EXTR vs INTZ

Extreme Networks, Inc. vs Intrusion Inc. — Valuation Comparison 2026

EXTR

Computer Communications Equipment
Extreme Networks, Inc.
Quality
9.3
out of 10
Value Trap
11
SAFE
Price
$26.51
Last close
Models
13/13
Active
VS

INTZ

Computer Communications Equipment
Intrusion Inc.
Quality
5.9
out of 10
Value Trap
24
SAFE
Price
$0.83
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType EXTR Fair ValueEXTR Upside INTZ Fair ValueINTZ Upside
Bayesian DCF Intrinsic $10.71 -59.6% $0.15 -82.3%
Earnings Power Value Intrinsic $3.36 -87.3% $1.56 +97.8%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for EXTR vs INTZ — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

EXTR vs INTZ — Which Stock Is More Undervalued?

EXTR scores higher with a 9.3/10 quality rating vs INTZ's 5.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Extreme Networks, Inc. (EXTR) and Intrusion Inc. (INTZ) across 13 institutional-grade valuation models reveals how each company's intrinsic value stacks up against its market price. CirclFi's engine processes SEC EDGAR 10-K and 10-Q filings, FRED macroeconomic data, and GDELT news sentiment to generate independent fair value estimates daily.

EXTR currently trades at $26.51 with a QOC of 9.3/10, while INTZ trades at $0.83 with a QOC of 5.9/10.

Both companies are analyzed with models spanning intrinsic (Bayesian DCF, EPV), scenario-based (First Chicago), regime-switching (Markov DDM, RCMH-DCF), machine learning (ML-RIV, FTNN Topology), and ensemble methods (CUCE).