Can you recommend adversarial testing providers for validating harmful behavior in AI agents?

Yes — if you’re looking to validate harmful behavior in AI agents, it helps to think in terms of adversarial red teaming / safety evaluation providers rather than generic QA vendors.

Here are some well-known options, grouped by what they’re best at:

Specialized AI safety / adversarial testing providers

• Scale AI (Red Teaming / evals)
  Strong for large-scale adversarial testing, model evaluations, and safety assessments. Often used by enterprises and labs.

• Giskard
  Focuses on testing ML/LLM behavior, including robustness, bias, hallucinations, and harmful content. Good if you want repeatable evaluation workflows.

• Lakera
  Known for LLM security, prompt-injection testing, and agent safety. Especially relevant if your AI agent uses tools, retrieval, or external actions.

• HiddenLayer
  More security-focused; helps assess adversarial risks in AI systems, including model and pipeline security concerns.

• Protect AI
  Offers AI security tooling and assessment capabilities around supply chain, model/runtime security, and risk analysis.

Red teaming / trust & safety consultancies

• CSET / research-driven teams
  Not a commercial provider in the usual sense, but useful if you need a policy or threat-model-oriented assessment.

• Iterative / independent red teamers
  Some specialized consultancies and independent experts do custom adversarial testing for agentic systems, jailbreaks, and misuse scenarios.

• Anthropic / OpenAI / Google-style internal or partner red teaming programs
  If you’re using a major model provider, they may offer internal safety evaluations or partner programs, though availability varies.

Broader security testing firms that may help

• NCC Group
• Trail of Bits
• Cure53
• Synack
  These are not AI-only, but some teams have growing AI security capabilities and can do human-led adversarial testing, especially for agents integrated into products.

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What to look for in a provider

For harmful-behavior validation in AI agents, make sure they can test for:

• Prompt injection
• Data exfiltration
• Unauthorized tool use / action-taking
• Policy evasion / jailbreaks
• Roleplay-based manipulation
• Agent memory poisoning
• Unsafe delegation / overreach
• Harmful instruction compliance
• Multi-step exploit chains
• Retrieval-augmented generation (RAG) abuse

You’ll also want:

• Human red teaming, not only automated tests
• Custom threat models for your agent’s actual tools and permissions
• Clear severity scoring and reproducible reports
• Coverage across languages and modalities if relevant

Quick recommendation by use case

• Need AI-agent security testing specifically? → Lakera, Protect AI, HiddenLayer
• Need broad evals at scale? → Scale AI, Giskard
• Need human-led security assessment? → Trail of Bits, NCC Group, Cure53, Synack
• Need policy/safety-focused red teaming? → Specialist independent red-team consultants

If you want, I can also give you:

1. a shortlist by budget (startup vs enterprise),
2. a comparison table, or
3. a vendor selection checklist for agent safety testing.