conducting-social-engineering-pretext-call
FeaturedPlan and execute authorized vishing (voice phishing) pretext calls to assess employee susceptibility to social engineering and evaluate security awareness controls.
Install
Quality Score: 99/100
Skill Content
Details
- Author
- mukul975
- Repository
- mukul975/Anthropic-Cybersecurity-Skills
- Created
- 3 months ago
- Last Updated
- today
- Language
- Python
- License
- Apache-2.0
Similar Skills
Semantically similar based on skill content — not just same category
conducting-social-engineering-penetration-test
Design and execute a social engineering penetration test including phishing, vishing, smishing, and physical pretexting campaigns to measure human security resilience and identify training gaps.
conducting-spearphishing-simulation-campaign
Spearphishing simulation is a targeted social engineering attack vector used by red teams to gain initial access. Unlike broad phishing campaigns, spearphishing uses OSINT-derived intelligence to craf
executing-phishing-simulation-campaign
Executes authorized phishing simulation campaigns to assess an organization's susceptibility to email-based social engineering attacks. The tester designs realistic phishing scenarios, builds credential harvesting infrastructure, sends targeted phishing emails, and tracks open rates, click-through rates, and credential submission rates to measure human security awareness. Activates for requests involving phishing simulation, social engineering assessment, email security testing, or security awareness measurement.
phishing-sim
Phishing-simulation campaign workflow — RoE and ethical-scope template, population segmentation, pretexting patterns (HR/IT/finance/vendor/calendar), infrastructure (sender domain, SPF/DKIM/DMARC, tracking), click-rate and credential-success metrics, opt-out and duty of care, NL/EU AVG context for employee monitoring.
detecting-deepfake-audio-in-vishing-attacks
Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models. Supports batch analysis of audio files, generates confidence scores, and produces forensic reports. Activates for requests involving deepfake voice detection, vishing investigation, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.