Results for “nemesis”

Configure and run Nessus vulnerability scans, analyze results, and integrate scanning into continuous vulnerability management workflows.

Conduct authenticated and unauthenticated vulnerability scans using Tenable Nessus to identify known vulnerabilities, misconfigurations, and missing patches, with prioritized remediation guidance.

Establishes recurring vulnerability scanning workflows using Nessus, Qualys, or OpenVAS, prioritizes findings with risk scoring and CISA KEV data, integrates with SIEM for exploitation detection, and tracks remediation via SLA-based dashboards and automated ticketing.

Implement JWT authentication, RBAC guards, Helmet hardening, and Argon2 hashing in NestJS. Use when adding auth strategies, role-based access control, CSRF protection, or security headers.

Enumerate SMB, WinRM, LDAP, and MSSQL services, validate credentials, spray passwords, and execute commands on remote hosts using NetExec during authorized penetration tests.

Detect and respond to Adversary-in-the-Middle (AiTM) phishing attacks that use reverse proxy kits like EvilProxy, Evilginx, and Tycoon 2FA to bypass MFA and steal session tokens.

Analyze Zeek network logs to detect lateral movement techniques including SMB admin share access, DCE/RPC remote service creation, NTLM account spray, Kerberos anomalies, and large internal data transfers.

Run CIS Kubernetes Benchmark checks and remediate findings with kube-bench.

AI security and safety specialist for guardrails and adversarial resilience. Use when the user asks to talk to Snape, requests a safety audit, or needs guardrails design.

Categorize BES cyber systems and implement NERC CIP compliance controls for high, medium, and low impact assets, including electronic security perimeters, configuration management, and supply chain risk management.

Plan, run, and measure adversary engagement operations using the MITRE Engage framework, covering the Engage Matrix, 10-Step Operational Process, and mapping Activities to ATT&CK techniques.

Detect poisoned training data and backdoored models across the ML pipeline using statistical analysis, activation clustering, and spectral signatures.