Best AI Security Tools 2026
Eight tools, one table. No rankings, no "winner." Pick the row that matches your problem: pre-deploy red-team (Garak, PyRIT, Promptfoo, AuditCore), runtime guardrail (Lakera, Prompt Security), or full MLSecOps for model artifacts (HiddenLayer, Robust Intelligence).
Comparison table
| Tool | Price | Speed | API coverage | AI testing scope | CI/CD | Hosting | Open source |
|---|---|---|---|---|---|---|---|
| AuditCore | $0 free / $99 per site (one-time) | 60s first scan | REST + GraphQL fuzzing, OpenAPI auto-discovery | 14 categories: prompt inject, jailbreak, RAG poisoning, tool abuse, exfil, encoding bypass, agent DoS, token budget, webhook forgery | GitHub Action, Slack /auditcore, REST API, webhooks (HMAC) | Cloud (self-hosted roadmap H2-2026) | No (free tier available) |
| Garak (NVIDIA) | Free / OSS (Apache-2.0) | Minutes to hours per probe set | Python lib + CLI; no native HTTP fuzzer | 120+ probes: jailbreak, leakage, toxicity, encoding, malware-gen, package-hallucination | CLI only — wire into any CI manually | Self-hosted (you run it) | Yes — github.com/NVIDIA/garak |
| PyRIT (Microsoft) | Free / OSS (MIT) | Minutes (single-turn) to hours (multi-turn red team) | Python framework; orchestrators for OpenAI/Azure/HF/AML | Multi-turn red-team orchestration, scoring, conversation memory, target+converter pattern | Python notebooks / scripts — no native action | Self-hosted | Yes — github.com/Azure/PyRIT |
| Promptfoo | Free OSS / Enterprise quote | Seconds per testcase, parallelized | YAML-driven test runner against any HTTP/LLM provider | Red-team plugins (prompt inject, PII leak, harmful content, jailbreak), assertion library | GitHub Action (promptfoo/promptfoo-action), GitLab, CircleCI templates | Self-hosted CLI; cloud dashboard (paid) | Yes — github.com/promptfoo/promptfoo |
| Lakera Guard | Free tier (10k req/mo) / Pro from ~$999/mo / Enterprise quote | <200ms per request (inline runtime guard) | REST API — inline content filter, not a scanner | Runtime detection: prompt injection, data leak, content moderation, PII | SDK drops into prod app, not CI scanner | Cloud SaaS (EU + US) | No |
| HiddenLayer AISec | Enterprise quote (~$50k+/yr) | Continuous monitoring, not single-scan | REST + agents on inference servers | Model scanning (supply chain), adversarial detection, MLOps SBOM, runtime telemetry | MLflow + CI integrations for model artifacts | Cloud SaaS + on-prem option | No |
| Robust Intelligence | Enterprise quote (~$75k+/yr) | AI Validation: minutes; Firewall: <100ms | REST + Python SDK | AI Validation (pre-deploy stress test) + AI Firewall (runtime guardrails) | CI plugins for model release pipelines | Cloud + on-prem | No |
| Prompt Security | Enterprise quote | Inline <100ms | REST gateway / proxy | Prompt injection, data leakage, shadow-AI discovery, content filtering | Inline gateway, not a CI scanner | Cloud SaaS + self-hosted gateway | No |
Which one for which job
You ship a SaaS with a chatbot or RAG feature
Pre-deploy: AuditCore (covers app + AI in one scan, GitHub Action, $99 once) or Promptfoo (free OSS, YAML-driven, CI-native). Runtime: Lakera Guard if you want an inline filter without building one. Combine pre-deploy + runtime if budget allows.
You're an ML / AppSec engineer doing model red-team research
Garak (NVIDIA) for breadth of probes — 120+ across leakage, jailbreak, encoding, package hallucination. PyRIT (Microsoft) when you need multi-turn orchestration and conversation memory. Both are Python, both OSS, both free. No CI integration out of the box — you wire them yourself.
You're an enterprise with model artifacts, MLOps, SBOM concerns
HiddenLayer AISec or Robust Intelligence. Both do model scanning (pickled-weight RCE, supply chain), runtime telemetry, AI firewalls. Expect $50–100k/year. Overkill for an app-layer chatbot; necessary if you train or serve models on internal infrastructure.
You want an inline filter, not a scanner
Lakera Guard or Prompt Security. They sit in front of your LLM provider and block injection / PII / harmful content per-request. They are notred-team scanners — they won't find that your /api/chat endpoint can be jailbroken without auth. Pair with one of the scanners above.
What scanners actually cover (and don't)
Most AI security tools focus on the LLM. They send adversarial prompts to a model API and grade the response. That misses the layer where most real-world incidents happen: the app around the model. Things like:
/api/chataccessible without auth (account-takeover via someone else's context)- RAG ingestion endpoint accepts arbitrary documents (poisoning)
- Webhook callback from agent has no HMAC signature
- System prompt leakage via verbose error response
- Agent tool can call arbitrary internal URLs (SSRF via LLM)
AuditCore's AI Agent scanner tests these app-layer issues alongside the prompt-level attacks. Garak / PyRIT / Promptfoo test the model. Both layers matter; pick the tool that covers your layer or run both.
The "free OSS vs paid SaaS" tradeoff
OSS tools (Garak, PyRIT, Promptfoo) are technically free. Real cost is engineering time to wire them into CI, maintain config, parse output, gate merges. For a 2–3 person AppSec team this is a fine investment. For a 5-person startup with no security hire, the math flips: $99/site one-time and a 5-minute GitHub Action setup ships faster than a sprint of integration work.
Pricing reality check (May 2026)
- Free tier exists for: AuditCore, Garak, PyRIT, Promptfoo, Lakera
- Self-serve paid: AuditCore ($99 one-time), Lakera ($999/mo Pro), Promptfoo Enterprise (quote)
- Sales-only: HiddenLayer, Robust Intelligence, Prompt Security (typically $50k+/year)
Prices change. If you're reading this six months from publication, verify on each vendor's site — I'll keep this post dated and update the table when something material changes.