The Agentic Attack Surface Does Not Stay Still
Four recent papers show why LLM security now has to cover memory, retrieval, tools, identity, delegation, interfaces, and the infrastructure around the model.
notebook / category
cybersecurity
7 entries in this research area.
Using MITRE ATLAS to Make AISecOps Threat-Informed
MITRE ATLAS gives AI security teams a shared map of adversary behavior for threat modeling, detection engineering, red teaming, and incident response.
Using OWASP's Agentic Top 10 to Govern Systems That Act
The OWASP Agentic Top 10 moves security beyond model output and into goals, tools, identities, memory, delegation, and runtime control.
Using the OWASP LLM Top 10 as an Engineering Baseline
The OWASP LLM Top 10 turns common language-model failure modes into security requirements, tests, telemetry, and response plans.
Using NIST AI RMF to Build an AISecOps Program
NIST AI RMF gives an AI security program its operating model: govern the work, map the context, measure the risk, and manage what happens next.
Zero Trust Is the Foundation AI Agents Need
Anthropic's framework connects agent identity, least agency, tool boundaries, memory integrity, and recovery into one practical security model.
Threat Modeling the Agent on Your Laptop
A practical security review for agents that can read files, run commands, and use outside services.