CTI-REALM
We show this table for reference; we do not rank on it.
A cybersecurity benchmark that measures whether an agent can turn raw threat-intelligence reports into working detection rules.
Benchmark score on CTI-REALM — September 27, 2026
We compile the CTI-REALM rows from provider self-reports. Fugu Cyber leads the table at 72.1%. We do not use these results to rank models overall.
1 modelAgenticCurrentDisplay onlyUpdated September 27, 2026
Benchmark score table (1 model)
ScoreAbout CTI-REALM
Year
2026
Tasks
Threat-intelligence-to-detection-rule workflows
Format
Success rate
Difficulty
Professional cyber threat detection
Sakana AI describes CTI-REALM as a real-world security benchmark for translating cyber threat intelligence into executable detection rules. We store exact provider-reported results as display-only evidence until the benchmark owner publishes a stable, independently verifiable leaderboard artifact.
Freshness and provenance
Version
CTI-REALM 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
Questions
What does CTI-REALM measure?
A cybersecurity benchmark that measures whether an agent can turn raw threat-intelligence reports into working detection rules.
Which model scores highest on CTI-REALM?
Fugu Cyber by Sakana AI currently leads with a score of 72.1% on CTI-REALM.
How many models are evaluated on CTI-REALM?
1 AI models have been evaluated on CTI-REALM on BenchLM.
Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
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