All articles
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What Is an LLM Firewall? Prompt-Layer Defenses Explained
An LLM firewall inspects prompts and completions for injection, PII, and unsafe content. What these controls catch, where they sit, and what they miss.
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Prompt Injection Detection Tools: A Practitioner's Evaluation
Lakera Guard, Protect AI's DeBERTa classifier, Meta Prompt Guard, NeMo Guardrails, and LLM Guard on latency, false positives, and pipeline fit.
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Hallucination Detection Tools Compared: 11 Options
Eleven hallucination detection tools compared by family, deployment, and grounding requirement: HHEM, Lynx, MiniCheck, RAGAS, Bedrock, TLM, and more.
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Omni-Moderation API Guide: Categories, Scores, Limits
What omni-moderation-latest actually returns: all 13 categories, which ones accept images, how to read category_scores, and where the free endpoint stops.
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LLM Hallucination Detection Methods Explained: Four Techniques
The four main LLM hallucination detection methods compared: sampling consistency, claim decomposition, internal-state probing, and NLI faithfulness checks.
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How to Detect Jailbreak Prompts: A Practitioner's Guide
How to detect jailbreak prompts with perplexity heuristics, trained classifiers, and multi-turn scoring, plus the blind spots of each approach.
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How to Mitigate Prompt Injection Attacks: Defense in Depth
No single control stops prompt injection. This guide covers the layered defenses that reduce risk in production, from input hardening to monitoring.
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Best AI Content Moderation Tools 2026: Platform Comparison
A comparison of the leading AI content moderation platforms in 2026, covering Azure AI Content Safety, Hive, AWS Rekognition, and Perspective API.
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Fine-Tuned Classifiers vs. Moderation APIs: Cost and Tradeoffs
Off-the-shelf moderation APIs are cheap to start and expensive to outgrow. Fine-tuned classifiers are the reverse, and the crossover has a measurable point.
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Image & Video Content Moderation Tools (2026)
Text moderation gets the attention, but image and video hold the hard problems. A map of the cloud APIs, self-hosted options, and the CSAM referral path.
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Llama Guard vs Llama Guard 2 vs Llama Guard 3: Lineage Clarified
Meta's Llama Guard series gets cited loosely, often with the wrong base model or taxonomy. Here is the verified lineage, version by version, with sources.
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Perspective API Review: 8 Attributes and Where It Fails
Perspective API scores toxicity, insult, threat and five other attributes for comment moderation, and structurally misses the harms in LLM outputs.
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Content Moderation for RAG: The Retrieval Layer Is an Attack Path
RAG pipelines have a moderation gap at the retrieval layer that input and output classifiers miss, because injected documents enter the context first.
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Classifier Ensembles for Production Content Moderation
Single classifiers have characteristic blind spots. Ensembles that mix architectures and training data cut those failures, at a real cost in latency.
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False Positive Costs in Content Moderation: How to Measure Them
False positives in content moderation drive hidden costs: user abandonment, review queue spend, and appeal load. How to quantify and calibrate them.
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OpenAI Moderation API Review: What It Catches and Misses
OpenAI Moderation API review: ~20ms latency, free with API credits, image support, and the obfuscation, context, and customization gaps it leaves open.
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Llama Guard Benchmark Review: Real Performance vs. Vendor Claims
Meta's Llama Guard is the default open-source moderation classifier. Its benchmark numbers look strong; here is what they do and do not actually measure.
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NeMo Guardrails in Production: What It Does Well; Where It Fails
NVIDIA's NeMo Guardrails offers conversation-flow control that plain classifiers cannot provide. The deployment complexity is real and worth costing out.