Giskard AI Security

Why pentests miss AI agent failures, and how a team of sandboxed AI agents red teams them: method, benchmark results and current limits

PHP2Shell, Node2Shell and LiteLLM 1.107.0 hit in one week. What happened, whether we were exposed, and five controls to close supply chain gaps

AI Security teams test techniques like prompt injection, while incident records point to hallucination. Why AI risk modeling should start from the harm.

Giskard's StereoTales paper, on harmful stereotypes in 23 frontier LLMs across 10 languages, is accepted at NeurIPS 2026.

A pentest proves an exploit worked or failed. An LLM agent gives no such proof. Learn the differences between traditional pentesting and AI red teaming.

NeMo, Lakera, Bedrock, Azure, Cisco, Giskard: nine AI guardrail tools scored on context-awareness, agentic coverage, quality, and policy-as-code.

Giskard v.3.0 red teams any AI agent that speaks JSON, not just chatbots. The release includes multi-turn scenarios, and custom LLM Judge checks.

Field-tested guidance for integrating AI security audits into enterprise AI projects. What AI red teaming is, how an audit runs, and typical failure modes.

OWASP's 2026 Top 10 for LLM Applications: reordered risks, evidence-backed ranking, renamed Hidden Context Exposure, and how each entry maps to agentic AI and red teaming.

We planted 17 vulnerabilities in a banking AI agent and pointed four AI red teaming tools at it. We analyse the results, and the non-detected failures.

Giskard is SOC 2 Type II, GDPR, and HIPAA compliant. The Trust Center holds compliance evidence; status.giskard.ai shows live status and measured uptime; enterprise SLAs define uptime and support commitments. Here's what to request in vendor review.

On July 16, 2026, an autonomous AI agent breached Hugging Face, & safety filters blocked the company's own investigation. We analyze how the attack worked.

Promptfoo is strong for YAML eval in pull requests. Compare agent-native red teaming with multi-turn probes and an integrated fix pipeline beyond PR checks alone.

DeepTeam is a solid Python guardrails library for eval silos. Compare alternatives with shared Hub datasets, task owners, and CI regression when security and quality merge.

Deepchecks is strong for LLM eval and production monitoring workflows. Compare attack-first red teaming with automated adversarial generation and a built-in fix loop.

Splx AI pairs red teaming with Agentic Radar hardening. Compare alternatives that combine security probes with RAG quality scans and regression tests in one loop.

Mindgard offers managed continuous red teaming with expert support. Compare in-product fix loops, Hub datasets, and CI regression when scans need owners and tests.

Lasso Security excels at MCP inventory and agent discovery scans. Compare alternatives that turn findings into tasks, regression tests, and guardrails teams can ship.

Garak ships 120+ open-source model probes for security testing. Compare alternatives with multi-turn jailbreaks and tool-call coverage when agents leave demo stage.

PyRIT offers flexible Azure attack orchestration from Microsoft's red team. Compare productized agent red teaming without hand-rolling pipelines or maintaining eval code.