Threat Hunting Tools
Proactive threat hunting tools for Indian cybersecurity professionals — from structured hunt planning and query libraries to lateral movement deep dives and insider threat detection. Turn reactive alert response into proactive threat discovery.
Hunt Planning
Hunt Plan Builder
Build a complete, structured hunt plan from a hypothesis. Generates hypothesis statement, data sources, indicators to look for, positive finding criteria, and escalation path.
Build hunt plan →Hunt Hypothesis Library
150+ structured hunt hypotheses organised by MITRE tactic. Each with rationale, required log sources, confidence level, and ready-to-adapt query. Filter by tactic, log source, and difficulty.
Browse hypotheses →Sigma Rule Converter
Paste any Sigma rule and convert it to SPL, KQL, or EQL instantly. Runs entirely client-side — your rules never leave your browser. Covers all common Sigma field mappings.
Convert rule →Query Libraries
SPL Hunt Query Library
60+ production-ready Splunk SPL hunt queries organised by MITRE technique. Required log sources, expected output volume, tuning guidance, and what a positive looks like.
Browse SPL queries →KQL Hunt Query Library
60+ Microsoft Sentinel and Defender Advanced Hunting KQL queries. Covers Windows endpoint, Azure AD, Office 365, and network telemetry with tuning notes.
Browse KQL queries →IOC to Hunt Query Converter
Paste a list of IOCs from any threat report. Get a complete SPL and KQL query searching for all of them across process, network, DNS, and file creation events simultaneously.
Convert IOCs →Statistical Hunting
Beacon Detection Calculator
C2 beacons have distinctive timing patterns. Understand the maths and get the exact SPL/KQL query that calculates connection interval statistics and flags beaconing behaviour across your network.
Hunt beacons →Long Tail Frequency Analyser
Find rare process executions, DNS queries, or network destinations that appear on only 1–2 hosts. Paste your data as CSV and get frequency distribution with statistical outlier flagging.
Analyse frequency →LOLBin Cluster Hunt
Individual LOLBin usage is noisy. Clusters of 3+ LOLBins from the same process in 15 minutes are near-uniquely malicious. Generate the cluster detection query for your SIEM.
Hunt clusters →Lateral Movement Deep Dives
Kerberos Attack Hunt Suite
Complete hunt suite for Kerberoasting, AS-REP Roasting, Pass-the-Ticket, and Golden/Silver Ticket attacks. SPL and KQL queries for each with what the data looks like when the attack fires.
Hunt Kerberos attacks →SMB Lateral Movement Hunt
Distinguish malicious SMB lateral movement from legitimate file sharing. Covers ADMIN$/C$ share abuse, PsExec patterns, PSEXESVC artefacts, and SMB named pipe hunting.
Hunt SMB movement →Lateral Movement Hunt Pack
WMI, DCOM, WinRM, RDP, token impersonation, and remote registry — every lateral movement technique with dedicated hunt queries, required audit settings, and what normal vs malicious looks like.
View hunt pack →Insider Threat Hunting
Insider Threat Hunt Pack
Off-hours activity, abnormal data access, bulk downloads, email forwarding rules, print and screenshot activity. Complete hunt pack for insider threat indicators with SPL and KQL queries.
View hunt pack →Data Staging & Exfil Hunt
Hunt for pre-exfiltration staging — large file copies to temp directories, ZIP creation of sensitive files, database exports, cloud storage uploads, DNS exfiltration, and email exfil patterns.
Hunt data staging →Ransomware Pre-Encryption Hunt
Catch ransomware operators before they encrypt. Hunt for shadow copy enumeration, network share discovery, credential dumping, backup server access, and mass file access patterns.
Hunt ransomware staging →Proactive threat hunting — finding what your alerts miss.
Threat hunting is the practice of proactively searching through an organisation's security data to detect threats that have evaded automated detection systems. Unlike reactive alert triage — which responds to what your SIEM has already flagged — threat hunting starts with a hypothesis about how an attacker might behave and then searches historical log data to find evidence of that behaviour. It is the difference between waiting for a fire alarm and periodically walking the building looking for smouldering wires.
Threat hunting matters particularly in the Indian context because the primary APT groups targeting India — Sidewinder, APT36, SideCopy — are known for long dwell times. Sidewinder campaigns have been observed maintaining access in target environments for months before their presence was detected. A reactive SOC that only responds to alerts will miss an attacker who has specifically engineered their activity to stay below detection thresholds. Proactive hunting based on knowledge of these groups' specific TTPs is how long-dwell compromises are discovered before they become data breaches.
The 15 threat hunting tools on this page support the full hunting workflow — from building a hypothesis grounded in threat intelligence, to generating the SIEM queries to test it, to documenting findings. They are designed for security professionals and threat hunters ready to invest time in proactive security rather than purely reactive operations.
Frequently asked questions — Threat Hunting
What is a threat hunting hypothesis?
A threat hunting hypothesis is a specific, testable statement about attacker behaviour that a hunter will search for in log data. A well-formed hypothesis follows this structure: "If [attacker technique] occurred in our environment, I would expect to see [specific observable evidence] in [specific log source]." For example: "If Kerberoasting occurred, I would expect to see Windows Event ID 4769 with EncryptionType 0x17 (RC4) requested from a non-service user account in the Security event log." The hypothesis determines exactly what to search for, making the hunt systematic rather than random.
When is a security team ready to start threat hunting?
Threat hunting requires two foundational prerequisites: adequate log coverage (you cannot hunt for what you cannot see in your data) and stable alert triage operations (a team drowning in alerts cannot spare analyst time for proactive hunting). A practical readiness indicator: if your SOC has 90-day log retention covering endpoints, network, and authentication events, and if your alert queue is consistently cleared within the same business day, you have the foundation for productive threat hunting. If logs are retained for only 30 days or alert backlogs run multiple days, investing in those foundations first will yield better returns than starting a hunting programme.
What is a Sigma rule and how does it relate to threat hunting?
Sigma is a vendor-neutral detection rule format. In the threat hunting context, Sigma rules serve two purposes. First, a successful hunt finding — where a hunter has manually identified a malicious pattern — is converted into a Sigma rule so that the same pattern can be detected automatically going forward. Second, community Sigma rules from repositories like SigmaHQ provide ready-made hunting hypotheses — each rule represents a detection that the community has validated as meaningful, which makes it a starting point for a structured hunt.
How do you measure the output of a threat hunting programme?
Threat hunt output metrics: number of confirmed threats discovered per hunt (true positive rate), number of new detection rules created from hunt findings (this is the most durable output — a hunt that produces a new rule that runs continuously creates ongoing value), reduction in dwell time for discovered incidents (comparing time-from-compromise to time-from-discovery for hunted vs alerted incidents), and percentage of MITRE ATT&CK techniques covered by at least one completed hunt. Many teams track a "hunt coverage map" similar to an ATT&CK Navigator layer to visualise which techniques they have hunted for and which remain unaddressed.