Blue Team POV

“We Caught Red” Isn’t the Win.
Real Detections Are.

Same Team, One Fight.

Catching your internal red team is a checkpoint, not a trophy. The goal is to build signal-rich detections that catch real adversaries—without flooding ops or gaming the test.

Precision over vanity metrics Partnership over point-scoring Threat-led, data-driven
Reframe the Win

Catching Red ≠ Defensible Security

“We found the red team” can feel good—but it’s not the mission. If detection logic only trips on your red team’s constraints, you didn’t harden the org; you optimized for the test.

Anti-patterns: blocking all traffic to a budget cloud provider because red’s C2 is there; alerting on a specific commercial C2 brand string because that’s what red can afford. These don’t translate to real-world adversaries and they waste everyone’s time.

Quality Over Quips

What Useful Detections Look Like

Great detections focus on behaviors and invariants that adversaries can’t easily change, not vendor names or hosting ASNs that they can swap in minutes.

Technique-level signals (e.g., living-off-the-land misuse, suspicious parent/child process chains)
Cross-source corroboration (EDR + DNS + proxy + identity)
Context-aware baselining (peer/asset role, seasonality, maintenance windows)
Tunings that reduce fatigue (auto-suppress known-good, escalate pattern drift)
Partner for Signal

Use Red to Make Blue Stronger

Red is your R&D lab. Collaborate to design tests that pressure the right seams and produce reusable signals. Ask for variants: different cloud providers, payload packers, signed binaries, staging paths, and opsec levels.

Ask red for: a matrix of scenarios (low/no-budget → well-resourced), technique toggles (e.g., C2 family swap), and operating constraints that mimic real threats—not just the easiest to detect.

Culture & Craft

Peer-Policing Vanity Detections

Celebrate learning, not gotchas. If a rule exists only to rack up “caught red” points, call it out. Redirect to detections that generalize to real intrusions and improve incident flow.

Aim critique at systems, not people
Document why each rule exists and what threat it covers
Track false positives/negatives & action cost
Retire rules with poor precision/recall
Starter Kit

Replace Traps with Signal

Replace provider/brand matches with behavior chains (e.g., office app → script interpreter → LOLBin → outbound with rare destination & new JA3)
Instrument identity: anomalous MFA, risky token minting, unusual OAuth consent
Layer detections: DNS entropy + TLS SNI age + process ancestry
Codify detection reviews with red & IR every sprint

Drop these: blanket “anything to DigitalOcean” blocks, “alert on Cobalt Strike string” without behavior context. They stall engagements and don’t map to real adversaries.

Outcomes That Matter

Measure Wins That Move Risk

Shift from “we caught red” to metrics that reflect real security outcomes:

Precision/Recall per rule & per campaign (cut alert fatigue)
Time-to-detect & time-to-understand for realistic scenarios
Repeat-intrusion rate by technique (are fixes sticking?)
Mean-time-to-contain/eradicate for top TTPs

Team pledge: We’ll tune for adversary behaviors, not internal constraints. We win together when detections catch what real attackers do.