Cybersecurity in the public sector often means navigating within strict budgetary requirements that can feel like hitting a brick wall that slows momentum and limits progress. With global cyber attacks continually on the rise, what does a Cybersecurity Engineer do when the checkbook fails to meet the mission demands for Enterprise-grade security?

The answer isn’t to spend more, but rather spend smarter. That starts with one of the more underutilized levers in the security stack, a properly configured SIEM.

Before diving in head first on how you can maximize your SIEM, there are a few important numbers to remember, that will suddenly make the cost of a Splunk license, seem like a bargain.

• $10 Million – The average cost of a government data breach when factoring in the total cost of an investigation, remediation, and the loss of public trust. (IBM Security, 2025)
• 197 Days – Without automated threat detection the average number of days an attacker is living in your network rent-free, while someone is sifting for a needle in the hay stack reviewing raw log data. (IBM Security, 2025).

A well-tuned SIEM can close that detection gap to minutes, not because there are more analysts searching for the needle, instead they are leaving the heavy lifting to the Platform, allowing for round the clock monitoring.

Here’s the kicker: most government organizations are already generating the data needed. Firewall logs, Active Directory events, and DNS queries, already exist. The question becomes how do you make that data work for you by turning it into intelligent insight?

The “Firehose” Trap

Tempting logic will suggest that every log generated in your environment will need to be ingested. More data means more visibility, and more visibility means better security, right? If only it were that simple.

Using the approach of “ingest everything” means that a government agency will blow through their budgets by the first quarter. This leaves the SIEM, while technically running, practically useless.

Splunk’s licensing models can be ingest-based and, more increasingly, compute-based. Every single gigabyte or virtual compute unit has a real dollar figure attached to it. Ingesting every raw, unfiltered log without a clear purpose, no longer becomes security, but an expensive log storage dressed up with a dashboard. Elastic Deployments aren’t immune to it either. Unfiltered data means larger clusters, higher infrastructure costs, which in turn leads to slower searches during times when speed matters the most.

What separates mature security environments from those that are throwing money into the trash? Shifting the logic from turning on the firehose by “ingesting everything” to knowing ingesting what matters most and knowing exactly why. That “why” is often the most difficult aspect, skipping that understanding is where budgets run away and are blown out of the water.

Your Greatest Advantage is Knowing Your Data

Before a single log event hits your SIEM, ask yourself one question, “What specific threat will this data help me detect or investigate?” If the answer is “it could be useful someday”, then that log can be placed on the back burner and revisited at a later date.

A simple prioritization tier will help ensure you are effectively ingesting what matters most.

Tier 1 – Critical

These are your highest priority for ingestion as they are needed for detecting attacks and confirming what happened during an incident.

• Authentication Logs
• Privileged Access Logs
• EDR Telemetry
• Cloud Audit Trails

Tier 2 – High

Supporting logs that will create strong context for investigations and work best alongside critical data sources.

• Domain Controller Logs
• VPN and DNS logs
• Database Access
• Firewall Allow and Blocked Events.

Tier 3 – Medium
Data Enrichment and movement-tracking logs which are useful for correlation but give lower signs of compromise on their own.

• Proxy Logs
• Network Flow Data
• User Endpoint Logs

The fastest way to ingest 200GB of data that will trigger zero actionable alerts, is by treating a print server log with the same urgency as authentication events. The Center of Internet Security (CIS) recommends that log sources are prioritized by the direct relationship to known attack techniques, which will match this three tiered approach (CIS, 2024)

Pro Tip: Data Never Indexed = Data that Saves You Money

In Splunk,using a Heavy Forwarder with a transforms.conf will allow you to drop the noise and only ingest what matters before it hits your indexers. In Elastic, the use of node processors can filter your data at the edge.

A Prescriptive Approach: Build Detections First and Work Backwards

It’s time to flip the approach of a typical SIEM deployment: instead of ingesting data and figuring out what to detect, start with the threats you need to catch and work backwards to the exact data required. While obvious in theory, it’s rarely done in practice.

For every tactic from Initial Access to Exfiltration, ask yourself: do I have a detection rule and do I have the data to support it and the subsequent investigation? These questions will be your roadmap, everything else is noise you’re paying to store (MITRE, 2024).

Take lateral movement via Pass-the-Hash (T1550.002) as an example. You only need exactly three Windows Security Event IDs to detect it: 4624, 4625, and 4648. Not all Windows Security Event data, just three ID’s.

Filtering at the forwarder level for those specific event codes, and you’ve just cut your Windows Event Log ingestion down by 60-80%. This alone will improve detection fidelity on one of the most common post-exploitation techniques in an adversary’s playbook (Microsoft, 2023).

For every detection rule written, documentation of the exact fields and log sources is an absolute must. This will become your data playbook and the justification for every ingestion decision, and informing the system owner why you need the logs.

Typically five high priority threat categories, mapped, and filtered correctly will ingest between 5-6 GB per day. When you compare that to the 200 GB/day many organizations ingest without a defined detection strategy, is not just cost savings, it’s the difference between a SIEM that pays for itself and one that is perpetually on the chopping block come budget season.

SIEM vs. Raw Log Hunting: Never a Fair Fight

When the budget strings start to tighten, the conversations sometimes go like this: “We already have the logs in a database, can’t we just query them directly and skip the cost of a SIEM license?” The answer should always be a firm no, and here’s why.

Raw log hunting is the cybersecurity equivalent of trying to find a gas leak by sniffing every room in the building one at a time. It might technically work, eventually, but by the time you’ve finished your manual sweep, the house is already on fire.

The capability gap is significant. A SIEM provides realtime automated detection, native cross source correlation, built-in threat intelligence matching, and the ability for one analyst to monitor an entire environment simultaneously. Raw log hunting gives you one analyst, one log source at a time, with manual joins that are brittle and slow.

Detecting low-and-slow attacks, like the kind nation-state actors favor against government targets, is effectively impossible without the statistical baselining and behavioral analytics a SIEM provides (CISA, 2023).

The Return on Investment argument writes itself. A well configured Splunk or Elastic deployment, even at $500K–$1M annually for a midsize agency, looks like an outstanding value against a $10M+ breach. The question isn’t whether you can afford a SIEM, it’s whether you can afford not to have one.

Stretching the Budget: More Value for Less Spend

Accepting that a SIEM is necessary is step one. Making it work within a government budget cycle, with all the procurement timelines and “we’ll revisit this in Q3” conversations that entails, will be the ongoing challenge. Here’s how experienced platform engineers actually do it.

A few tactics that actually move the needle:

• Splunk Summary indexes: Pre-aggregate high volume data into hourly statistical summaries. You get the trend data for anomaly detection at 1–5% of the raw storage cost. Your compliance team stays happy and your wallet will love you.
• Elastic ILM Tiers: Hot for 30 days, warm at day 7, frozen after day 14. Define the policy once and stop paying premium storage prices for data nobody’s queried in a month.
• Free threat intel feeds: CISA, AlienVault OTX, and open-source Threat Intelligence Platforms like MISP and OpenCTI are free. MS-ISAC has a curated feed available specifically for US State, Local, Tribal, and Territorial entities. Incidator-based detections matching known bad IPs and domains against your traffic is one of the highest ROI capabilities in your SIEM. If you’re not running these feeds today, fix that this week, not next quarter (CISA, 2024).
• SOAR-Lite Automation: Splunk’s Adaptive Response and Elastic’s Alerting Connectors can automatically block bad IPs, disable accounts on brute force thresholds, and open service tickets without the need for an additional license. You’re not getting the full SOAR experience, but you’re getting the majority of the value at none of the additional cost.

Conclusion:

The threat landscape isn’t slowing down anytime soon, and government cybersecurity budgets aren’t ballooning to meet it. The agencies that get the most out of their Splunk and Elastic investments aren’t the ones with the deepest pockets,they’re the ones that showed up with a strategy: know your crown jewels, audit before you ingest, map your detections, and tune relentlessly. A detection rule that fires 500 alerts a day isn’t a security win, it’s alert fatigue at its finest.

A focused, well-tuned SIEM will outperform a bloated one every single time. Build for precision and your budget will thank you long before your auditors do.

References:

Center for Internet Security. (2024). CIS controls version 8.1. https://www.cisecurity.org/controls

Cybersecurity and Infrastructure Security Agency. (2024). Free cybersecurity services and tools. U.S. Department of Homeland Security. https://www.cisa.gov/free-cybersecurity-services-and-tools

IBM Security. (2025). Cost of a data breach report 2023. IBM Corporation. https://www.ibm.com/reports/data-breach

Microsoft. (2023). Windows security event log reference: Audit logon events. Microsoft Corporation. https://learn.microsoft.com/en-us/windows/security/threat-protection/auditing/audit-logon

MITRE Corporation. (2024). MITRE ATT&CK framework: Enterprise matrix. The MITRE Corporation. https://attack.mitre.org/matrices/enterprise