AI Evaluation and Security
Before Buying an AI Tool: Build a Benchmark Decision Sheet
Help a small engineering team turn a vendor benchmark claim into a documented purchase or pilot decision.
By Romfix Editorial Team
Independent technology publication
Turn AI evidence into practical checks.
Practical decision worksheets for AI tools, evaluation and application security.
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Security and model intelligence
AI Evaluation and Security
A Release-Gate Worksheet for an AI Cyber Evaluation
Help an evaluation owner prepare an enforceable scope and stop-path review before starting a controlled cyber exercise.
By Romfix Editorial Team
AI Evaluation and Security
Run a Prompt Injection Tabletop Around One Tool Call
Guide an application team through a harmless tabletop that identifies the independent control protecting one consequential tool call.
By Romfix Editorial Team
AI Security
AI Supply Chain Security: Models, Data, Code, and Provenance
An operational AI supply-chain guide covering models, datasets, code, containers, prompts, services, provenance, release controls, and incident response.
By PermsAI Editorial Team
AI Security
LLM Security Risks: A Practical Guide for Developers
A developer-focused architecture guide to LLM trust boundaries, authorization, retrieval, output validation, tool safety, secrets, and monitoring.
By PermsAI Editorial Team
AI News
Year in AI Security: Evidence, Incidents, and Durable Lessons
A year-to-date evidence synthesis for 2026, separating durable engineering lessons from incomplete or still-unresolved claims.
By PermsAI Editorial Team
AI News
Open-Source Model Security Research: A Quarterly Evidence Review
A dated evidence review for securing open-source and open-weight model artifacts from repository to isolated serving.
By PermsAI Editorial Team
AI News
AI Regulation and Security Standards: Technical Change Log
A dated technical change log for NIST, EU, and standards-body updates, with control mappings and evidence to retain.
By PermsAI Editorial Team
AI News
AI Cyber Capability Evaluations: Reading New Evidence Safely
A dated guide to reading cyber-capability results without confusing benchmark performance with real-world compromise probability.
By PermsAI Editorial Team
AI News
RAG Security Research Review: Poisoning, Leakage, and Provenance
Current RAG security evidence separates poisoning, leakage, access control, and provenance, then maps research claims to defensible controls.
By PermsAI Editorial Team
AI News
Prompt Injection Research Review: Defenses That Generalize
A dated research synthesis separates attack detection from damage prevention and evaluates when prompt-injection defense evidence transfers beyond one benchmark.
By PermsAI Editorial Team
AI News
AI Agent Incident Reviews: Failure Paths and Control Lessons
Three documented evaluation incidents reveal how weak boundaries, inferred authorization, and delayed detection propagate into real impact. Evidence reviewed 2026-09-17.
By PermsAI Editorial Team
AI News
Frontier Model System Card Review: Security Evidence Checklist
An evidence-led review of GPT-6 Astra's September 2026 system card, using supported, partial, unestablished, and unreported claim statuses without ranking models.
By PermsAI Editorial Team
AI News
OWASP GenAI Top 10 Updates: Changes for Builders
A release-led comparison of OWASP's 2026 and 2025 LLM Top 10, with exact counterparts, date caveats, and a control-impact map for existing applications.
By PermsAI Editorial Team
AI News
NIST AI Agent Security Guidance: What Changed and Why It Matters
A dated analysis of NIST's agent-security RFI, NCCoE identity concept paper, and standards initiative, with practical control translations and explicit draft-status limits.
By PermsAI Editorial Team
AI News
Monthly AI Security Research Review
September 2026 month-to-date review of AI security research, with evidence cards, limitations, and actions for testing agentic systems.
By PermsAI Editorial Team
Benchmarks
Frontier Model Evaluations: Capabilities, Safeguards, and Limits
How to read frontier model evaluations as dated evidence about capabilities, safeguards, and limits—and turn the results into bounded security decisions.
By PermsAI Editorial Team
Benchmarks
Test-Time Compute and Reasoning Benchmarks
A practical framework for reporting test-time compute, samples, search, tools, retries, quality, latency, and cost in reasoning benchmarks without hiding the budget.
By PermsAI Editorial Team
Benchmarks
Benchmark Saturation: When a Test Stops Being Useful
A practical framework for detecting benchmark saturation and choosing whether to keep, complement, refresh, or replace an AI evaluation.
By PermsAI Editorial Team
Benchmarks
Benchmark Contamination and Data Leakage in LLM Evaluation
A practical audit for benchmark contamination, data leakage, tool exposure, and evidence-based LLM evaluation claims.
By PermsAI Editorial Team
Benchmarks
LLM-as-a-Judge Evaluation: Bias, Calibration, and Validation
A practical method for validating LLM judges with human reference evidence, bias testing, calibration, slice analysis, and drift monitoring.
By PermsAI Editorial Team
Benchmarks
Agentic Benchmarks: Measuring Tools, Planning, and Reliability
A practical guide to measuring agentic systems as evaluated workflows, including tools, environments, recovery, safety constraints, and reproducibility.
By PermsAI Editorial Team
Benchmarks
AI Security Benchmarks: What Attack Success Rates Mean
How to interpret AI security benchmark attack-success rates with clear denominators, attacker budgets, defenses, utility, uncertainty, and evidence.
By PermsAI Editorial Team
Benchmarks
Coding Benchmarks Explained: HumanEval, SWE-bench, and Beyond
A practical guide to interpreting coding AI benchmarks: compare function completion, repository repair, agent scaffolds, test quality, and reproducibility.
By PermsAI Editorial Team
Benchmarks
LLM Evaluation Harnesses: Reproducibility and Hidden Variables
A practical guide to evaluation harness reproducibility: identify hidden variables, report the full evaluated system, and label benchmark comparisons honestly.
By PermsAI Editorial Team
Benchmarks
Designing a Private LLM Evaluation Dataset
A practical architecture for building private LLM evaluation data that measures real tasks without leaking the holdout into development.
By PermsAI Editorial Team
Benchmarks
How to Compare AI Models for a Production Use Case
A workload-first method for turning production requirements into a defensible AI model selection decision.
By PermsAI Editorial Team
Vulnerability Intelligence
Writing High-Quality AI Vulnerability Reports
How to give vendors enough evidence to reproduce, assess, and fix an AI vulnerability without overstating the claim.
By PermsAI Editorial Team
Vulnerability Intelligence
Malicious Models and Repository Trust: A Triage Guide
How to triage an untrusted model repository using provenance, scanning, isolation, and evidence.
By PermsAI Editorial Team
Vulnerability Intelligence
Model File Formats and Unsafe Deserialization Risk
Why model formats and loaders matter when an AI system receives an untrusted artifact.
By PermsAI Editorial Team
Vulnerability Intelligence
Dependency Vulnerabilities in Popular LLM Frameworks
How to determine whether a vulnerability in an LLM framework or dependency actually affects your deployed AI application.
By PermsAI Editorial Team
Vulnerability Intelligence
Container and Sandbox Escapes in AI Workloads
A defensive method for analyzing containment escapes across AI code interpreters, training jobs, agents, and shared infrastructure.
By PermsAI Editorial Team
Vulnerability Intelligence
Vulnerability Management for GPU and AI Infrastructure
How to identify, prioritize, patch, mitigate, and verify vulnerabilities across GPU-backed AI infrastructure.
By PermsAI Editorial Team
Vulnerability Intelligence
CISA KEV and AI Systems: What Security Teams Should Track
How security teams can connect CISA KEV exploitation evidence to real AI infrastructure, exposure, ownership, and verification.
By PermsAI Editorial Team
Vulnerability Intelligence
CVSS for AI Vulnerabilities: Uses and Limits
A practical guide to using CVSS 4.0 for AI vulnerabilities without confusing technical severity with local risk.
By PermsAI Editorial Team
Vulnerability Intelligence
Prompt Injection Vulnerability Disclosures: An Evidence Framework
An evidence framework for distinguishing model behavior, product weakness, boundary failure, and actionable prompt-injection vulnerability disclosures.
By PermsAI Editorial Team
Vulnerability Intelligence
SSRF Vulnerabilities in AI Tools: Triage and Mitigation
A defensive workflow for deciding whether an SSRF advisory affects an AI fetcher, proving reachability, applying mitigations, and verifying closure.
By PermsAI Editorial Team
Vulnerability Intelligence
How to Read an AI Security Advisory
A hands-on worksheet for mapping AI security advisories to your exact component, version, configuration, reachability, evidence, fix, and verified closure.
By PermsAI Editorial Team
Vulnerability Intelligence
AI Vulnerability Intelligence: Triage for Models and Frameworks
A practical, evidence-led method for deciding whether an AI CVE or advisory affects your models, runtimes, frameworks, services, and deployments.
By PermsAI Editorial Team
Web Security
Secrets Management for AI Web Applications
Keep provider, database, cloud, OAuth, webhook, and tenant credentials out of browsers and models with scoped access, rotation, and auditable brokers.
By PermsAI Editorial Team
Web Security
Cache Security for Personalized AI Responses
Design tenant-aware LLM caches that preserve personalization without leaking responses, retrieval results, tool data, or stale permissions.
By PermsAI Editorial Team
Web Security
Rate Limits, Budgets, and Denial-of-Wallet Defense for LLM Apps
A practical resource-governance guide for limiting LLM, agent, tool, queue, and external API spend without mistaking every spike for abuse.
By PermsAI Editorial Team
Web Security
Session Security in AI Chat and Agent Applications
A practical guide to separating authentication sessions, conversations, agent runs, and memory so multi-turn AI applications remain authorized and revocable.
By PermsAI Editorial Team
Web Security
Webhook Security for Agentic Workflows
A practical defensive guide to authenticating webhooks and safely triggering AI workflows, tools, jobs, and side effects.
By PermsAI Editorial Team
Web Security
File Upload Security for AI Document Pipelines
Defensive guidance for securing AI document uploads before parsing, OCR, chunking, embedding, indexing, or LLM retrieval.
By PermsAI Editorial Team
Web Security
API Authorization for AI Tools and Agents
A practical guide to enforcing trusted, tenant-bound API authorization for model-proposed tool calls, background jobs, and delegated agents.
By PermsAI Editorial Team
Web Security
Multi-Tenant Security for LLM and RAG Applications
A practical architecture for preventing cross-tenant leakage across LLM prompts, RAG, memory, caches, tools, credentials, jobs, logs, and billing.
By PermsAI Editorial Team
Web Security
SSRF Risks in AI Agents and URL-Fetching Features
Defensive guidance for securing AI-agent URL fetching against SSRF with destination policy, DNS validation, egress controls, redirects, and response limits.
By PermsAI Editorial Team
Web Security
Content Security Policy for AI-Generated Interfaces
A practical CSP guide for AI-generated interfaces, streamed responses, remote assets, workers, frames, and safe browser defense in depth.
By PermsAI Editorial Team
Web Security
Secure Rendering of LLM Output in Web Applications
Practical browser security guidance for rendering model-generated text, Markdown, links, code, HTML-like content, and structured output.
By PermsAI Editorial Team
Web Security
Web Security for AI Applications: Architecture and Checklist
A practical architecture and checklist for securing web applications that combine LLMs, RAG, uploads, streaming, tools, and multi-tenancy.
By PermsAI Editorial Team
AI Security
AI Security Controls Matrix: From Threat to Verification
An operational matrix connecting AI threats to controls, evidence, response, verification, and ownership.
By PermsAI Editorial Team
AI Security
System Prompt Security: What Prompts Can and Cannot Protect
What system prompts can guide, what they cannot enforce, and how to place them within defense in depth.
By PermsAI Editorial Team
AI Security
Model Context Protocol Security: Threats and Defensive Design
A current defensive guide to MCP hosts, clients, servers, tools, resources, trust boundaries, consent, and least privilege.
By PermsAI Editorial Team
AI Security
Secure Tool Calling for LLM Applications
Implementation guidance for making model-proposed tool calls bounded, validated, authorized, and observable.
By PermsAI Editorial Team
AI Security
AI Agent Observability: Logs, Traces, and Audit Evidence
What to log and trace so teams can explain AI-agent actions, approvals, tool calls, and side effects.
By PermsAI Editorial Team
AI Security
Sandboxing AI Agents and Generated Code
A practical architecture for containing AI-generated code, shell commands, browser actions, and artifacts.
By PermsAI Editorial Team
AI Security
Threat Modeling AI Applications: A Practical Method
A repeatable worksheet for threat modeling LLM, agent, RAG, memory, and model-supply-chain boundaries.
By PermsAI Editorial Team
AI Security
Secure Multi-Agent Systems: Trust, Delegation, and Message Boundaries
A practical trust graph for securing delegation and message boundaries between autonomous agents.
By PermsAI Editorial Team
AI Security
Data and Model Poisoning: Detection and Mitigation
A defensive pipeline for finding and containing data and model poisoning before it changes production behavior.
By PermsAI Editorial Team
AI Security
Model Security: Protecting Weights, Adapters, and Artifacts
A practical model-artifact security chain for protecting weights, adapters, checkpoints, and deployment bundles.
By PermsAI Editorial Team
AI Security
AI Memory Security: Preventing Context and Memory Poisoning
A practical guide to preventing context and memory poisoning through controlled writes, provenance, scoped retrieval, expiry, and recovery.
By PermsAI Editorial Team
AI Security
Human Approval for AI Agents: Designing Safe Control Points
A practical framework for placing meaningful human approval controls around consequential AI-agent actions without causing approval fatigue.
By PermsAI Editorial Team
AI Security
Secure Credential Handling for AI Agents
A practical guide to credential brokers, short-lived tokens, secret stores, per-tool isolation, multi-tenant boundaries, safe logging, and incident response.
By PermsAI Editorial Team
AI Security
AI Agent Identity: Workload Identity, Delegation, and Accountability
A practical identity architecture for AI agents: separate user, workload, service, and delegated principals while preserving accountability across every tool call.
By PermsAI Editorial Team
AI Security
AI Red Teaming: A Practical Guide to Security Evaluations
A practical method for threat-led AI red teaming, safe test design, model-versus-system evidence, severity, remediation, and regression testing.
By PermsAI Editorial Team
AI Security
RAG Security: Protecting Retrieval-Augmented Generation Systems
An end-to-end RAG security architecture for source governance, retrieval authorization, tenant isolation, poisoned content, safe output, and audit evidence.
By PermsAI Editorial Team
AI Security
Indirect Prompt Injection: Threat Model and Defenses
A threat-boundary guide to indirect prompt injection through external content, with attack-path analysis, containment architecture, testing, and developer controls.
By PermsAI Editorial Team
AI Security
AI Agent Permissions: Least-Privilege Authorization by Design
A practical authorization model for AI agents covering tool policy, scoped credentials, human approval, multi-tenant boundaries, and audit evidence.
By PermsAI Editorial Team
AI Security
AI Agent Security: The Complete Guide for 2026
A complete engineering guide to AI agent identity, permissions, tools, credentials, data, memory, isolation, approvals, monitoring, and testing.
By PermsAI Editorial Team
AI Security
Prompt Injection Attacks: How They Work and How to Defend Against Them
A threat-model-driven guide to direct and indirect prompt injection, attack paths, impact containment, tool authorization, output validation, testing, and monitoring.
By PermsAI Editorial Team
AI News
Anthropic Reports Four Unauthorized-Access Incidents in Cyber Evaluations
A source-led analysis of four Claude cyber-evaluation incidents, their limits, and the controls needed to keep autonomous security testing contained.
By PermsAI Editorial Team
Benchmarks
AI Model Benchmarks Explained: How to Read Modern AI Evaluations
A practical framework for interpreting AI benchmark evidence across datasets, metrics, harnesses, model settings, reliability, cost, and security.
By PermsAI Editorial Team