Results for “sigma-rules”

Guides blue-team threat hunting and detection engineering with hypothesis-driven workflows, Sigma/YARA rule creation, SIEM query design, and validation using Atomic Red Team in authorized environments.

Transform threat intelligence and attack patterns into testable hunting hypotheses for proactive threat detection.

Maps observed adversary behaviors, security alerts, and detection rules to MITRE ATT&CK techniques and sub-techniques to quantify detection coverage and guide control prioritization.

Detect Kerberoasting attacks by monitoring for anomalous Kerberos TGS requests targeting service accounts with SPNs for offline password cracking.

Detect suspicious PowerShell execution patterns including encoded commands, download cradles, AMSI bypass attempts, and constrained language mode evasion.

Hunt for supply chain compromise indicators including trojanized software updates, compromised dependencies, unauthorized code modifications, and tampered build artifacts.

Hunt for Mimikatz execution using command-line patterns, LSASS access signatures, binary indicators, and in-memory detection of known modules.

Hunt for registry-based persistence mechanisms including Run keys, Winlogon modifications, IFEO injection, and COM hijacking in Windows environments.

Detect insider threat behavioral indicators including unusual data access, off-hours activity, mass file downloads, privilege abuse, and resignation-correlated data theft.

Creates custom Semgrep rules for detecting security vulnerabilities, bug patterns, and code patterns with proper testing and validation.

Hunt for adversary persistence via Windows Scheduled Tasks by analyzing task creation events, suspicious task actions, and unusual scheduling patterns.

Generate siem rule generator operations. Auto-activating skill for Security Advanced. Triggers on: siem rule generator, siem rule generator Part of the Security Advanced skill category. Use when working with siem rule generator functionality. Trigger with phrases like "siem rule generator", "siem generator", "siem".

Apply GDPR-compliant engineering practices across your codebase, covering API design, data models, authentication, logging, retention, and cloud infrastructure.

Detect privilege escalation attempts including token manipulation, UAC bypass, unquoted service paths, kernel exploits, and sudo/doas abuse across Windows and Linux.

Systematically reduce SIEM false positives through rule tuning, threshold adjustment, correlation refinement, and threat intelligence enrichment to combat alert fatigue.

Design, implement, test, and maintain SIEM detection rules mapped to MITRE ATT&CK across Splunk, Elastic, and Sentinel platforms.

Reduce SIEM alert fatigue by systematically tuning detection rules in Splunk and Elastic, using statistical baselines, whitelists, and precision/recall metrics.

Hunt for unusual network connections by analyzing outbound traffic patterns, rare destinations, non-standard ports, and anomalous connection frequencies from endpoints.

Extract, parse, and analyze Windows Event Logs (EVTX) using Chainsaw, Hayabusa, and EvtxECmd to detect lateral movement, persistence, and privilege escalation.

Build collaborative forensic incident timelines using Timesketch to ingest, normalize, and analyze multi-source event data for attack chain reconstruction and investigation documentation.

Detect MITRE ATT&CK T1547.001 registry Run key persistence by analyzing Sysmon Event ID 13 logs and registry queries to identify malicious auto-start entries.

Executes Atomic Red Team tests mapped to MITRE ATT&CK techniques, performs coverage gap analysis, and runs detection validation loops to measure blue team visibility.

Facilitate structured post-incident reviews to identify root causes, document what worked and failed, and produce actionable recommendations to improve future incident response.

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.

Hunt for adversary abuse of Living Off the Land Binaries (LOLBins) by analyzing endpoint process creation logs for suspicious execution patterns of legitimate Windows system binaries used for malicious purposes.