Results for “network-anomaly-detection”

"Anomaly" covers three distinct problems, and a detector built for one is close to

Detect anomalies in DNP3 protocol communications used in SCADA systems by monitoring for unauthorized control commands, firmware update attempts, protocol violations, and deviations from baseline traffic patterns using deep packet inspection and machine learning approaches.

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

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.

Detects DNS tunneling by computing Shannon entropy of DNS query names, analyzing query length distributions, inspecting TXT record payloads, and identifying high subdomain cardinality using scapy for packet capture analysis.

Automates packet capture analysis using tshark and pyshark to extract protocol statistics, detect suspicious flows, identify IOCs, and analyze DNS anomalies from PCAP files.

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns using the Python netflow library.

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.

Analyze Zeek conn.log and NetFlow data to detect ransomware network indicators including C2 beaconing, TOR exit node connections, data exfiltration, and suspicious DNS patterns.

Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations on authorized network segments.

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

Detects anomalies in Modbus/TCP and Modbus RTU communications in industrial control systems using Zeek, Suricata, and custom Python analysis.

Detect and prevent ARP spoofing attacks using ARPWatch, Dynamic ARP Inspection, Wireshark analysis, and custom Python monitoring scripts to protect against man-in-the-middle interception.

Detect suspicious Windows service installations (MITRE ATT&CK T1543.003) by parsing System event logs for Event ID 7045, analyzing service binary paths, and identifying indicators of persistence mechanisms.

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.

Analyze Zeek network logs to detect lateral movement techniques including SMB admin share access, DCE/RPC remote service creation, NTLM account spray, Kerberos anomalies, and large internal data transfers.

Performs advanced network reconnaissance using Nmap's scripting engine, timing controls, evasion techniques, and output parsing to discover hosts, enumerate services, detect vulnerabilities, and fingerprint operating systems across authorized target networks.

Detects unusual options activity and classifies smart money signals to help follow institutional positioning, including volume/OI ratio spikes, block trades, sweep orders, and net premium flow.

Capture and analyze network traffic using Wireshark and tshark to reconstruct network events, extract artifacts, and identify malicious communications.

Detect NTLM relay attacks by analyzing Windows Event 4624 logon type 3 with NTLMSSP authentication, identifying IP-to-hostname mismatches, Responder traffic signatures, SMB signing status, and suspicious authentication patterns across the domain.

Analyze Zeek dns.log files to detect DNS-based data exfiltration by computing Shannon entropy, flagging long subdomain labels, and identifying anomalous query patterns.

Analyzes malware-generated network traffic from PCAP files to identify C2 protocols, data exfiltration, DNS tunneling, and beaconing patterns using Wireshark, Zeek, Suricata, and Python.

Detects command-and-control (C2) communications tunneled through DNS protocol, including DNS tunneling tools, domain generation algorithms, and encoded payload delivery via TXT/CNAME records.

Detect DNS tunneling and data exfiltration by analyzing Zeek dns.log for high-entropy subdomain queries, excessive query volume, long query lengths, and unusual DNS record types indicating covert channel communication.

Detect domain fronting C2 traffic by analyzing SNI vs HTTP Host header mismatches in proxy logs and TLS certificate discrepancies using pyOpenSSL for certificate inspection.

N+1 Query Detection and Resolution