Results for “tension-hunting”

Hunt for spearphishing campaign indicators across email logs, endpoint telemetry, and network data to detect targeted email attacks.

Proactively hunts for Advanced Persistent Threat activity using hypothesis-driven searches across endpoint telemetry, network logs, and memory artifacts.

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

Hunt for adversary persistence and execution via Windows scheduled tasks by analyzing task creation events, suspicious task properties, and unusual execution patterns.

Proactively hunt for adversary abuse of legitimate system binaries (LOLBins) to execute malicious payloads while evading detection.

Hunt for web shell deployments on internet-facing servers by analyzing file creation in web directories, suspicious process spawning from web servers, and anomalous HTTP patterns.

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

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.

Proactively hunt for threats by analyzing IOCs, detecting behavioral anomalies in telemetry, and prioritizing signals mapped to MITRE ATT&CK.

Hunt for adversary abuse of legitimate cloud services for C2, data staging, and exfiltration across Azure, AWS, GCP, and SaaS platforms.

Expert guidance for proactive threat hunting. Use this when the user asks to "hunt" for threads, IOCs, or specific TTPs.

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

Identify command-and-control beaconing patterns in network traffic by applying statistical frequency analysis, jitter calculation, and coefficient of variation scoring to detect periodic callbacks from compromised endpoints.

Detect C2 beaconing patterns in network traffic using frequency analysis, jitter detection, and domain reputation to identify compromised endpoints communicating with adversary infrastructure.

Detect data staging activity before exfiltration by monitoring for archive creation with 7-Zip/RAR, unusual temp folder access, large file consolidation, and staging directory patterns via EDR and process telemetry.

Hunt for threats in Windows Event Logs using Chainsaw, a fast Rust-based forensic tool that runs Sigma rules, keyword searches, and artifact analysis offline.

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

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

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.

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.

Analyze network traffic, logs, and data flows to detect potential data exfiltration via DNS tunneling, cloud storage uploads, encrypted channels, and other indicators of compromise.