TIFCE – A Practical Model to Evaluate Threat Intelligence Feeds

Threat Intelligence Feeds have become one of the most widely adopted components of modern detection strategies. Continuously, new repositories are published by multiple vendors, open-projects on GitHub, social networks, and multiple times they are introduced as the 'most complete' lists of malicious IPs, domains, URLs, and file hashes. In practice, however, some of these feeds are little more than mirrors of one another, re-publishing indicators from the same upstream sources or obsolete content.

This creates a structural problem for security teams. Adding more feeds does not necessarily increase visibility or protection. In many cases, it only increases duplication, alert noise, and operational overhead, while providing a false sense of coverage. A detection stack filled with overlapping intelligence does not become stronger — it becomes harder to manage and less precise.

For this reason, Threat Intelligence Feeds must be evaluated before being operationalized. Even before assessing whether a feed aligns with a specific industry, geography,languages, or technology stack (classification explained and published on MATCH-4 https://zenodo.org/records/17012869) , a more fundamental question must be answered: Is the feed itself valuable?

The TIFCE model (Threat Intelligence Feed Content Evaluation) addresses this question by providing a structured way to measure the intrinsic quality of a Threat Intelligence Feed. Instead of relying on reputation, popularity, or volume of indicators, TIFCE evaluates feeds based on how their data behaves inside real security telemetry. The model is built on four pillars that determine whether a feed adds protection, redundancy, risk, or noise.

1. Unique IOCs — Measuring Originality of the Feed

The first pillar of TIFCE evaluates whether a Threat Intelligence Feed contributes indicators that are not already widely distributed across other repositories.

A significant portion of public and commercial feeds rely on the same upstream sources, such as MISP instances, OSINT aggregators, or malware-sharing platforms. When this happens, multiple feeds may appear independent while actually delivering the same indicators. This leads to duplicated detections and repeated alerts for the same threat, reducing operational efficiency.

Within the TIFCE model, uniqueness is measured by aggregating indicators across feeds and identifying how many feeds report each IOC. A feed that contributes a high number of exclusive indicators provides real expansion of threat visibility. A feed that mostly overlaps with others adds little incremental value.

2. Detected IOCs — Measuring Environmental Relevance

A feed can be unique and still be irrelevant. The second TIFCE pillar measures whether the feed’s indicators actually appear in the organization’s environment.

This is done by correlating the feed’s IOCs with security telemetry such as email activity, file downloads, URLs accessed, or network connections. If a feed’s indicators never appear in real telemetry, it may describe threats that are geographically, sectorially, or temporally unrelated to the environment being protected.

This stage answers questions such as:

• Are these indicators being seen by security controls?

• Are they being blocked, quarantined, or allowed through?

• Are they completely absent?

A feed that consistently intersects with real activity provides actionable intelligence. A feed that never matches anything observed in telemetry is only theoretical.

3. Malicious IOCs — Measuring Signal Versus Noise

Not every matched indicator represents a real threat. The third TIFCE pillar evaluates whether the detected IOCs are truly malicious.

Indicators that are blocked or quarantined by security controls provide a strong signal that the feed contains confirmed threats. However, when indicators appear in content delivered to users, further validation is required. Public feeds frequently include domains or URLs that belong to legitimate platforms, compromised but benign infrastructure, or cloud services that are widely used.

TIFCE requires that these cases be evaluated to distinguish:

• True positives, where a feed reveals a missed threat

• False positives, where legitimate services are mislabeled

Feeds that consistently generate validated malicious detections improve protection. Feeds that produce large volumes of false positives introduce risk and operational cost.

4. Active IOCs — Measuring Feed Freshness

Threat intelligence has a limited lifespan. Malicious infrastructure changes, campaigns end, and domains or IP addresses are recycled. The fourth pillar of TIFCE evaluates whether a feed is still actively maintained.

A feed that no longer receives updates gradually fills with obsolete indicators. These may point to domains that no longer exist or IPs that now belong to legitimate organizations. Using such data in detection pipelines degrades accuracy and increases false alerts.

Feed activity can be measured through update frequency, commit history, timestamps, or the rate of new IOC publication. An effective Threat Intelligence Feed is not only accurate — it is current.

Why TIFCE Matters

Only feeds that demonstrate originality, environmental relevance, validated maliciousness, and ongoing activity should be considered candidates for deeper alignment models such as sector matching or threat profiling.

In modern security operations, the value of threat intelligence is not defined by how many indicators exist, but by how many of them actually protect the environment.