with standard HTTP
  • Find HTTPS C2 channels
  • SMTP
  • Identify where unauthorized email is coming from
  • Find compromised mail services
  • Fuzzy matching likely phishing domains
  • Data exfiltration detection
  • Apply threat intelligence to generic network logs
  • Active Dashboards and Visualizations
  • Correlate network datasets
  • Build frequency analysis tables
  • Establish network baseline activity

Section 3: Advanced Endpoint Analytics

  • Endpoint logs
  • Understanding value
  • Methods of collection
  • Agents
  • Agentless
  • Scripting
  • Adding additional logging
  • EMET
  • Sysmon
  • Group Policy
  • Windows filtering and tuning
  • Analyze critical events based on attacker patterns
  • Finding signs of exploitation
  • Find signs of internal reconnaissance
  • Finding persistence
  • Privilege escalation
  • Establishing a foothold
  • Cleaning up tracks
  • Host-based firewall logs
  • Discover internal pivoting
  • Identify unauthorized listening executables
  • See scan activity
  • Credential theft and reuse
  • Multiple failed logons
  • Unauthorized account use
  • Monitor PowerShell
  • Configure PowerShell logging
  • Identify obfuscation
  • Identify modern attacks

Section 4: Baselining and User Behavior Monitoring

  • Identify authorized and unauthorized assets
  • Active asset discovery
  • Scanners
  • Network Access Control
  • Passive asset discovery
  • DHCP
  • Network listeners such as p0f, bro, and prads
  • NetFlow
  • Switch CAM tables
  • Combining asset inventory into a master list
  • Adding contextual information
  • Vulnerability data
  • Authenticated device vs unauthenticated device
  • Identify authorized and unauthorized software
  • Source collection
  • Asset inventory systems
  • Patching management
  • Whitelisting solutions
  • Process monitoring
  • Discovering unauthorized software
  • Baseline data
  • Network data (from netflow, firewalls, etc)
  • Use outbound flows to discover unauthorized use or assets
  • Compare expected inbound/outbound protocol
  • Find persistence and beaconing
  • Utilize geolocation and reverse dns lookups
  • Establish device-to-device relationships
  • Identify lateral movement
  • Configure outbound communication thresholds
  • Monitor logons based on patterns
  • Time-based
  • Concurrency of logons
  • # logons by user
  • # logons by source device
  • Multiple geo locations
  • Endpoint baseline monitoring
  • Configure enterprise wide baseline collection
  • Large scale persistence monitoring
  • Finding abnormal local user accounts
  • Discover dual-homed devices

Section 5: Tactical SIEM Detection and Post-Mortem Analysis

  • Centralize NIDS and HIDS alerts
  • Analyze endpoint security logs
  • Provide alternative analysis methods
  • Configure tagging to facilitate better reporting
  • Augment intrusion detection alerts
  • Extract CVE, OSVDB, etc for further context
  • Pull in rule info and other info such as geo
  • Analyze vulnerability information
  • Setup vulnerability reports
  • Correlate CVE, OSVDB, and other unique IDs with IDS alerts
  • Prioritize IDS alerts based on vulnerability context
  • Correlate malware sandbox logs with other systems to identify victims across enterprise
  • Monitor Firewall Activity
  • Identify scanning activity on inbound denies
  • Apply auto response based on alerts
  • Find unexpected outbound traffic
  • Find unexpected outbound traffic
  • Baseline allow/denies to identify unexpected changes
  • Apply techniques to filter out noise in denied traffic
  • SIEM tripwires
  • Configure systems to generate early log alerts after compromise
  • Identify file and folder scan activity
  • Identify user token stealing
  • Operationalize virtual honeypots with central logging
  • Allow phone home tracking
  • Post mortem analysis
  • Re-analyze network traffic
  • Identify malicious domains and IPs
  • Look for beaconing activity
  • Identify unusual time-based activity
  • Use threat intel to reassess previous data fields such as user-agents
  • Utilize hashes in log to constantly re-evaluate for known bad files
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