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Unify enterprise visibility and eliminate active business risk. SourceMash delivers expert engineering, data pipeline acceleration, and automated orchestration workflows across the Splunk platform transforming millions of machine-generated telemetry logs into predictive, real-time security intelligence.
Our Splunk Specializations
From setting up initial system data models to coding multi-app workflow integrationsSourceMash engineers scalable pipelines to accelerate security response windows across your modern global infrastructure.
Practice 01
Data velocity can strain operations and inflate licensing footprints. SourceMash designs scalable data topologies using Splunk Universal Forwarders and Heavy Forwarders to safely gather data from any operating system, cloud layer, or physical host. We focus on normalizing raw text structures via the Splunk Common Information Model (CIM), filtering non-essential events at the network perimeter to lower retention storage investments while maintaining rich trace accessibility.
Configuring custom transforms.d and props.conf files to strip out redundant data structures like verbose web traffic headers at the log boundary before it reaches storage clusters, lowering infrastructure indexing overhead significantly.
Securing visibility across public cloud setups. We engineer reliable data integrations using event firehoses, webhooks, and storage queues to systematically collect operational logs from AWS CloudTrail, Azure Log Analytics, and GCP Pub/Sub streams.
Architecting robust data availability models. We configure multi-site indexer clusters using high-speed flash arrays for hot search paths, automatically moving older trace libraries down to cold cloud-object pools to satisfy multi-year data retention compliance guidelines.
Practice 02
Isolated indicators are easy to miss. SourceMash deploys and optimizes Splunk Enterprise Security (ES) to correlate alerts from distinct systems across your enterprise environment. By building behavioral tracking models and custom risk scores, we map active alert groups to the universal MITRE ATT&CK framework, turning raw text streams into prioritized security alerts.
Engineering security rules inside Splunk. We build custom correlation searches that analyze disparate activitieslike unusual database access combined with sudden outbound connectionsto flag advanced threats while ignoring benign corporate activity.
Transitioning operations away from static alert models. We replace traditional system alerts with a modern Risk-Based Alerting setup, tracking threats across individual users or assets over time to surface high-risk patterns cleanly.
Integrating intelligence sources seamlessly. We link real-time threat data directly into your Splunk environment via TAXII, STIX, or custom cloud APIs, cross-referencing outbound network traffic against known malicious hosting vectors automatically.
Practice 03
Manual threat containment is too slow to stop modern attacks. SourceMash builds automated workflows using Splunk SOAR (formerly Phantom) to orchestrate defensive actions across your entire tech stack at machine speed. We integrate third-party APIs directly, building reliable visual and Python-based playbooks that automatically block active attacks within seconds.
Building reliable response automation workflows. We write custom Python structures inside Splunk SOAR to manage alert tasks like parsing attachments, querying file reputations, and managing multi-step approval gates safely.
Linking disparate security products. We deploy and configure verified connection assets to orchestrate actions directly across Active Directory, Microsoft Exchange, CrowdStrike nodes, and Cisco firewalls safely.
Streamlining inbox security. We build playbooks that extract URLs and attachments from reported emails automatically, checking reputations through sandboxes and deleting identical malicious variants across all enterprise mailboxes within seconds.
Manual triage often causes critical delays during active attacks. When a compromised credential triggers an alert, standard remediation paths rely on waiting for on-call engineers to log in, review the trace context, and disable access manually. SourceMash engineers Splunk SOAR playbooks to handle these verification sequences automaticallyquerying asset locations, validating abnormal patterns, and disabling compromised accounts via API commands within seconds of discovery.
A carefully planned, phased engineering approach to onboard critical data sources and build robust automation playbooks safely.
We analyze your target infrastructure layout and daily log generation models, evaluating structural performance across active data patterns to map out index storage retention buckets and plan license size strategies accurately.
We deploy lightweight Splunk Universal Forwarders across your assets, configuring secure TLS connections and setting up Heavy Forwarder tier parsing rules to normalize raw machine data before it moves to core indexers.
We map all incoming log streams to the standard Splunk Common Information Model (CIM), aligning variable event fields across cloud networks, identity layers, and endpoints to enable reliable enterprise searches.
We configure tailored correlation rules within Splunk Enterprise Security, tuning baseline behavior models, updating risk-scoring matrices, and linking event patterns directly to MITRE ATT&CK identifiers.
We configure API connections across your infrastructure stack inside Splunk SOAR, building visual and Python-based automation playbooks to manage threat containment loops like active network isolation securely.
Transition to steady-state operations. We monitor cluster health continuously, optimize slow-running SPL queries using summary indexing, upgrade application packs safely, and run regular threat simulations to ensure maximum reliability.
We deploy, fine-tune, and align the complete Splunk enterprise portfolio to build a resilient, high-performance security data ecosystem.
Our delivery teams maintain advanced certifications directly from Splunk, ensuring compliant architecture patterns across every deployment project.
Perspectives, research, and practical guidance from our enterprise technology experts.
Trusted by engineering directors and security managers worldwidediscover how SourceMash designs, fine-tunes, and accelerates modern Splunk ecosystems.
SourceMash rebuilt our security search patterns completely. Their Risk-Based Alerting configuration within Splunk Enterprise Security trimmed our daily console alert noise by 90%, allowing our defense team to remain focused on actual real-time system compromises.
The automated phishing response playbooks that SourceMash engineered inside our Splunk SOAR environment are outstanding. Incidents that used to require 30 minutes of manual verification are now triaged, reviewed, and completely neutralized via API commands within 45 seconds.
Migrating 40 terabytes of daily log pipelines to Splunk Cloud was an daunting task for our team. SourceMash structured our heavy edge forwarding paths and data filters perfectly, trimming our daily ingestion footprint by 35% without losing structural log visibility.
Everything you need to know before reaching out to us.
How can SourceMash help reduce our overall Splunk data ingestion license costs?
We deploy explicit filtering rules within your edge Heavy Forwarders or Splunk Edge Processors using custom regex transforms. This strips out repetitive system entries like verbose network connection logs, status heartbeats, or duplicate tracking strings at the network boundary before it reaches core indexers, trimming up to 40% of licensing volume without reducing tactical log visibility.
What is Risk-Based Alerting (RBA) within Splunk Enterprise Security, and how does it help?
RBA changes how security platforms track alerts. Instead of triggering single, isolated notifications for every single anomaly, RBA maps risk points to specific corporate assets or user identities over time. A notable incident is surfaced only when the aggregated risk pattern maps out an active multi-step attack sequence, cutting baseline alert noise by over 90%.
Do we need to write code to build automated playbooks inside Splunk SOAR?
No, most standard workflow logic can be designed using Splunk SOAR's visual block interface. However, for specialized requirementslike parsing unique API return tokens, handling complex calculations, or connecting to custom corporate databasesour engineers write secure Python code scripts directly within the automation engine blocks to manage actions reliably.
How does SourceMash ensure zero data gaps during a transition to Splunk Cloud?
We deploy a safe, dual-routing edge network architecture using Universal Forwarders to send log records to both your legacy on-premises servers and your new Splunk Cloud environment simultaneously. We cut over search and reporting operations only after cross-site data testing verifies complete field matching across your active indexes.