AI for Cybersecurity Analysts

What you do today

Lead incident response for confirmed security events — contain the threat, preserve evidence, coordinate remediation, and manage communications. Follow incident response playbooks while adapting to the specific situation.

AI that applies

AI automates initial containment actions — isolating compromised systems, blocking malicious IPs, and preserving forensic data. Automated playbooks execute standard response steps while analysts focus on decision-making.

How it works

The system monitors network traffic, access logs, and threat intelligence feeds in real time. The automation engine executes each step in the process sequence — validating inputs, applying business rules, generating outputs, and routing exceptions to human review queues. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.

What you do today

Detect and respond to DDoS attacks targeting network infrastructure or customers. Classify attack type (volumetric, protocol, application layer), activate mitigation — scrubbing centers, BGP diversion, rate limiting — and verify clean traffic delivery.

AI that applies

ML-based DDoS detection identifies attacks within seconds by comparing traffic patterns against baselines. Automated mitigation orchestration activates countermeasures without manual intervention for known attack patterns.

How it works

For analyze ddos attacks & manage mitigation, the system identifies attacks within seconds by comparing traffic patterns against. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.

What you do today

Monitor threat intelligence feeds for telecom-specific threats — new exploit techniques, emerging attack campaigns, and threat actor TTPs. Translate intelligence into defensive actions for your environment.

AI that applies

AI aggregates and correlates threat intelligence from multiple feeds, mapping indicators of compromise to your environment. Automated enrichment adds context to raw indicators.

How it works

The system monitors network traffic, access logs, and threat intelligence feeds in real time. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.

What you do today

Protect the telecom signaling layer from exploitation — monitoring SS7, Diameter, and GTP for unauthorized location queries, call interception attempts, and subscriber fraud. Manage signaling firewalls and security policies.

AI that applies

ML models analyze signaling traffic for anomalous patterns — unexpected location queries from unusual sources, bulk subscriber queries, and suspicious routing modifications. AI correlates events across protocols to detect multi-vector signaling attacks.

How it works

The system ingests signaling traffic for anomalous patterns — unexpected location queries from unus as its primary data source. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The output is a prioritized alert queue, with the highest-confidence findings surfaced first for immediate review.

What you do today

Watch SIEM dashboards for security events — intrusion attempts, malware detections, anomalous traffic patterns, policy violations. Triage alerts by severity and investigate suspicious activity.

AI that applies

AI-powered SIEM platforms correlate events across network, endpoint, and application logs to surface genuine threats from millions of daily events. ML reduces false positive rates by learning from analyst disposition decisions.

How it works

The system ingests millions of daily events as its primary data source. The analytics engine aggregates data across sources, applies statistical analysis to identify significant patterns and outliers, and presents the results through visualizations that highlight what needs attention. The output — genuine threats from millions of daily events — surfaces in the existing workflow where the practitioner can review and act on it.

What you do today

Scan network infrastructure for vulnerabilities — unpatched systems, misconfigurations, default credentials, exposed services. Conduct or manage penetration testing against critical systems. Track remediation of identified vulnerabilities.

AI that applies

AI prioritizes vulnerabilities by exploitability, business criticality, and exposure context — not just CVSS scores. Automated scanning runs continuously rather than quarterly.

How it works

For conduct vulnerability assessments & penetration testing, the system draws on the relevant operational data and applies the appropriate analytical models. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.

What you do today

Administer access controls for network elements, OSS/BSS systems, and sensitive data. Review access requests, manage privileged accounts, and investigate suspicious access patterns.

AI that applies

AI detects anomalous access patterns — unusual login times, unexpected privilege escalations, and access from new locations. Automated access reviews flag stale accounts and excessive privileges.

How it works

The system ingests flag stale accounts and excessive privileges as its primary data source. The analytics engine aggregates data across sources, applies statistical analysis to identify significant patterns and outliers, and presents the results through visualizations that highlight what needs attention. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.

What you do today

Investigate security issues affecting customers — SIM swap fraud, account takeover, unauthorized access to customer data. Coordinate with customer care, fraud teams, and law enforcement as needed.

AI that applies

AI detects SIM swap attempts by identifying changes in device behavior patterns. Automated fraud scoring flags high-risk account changes before execution.

How it works

The system ingests customer interaction data — transactions, communications, behavioral signals, and profile information. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.

What you do today

Prepare evidence for compliance audits — SOC 2, NIST CSF, CPNI, CALEA, critical infrastructure protection requirements. Gather documentation, demonstrate control effectiveness, and manage remediation of audit findings.

AI that applies

AI automates evidence collection and maps controls to multiple compliance frameworks simultaneously. Automated compliance monitoring detects control gaps before auditors do.

How it works

The system monitors regulatory data sources — rule changes, enforcement actions, and compliance records. The automation engine executes each step in the process sequence — validating inputs, applying business rules, generating outputs, and routing exceptions to human review queues. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.

What you do today

Write and maintain security policies, standards, and procedures for the telecom environment. Ensure alignment with regulatory requirements (CPNI, CALEA, critical infrastructure protection) and industry frameworks.

AI that applies

AI maps regulatory requirements to existing policies, identifying gaps. Generative AI assists in drafting policy updates and plain-language summaries.

How it works

The system monitors network traffic, access logs, and threat intelligence feeds in real time. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.