Security Sentinel

In Development

Network Security

Monitors network signaling for security anomalies including rogue base stations, signaling attacks, and unauthorized access patterns. Currently in early development, building detection models for SS7/Diameter protocol vulnerabilities and RAN-level threats.

securityanomaly detectionsignalingthreat

Current Score34.7

Best Score41.2

Total Iterations312

Skill Version0.1.5-alpha

Score Progression

Training score across 25 iterations

4-Layer Evaluation

Performance across correctness, simulation, performance, and robustness

Layer 1: Correctness

Detection logic validation

Layer 2: Simulation

Attack scenario testing (15 types)

Layer 3: Performance

Detection rate and false positive metrics

Layer 4: Robustness

Evasion technique resilience

Agent Parameters

Current configuration values

anomaly_sensitivitymedium

detection_window_sec60

min_confidence_threshold0.7

protocols_monitoredS1AP, GTP, Diameter

alert_severity_levels4

baseline_learning_period_hours72

Experiments

Latest 20 training runs

70% success

ID	Score	Description	Duration	Time
#20	35.0	Anomaly detection in signaling patterns	44m 19s	< 1h ago
#19	42.6	IMSI catcher detection heuristics	39m 58s	4h ago
#18	32.4	DDoS pattern recognition on S1 interface	43m 14s	11h ago
#17	26.7	Rogue base station identification	56m 2s	14h ago
#16	37.8	Subscriber authentication anomaly detection	38m 0s	20h ago
#15	39.9	GTP tunnel integrity monitoring	30m 14s	13h ago
#14	27.6	Diameter signaling attack detection	55m 36s	13h ago
#13	28.0	SS7 vulnerability scanning	54m 21s	1d ago
#12	39.5	RAN configuration drift detection	33m 8s	1d ago
#11	35.5	Unauthorized access pattern analysis	29m 52s	1d ago
#10	24.3	Encryption downgrade detection	45m 57s	1d ago
#9	30.5	Roaming fraud pattern analysis	28m 41s	1d ago
#8	39.4	SIM swap fraud detection	51m 8s	1d ago
#7	30.2	Network slice isolation verification	36m 42s	2d ago
#6	23.0	API security posture assessment	54m 2s	3d ago
#5	33.4	Certificate expiry monitoring	55m 55s	3d ago
#4	37.2	Baseline behavioral analysis	17m 28s	1d ago
#3	25.2	Lateral movement detection	30m 54s	3d ago
#2	23.8	Data exfiltration pattern matching	17m 28s	1d ago
#1	35.5	Zero-day signature generation	22m 19s	3d ago

DOIL Script

Declarative Operational Intent Language - defines what the agent should achieve

security.doil
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=="text-emerald-="text-amber-400">400">"text-accent">intent=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: detect_security_anomalies
=="text-emerald-="text-amber-400">400">"text-accent">domain=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: core.network_security
=="text-emerald-="text-amber-400">400">"text-accent">version=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: ="text-emerald-="text-amber-400">400">"="text-amber-400">0.1.="text-amber-400">5-alpha"

=="text-emerald-="text-amber-400">400">"text-accent">objective=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">:
  =="text-emerald-="text-amber-400">400">"text-accent">primary=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: detect_security_threats
  =="text-emerald-="text-amber-400">400">"text-accent">secondary=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: minimize_false_positive_rate
  =="text-emerald-="text-amber-400">400">"text-accent">constraint=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: detection_latency <= 5s

=="text-emerald-="text-amber-400">400">"text-accent">context=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">:
  =="text-emerald-="text-amber-400">400">"text-accent">interfaces=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: ="text-gray-500">[S1AP, GTP, Diameter, SS7="text-gray-500">]
  =="text-emerald-="text-amber-400">400">"text-accent">threat_model=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: ="text-gray-500">[rogue_bs, signaling_attack, unauthorized_access="text-gray-500">]
  =="text-emerald-="text-amber-400">400">"text-accent">environment=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: ="text-gray-500">[production, lab="text-gray-500">]

=="text-emerald-="text-amber-400">400">"text-accent">parameters=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">:
  =="text-emerald-="text-amber-400">400">"text-accent">search_space=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">:
    =="text-emerald-="text-amber-400">400">"text-accent">anomaly_threshold=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: ="text-gray-500">[="text-amber-400">0.5, ="text-amber-400">0.95, ="text-amber-400">0.05="text-gray-500">]
    =="text-emerald-="text-amber-400">400">"text-accent">detection_window_sec=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: ="text-gray-500">[="text-amber-400">10, ="text-amber-400">300, ="text-amber-400">10="text-gray-500">]
    =="text-emerald-="text-amber-400">400">"text-accent">baseline_period_hours=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: ="text-gray-500">[="text-amber-400">24, ="text-amber-400">168, ="text-amber-400">24="text-gray-500">]
    =="text-emerald-="text-amber-400">400">"text-accent">feature_set=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: ="text-gray-500">[statistical, ml_based, hybrid="text-gray-500">]
  =="text-emerald-="text-amber-400">400">"text-accent">constraints=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">:
    =="text-emerald-="text-amber-400">400">"text-accent">max_false_positive_rate_pct=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: ="text-amber-400">1
    =="text-emerald-="text-amber-400">400">"text-accent">max_detection_latency_sec=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: ="text-amber-400">5

=="text-emerald-="text-amber-400">400">"text-accent">evaluation=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">:
  =="text-emerald-="text-amber-400">400">"text-accent">layers=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">:
    - =="text-emerald-="text-amber-400">400">"text-electric-="text-amber-400">400">correctness=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: validate_detection_logic
    - =="text-emerald-="text-amber-400">400">"text-electric-="text-amber-400">400">simulation=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: run_attack_scenarios(attack_types=="text-amber-400">15)
    - =="text-emerald-="text-amber-400">400">"text-electric-="text-amber-400">400">performance=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: measure_kpis(="text-gray-500">[detection_rate, false_positive, latency="text-gray-500">])
    - =="text-emerald-="text-amber-400">400">"text-electric-="text-amber-400">400">robustness=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: test_evasion_techniques(sophistication=="text-gray-500">[low, medium, high="text-gray-500">])

=="text-emerald-="text-amber-400">400">"text-accent">convergence=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">:
  =="text-emerald-="text-amber-400">400">"text-accent">metric=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: f1_score
  =="text-emerald-="text-amber-400">400">"text-accent">target=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: >= ="text-amber-400">90%
  =="text-emerald-="text-amber-400">400">"text-accent">patience=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: ="text-amber-400">50
  =="text-emerald-="text-amber-400">400">"text-accent">strategy=="text-emerald-="text-amber-400">400">"text-gray-="text-amber-400">500">: adversarial_training

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