What's on the bench.
Detecting Ransomware Precursors In Network
Detects early-stage ransomware indicators in network traffic before encryption begins, including initial access broker activity, command-and-control beaconing, credential harvesting, reconnaissance scanning, and staging behavior. Uses network detection tools (Zeek, Suricata, Arkime), SIEM correlation rules, and threat intelligence feeds to identify ransomware precursor patterns such as Cobalt Strike beacons, Mimikatz network signatures, and RDP brute-force attempts. Activates for requests involving pre-ransomware detection, network-based ransomware indicators, or early warning ransomware monitoring.
Detecting Ransomware Encryption Behavior
Detects ransomware encryption activity in real time using entropy analysis, file system I/O monitoring, and behavioral heuristics. Identifies mass file modification patterns, abnormal entropy spikes in written data, and suspicious process behavior characteristic of ransomware encryption routines. Activates for requests involving ransomware behavioral detection, entropy-based file monitoring, I/O anomaly detection, or real-time encryption activity alerting.
Detecting Qr Code Phishing With Email Security
Detect and prevent QR code phishing (quishing) attacks that bypass traditional email security by embedding malicious URLs in QR code images within emails.
Detecting Process Injection Techniques
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.
Detecting Process Hollowing Technique
Detect process hollowing (T1055.012) by analyzing memory-mapped sections, hollowed process indicators, and parent-child process anomalies in EDR telemetry.
Detecting Privilege Escalation In Kubernetes Pods
Detect and prevent privilege escalation in Kubernetes pods by monitoring security contexts, capabilities, and syscall patterns with Falco and OPA policies.
Detecting Port Scanning With Fail2ban
Configures Fail2ban with custom filters and actions to detect port scanning activity, SSH brute force attempts, and network reconnaissance, automatically banning offending IP addresses and alerting security teams to suspicious network probing.
Detecting Pass The Ticket Attacks
Detect Kerberos Pass-the-Ticket (PtT) attacks by analyzing Windows Event IDs 4768, 4769, and 4771 for anomalous ticket usage patterns in Splunk and Elastic SIEM
Detecting OAuth Token Theft
Detects and responds to OAuth token theft and replay attacks in cloud environments, focusing on Microsoft Entra ID (Azure AD) token protection, conditional access policies, and sign-in anomaly detection. Covers access token theft, refresh token replay, Primary Refresh Token (PRT) abuse, and pass-the-cookie attacks. Activates for requests involving OAuth token theft detection, token replay prevention, Azure AD conditional access token protection, or cloud identity attack investigation.
Detecting Ntlm Relay With Event Correlation
Detect NTLM relay attacks through Windows Security Event correlation by analyzing Event 4624 LogonType 3 for IP-to-hostname mismatches, identifying Responder/LLMNR poisoning artifacts, auditing SMB and LDAP signing enforcement across the domain, and detecting NTLM downgrade attacks from NTLMv2 to NTLMv1 using event log analysis.
Detecting Network Scanning With Ids Signatures
Detect network reconnaissance and port scanning using Suricata and Snort IDS signatures, threshold-based detection rules, and traffic anomaly analysis to identify Nmap, Masscan, and custom scanning activity.
Detecting Network Anomalies With Zeek
Deploys and configures Zeek (formerly Bro) network security monitor to passively analyze network traffic, generate structured logs, detect anomalous behavior, and create custom detection scripts for threat hunting and incident response.
Detecting Modbus Protocol Anomalies
This skill covers detecting anomalies in Modbus/TCP and Modbus RTU communications in industrial control systems. It addresses function code monitoring, register range validation, timing analysis, unauthorized client detection, and deep packet inspection for malformed Modbus frames. The skill leverages Zeek with Modbus protocol analyzers, Suricata IDS with OT rules, and custom Python-based detection using Markov chain models for normal Modbus transaction sequences.
Detecting Modbus Command Injection Attacks
Detect command injection attacks against Modbus TCP/RTU protocol in ICS environments by monitoring for unauthorized write operations, anomalous function codes, malformed frames, and deviations from established communication baselines using ICS-aware IDS and protocol deep packet inspection.
Detecting Mobile Malware Behavior
Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app investigation.
Detecting Misconfigured Azure Storage
Detecting misconfigured Azure Storage accounts including publicly accessible blob containers, missing encryption settings, overly permissive SAS tokens, disabled logging, and network access violations using Azure CLI, PowerShell, and Microsoft Defender for Storage.
Detecting Malicious Scheduled Tasks With Sysmon
Detect malicious scheduled task creation and modification using Sysmon Event IDs 1 (Process Create for schtasks.exe), 11 (File Create for task XML), and Windows Security Event 4698/4702. The analyst correlates task creation with suspicious parent processes, public directory paths, and encoded command arguments to identify persistence and lateral movement via scheduled tasks. Activates for requests involving scheduled task detection, Sysmon persistence hunting, or T1053.005 Scheduled Task/Job analysis.
Detecting Living Off The Land Attacks
Detect abuse of legitimate Windows binaries (LOLBins) used for living off the land attacks. Monitors process creation, command-line arguments, and parent-child relationships to identify suspicious LOLBin execution patterns.
Detecting Lateral Movement In Network
Identifies lateral movement techniques in enterprise networks by analyzing authentication logs, network flows, SMB traffic, and RDP sessions using Zeek, Velociraptor, and SIEM correlation rules to detect attackers moving between systems.
Detecting Insider Threat Behaviors
Detect insider threat behavioral indicators including unusual data access, off-hours activity, mass file downloads, privilege abuse, and resignation-correlated data theft.
Detecting Insider Data Exfiltration Via Dlp
Detects insider data exfiltration by analyzing DLP policy violations, file access patterns, upload volume anomalies, and off-hours activity in endpoint and cloud logs. Uses pandas for behavioral analytics and statistical baselines. Use when investigating insider threats or building user behavior analytics for data loss prevention.
Detecting Golden Ticket Forgery
Detect Kerberos Golden Ticket forgery by analyzing Windows Event ID 4769 for RC4 encryption downgrades (0x17), abnormal ticket lifetimes, and krbtgt account anomalies in Splunk and Elastic SIEM
Detecting Golden Ticket Attacks In Kerberos Logs
Detect Golden Ticket attacks in Active Directory by analyzing Kerberos TGT anomalies including mismatched encryption types, impossible ticket lifetimes, non-existent accounts, and forged PAC signatures in domain controller event logs.
Detecting Fileless Malware Techniques
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. Activates for requests involving fileless threat detection, in-memory malware investigation, LOLBin abuse analysis, or WMI persistence examination.