Editorial desk
AI Sec Reviews Editorial
AI Sec Reviews Editorial is the publishing identity for AI Sec Reviews. It is a desk, not a person: no named author, no biography, no professional certifications.
Articles published under this byline are researched from primary sources — vendor and project documentation, published standards and specifications, research papers, and measurements published by whoever took them — drafted with AI assistance, and edited against those cited sources before publication. Nothing here is based on first-hand testing in a private lab, and any figure that appears is attributed to the source it came from.
Corrections go to hello@aisecreviews.com. More detail is on the about page and the editorial disclosure.
Posts (18)
- Defense
How to Secure Vector Database Access in RAG Systems
Vector stores in RAG pipelines carry auth gaps, embedding inversion risk and cross-tenant exposure. How to lock down both the read and write path.
- Methodology
AI Security Review: A Checklist for LLM Systems
An AI security review checklist for LLM systems: trust boundaries, data flows, control mapping, evidence to demand, and the findings reviewers miss.
- Comparisons
LLM Security Benchmarks Compared: What Each Measures
LLM security benchmarks compared: what HarmBench, JailbreakBench, AgentDojo, AgentHarm and CyberSecEval each measure, and where every one of them stops.
- Defense Guides
RAG Pipeline Security Best Practices: A Checklist
RAG pipeline security best practices: retrieval poisoning, access control at query time, embedding risks, and how OWASP and MITRE ATLAS frame the threats.
- Defense Guides
How Prompt Injection Detection Works: Classifiers, Monitors
How prompt injection detection works, from input scanning and embedding classifiers to fine-tuned guardrails and runtime monitoring, with the trade-offs.
- Comparisons
Best AI Security Testing Tools 2026: Scanners and Red Teams
A practitioner's comparison of the best AI security testing tools in 2026: open-source scanners, commercial red-teaming platforms, and how to choose.
- Defense Guides
OWASP LLM Top 10 Mitigation Guide: Controls for Every Risk
A practitioner's OWASP LLM Top 10 mitigation guide covering all ten 2025 risk categories, from prompt injection to unbounded consumption, with controls.
- Tool Reviews
Patronus AI Review: Automated LLM Evaluation and Guardrails
A review of Patronus AI's evaluation platform: the Lynx hallucination model, the Glider custom evaluator, built-in safety checks, and published pricing.
- Tool Reviews
Protect AI's ModelScan and NB Defense: An Open-Source Review
A review of Protect AI's two best-known open-source tools — ModelScan for model serialization attacks and NB Defense for Jupyter notebooks.
- Tool Reviews
Robust Intelligence (Now Cisco AI Defense): Platform Review
A review of Robust Intelligence, now part of Cisco AI Defense: algorithmic red teaming, model file scanning, and runtime protection of AI applications.
- Tool Reviews
Giskard Review: Open-Source Testing for LLM and RAG Apps
A review of Giskard, the open-source Python library for testing AI systems, covering its automated LLM vulnerability Scan and the RAGET RAG toolkit.
- Methodology
How to Evaluate AI Security Tools Without Getting Fooled
AI security tool demos are built for best-case scenarios. The evaluation dimensions, protocol, and vendor questions that expose how a tool really performs.
- Tool Reviews
PyRIT Review: Microsoft's AI Red Teaming Framework
A review of PyRIT, Microsoft's open-source AI red teaming framework: its target, orchestrator, converter, scorer and memory design, and multi-turn attacks.
- Tool Reviews
Guardrails AI: Output Validation Without Retraining
Guardrails AI provides a validation layer for LLM outputs — checking format, structure, and content without touching the model.
- Tool Reviews
Arize Phoenix: LLM Observability That's Actually Free
Arize Phoenix is an open-source LLM observability platform that has grown well beyond its origins as a drift detector, with evaluation tooling built in.
- Tool Reviews
Garak LLM Scanner Review: Research Tool or CI Gate?
A review of garak, NVIDIA's open-source LLM vulnerability scanner: plugin architecture, backend coverage, report quality, and the CI-gating pattern.
- Tool Reviews
Rebuff: Open-Source Prompt Injection Defense, Layer by Layer
Rebuff is a self-hosted prompt injection detector with four layers: heuristics, LLM-based detection, a vector database of past attacks, and canary tokens.
- Tool Reviews
Lakera Guard: Prompt Injection Detection in Practice
Lakera Guard is built for prompt injection detection rather than content moderation. What the documentation shows about coverage, latency, and cost.