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	34m 43s	< 1h ago
#19	42.6	IMSI catcher detection heuristics	28m 4s	4h ago
#18	32.4	DDoS pattern recognition on S1 interface	28m 54s	4h ago
#17	26.7	Rogue base station identification	43m 4s	9h ago
#16	37.8	Subscriber authentication anomaly detection	41m 18s	23h ago
#15	39.9	GTP tunnel integrity monitoring	52m 25s	19h ago
#14	27.6	Diameter signaling attack detection	46m 15s	16h ago
#13	28.0	SS7 vulnerability scanning	39m 28s	1d ago
#12	39.5	RAN configuration drift detection	23m 29s	1d ago
#11	35.5	Unauthorized access pattern analysis	58m 37s	1d ago
#10	24.3	Encryption downgrade detection	22m 2s	1d ago
#9	30.5	Roaming fraud pattern analysis	15m 36s	2d ago
#8	39.4	SIM swap fraud detection	52m 4s	2d ago
#7	30.2	Network slice isolation verification	31m 8s	1d ago
#6	23.0	API security posture assessment	33m 55s	2d ago
#5	33.4	Certificate expiry monitoring	43m 23s	2d ago
#4	37.2	Baseline behavioral analysis	48m 41s	2d ago
#3	25.2	Lateral movement detection	23m 17s	2d ago
#2	23.8	Data exfiltration pattern matching	15m 51s	2d ago
#1	35.5	Zero-day signature generation	48m 28s	4d 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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