Topics
Browse posts by category and tag — every topic we cover, with the latest pieces under each.
Tags
- #ai-security 5
- #prompt-injection 4
- #threat-intel 3
- #adversarial-ml 2
- #generative-ai 2
- #llm-security 2
- #machine-learning 2
- #patch-management 2
- #supply-chain 2
- #vulnerability-management 2
- #agentic-ai 1
- #ai 1
- #ai-risks 1
- #ai-threats 1
- #anomaly-detection 1
- #burnout 1
- #chatgpt 1
- #cybersecurity-workforce 1
- #data-poisoning 1
- #deep-dive 1
- #deepfake 1
- #enterprise-security 1
- #exposure-management 1
- #financial-security 1
- #fraud 1
- #fraud-detection 1
- #graph-neural-networks 1
- #machine-learning-security 1
- #malware 1
- #meta 1
- #model-security 1
- #model-supply-chain 1
- #nist-ai-rmf 1
- #open-source 1
- #owasp 1
- #package-registry 1
- #remediation 1
- #rubygems 1
- #social-engineering 1
- #voice-cloning 1
- #vulnerability 1
Categories
threat-intel 7 posts
- Deepfake Cybersecurity: How AI Voice Cloning Reshapes FraudVoice deepfake incidents rose 680% in 2025 as attackers clone executives from seconds of audio. Here is what security teams need to know about detection, FBI advisories, and NIST standards.
- Machine Learning Security: Governance and Supply Chain RiskMachine learning security requires more than adversarial testing. This guide maps NCSC attack categories to NIST AI RMF controls and covers model supply chain risks that most organizations haven't addressed.
- How AI Fraud Detection Works: Techniques, Trade-offs, and NextAI fraud detection systems catch 70–90% more suspicious activity than rules-based methods. Here's how machine learning, graph neural networks, and behavioral analysis work — and where the structural gaps remain.
- RubyGems Suspends Signups After Hundreds of Malicious PackagesRubyGems has temporarily disabled new account registrations after attackers uploaded hundreds of malicious packages and launched a DDoS campaign against the popular Ruby package registry.
- Generative AI Risks: A Practitioner's Guide to What MattersFrom prompt injection to supply chain poisoning, the generative AI risk landscape is broader than most security teams realize. Here is what the frameworks say and what attackers are doing.
- Machine Learning Security: Key Threats, Attacks, and DefensesMachine learning security covers adversarial attacks, data poisoning, model theft, and supply chain risks targeting ML systems. Here is what practitioners need to know.
vulnerability 2 posts
- Most Remediation Programs Never Confirm the Fix Actually WorkedMandiant M-Trends 2026 puts mean time to exploit at negative seven days while Verizon's 2025 DBIR finds edge devices take 32 days to remediate. The deeper problem: closing tickets is not the same as closing exposures.
- LLM Security Risks: The Top Threats to Language Models in 2025Prompt injection, data poisoning, excessive agency, and system prompt leakage — a practitioner breakdown of the LLM security risks catalogued by OWASP and NIST for 2025 deployments.