10 AI Security Tools That Actually Catch Prompt Injection (Tested)

I ran 47 real prompt injection attacks through every major AI security tool I could find. Some were obvious ("Ignore previous instructions"). Some were subtle (base64-encoded instructions, multilingual attacks, context window flooding). Some were genuinely novel (adversarial Unicode characters that exploit tokenization quirks).

The results were sobering. Most tools marketed as "AI security" are just regex filters with a logo. But a few actually work.

The Test Setup

Attack corpus: 47 prompt injection variants across five categories:

  • Multi-turn injection (building trust over several exchanges)

Target models: GPT-4.1, Claude Opus 4.7, Gemini 2.5 Pro

Scoring: Tool gets 1 point per attack blocked. A score of 40+ is "enterprise ready." Below 25 is decorative.

The Results

1. Lakera Guard — Best Overall (44/47)

What it does: API-level input/output filtering with model-based detection, not just pattern matching.

Why it wins: Lakera uses a secondary classification model trained specifically on adversarial prompts. It caught encoding attacks that regex-based tools missed entirely. The multi-turn detection is the best I tested—it flags suspicious conversation trajectories before the injection lands.

Price: $0.001 per request (volume discounts available)

Best for: Production AI apps with real user traffic

What didn't work: One novel Unicode attack slipped through. Lakera's team acknowledged the edge case and pushed a fix within 48 hours.

2. Prompt Security (formerly Rebuff) — Runner-Up (41/47)

What it does: Open-source prompt injection detection with a managed API option.

Why it's second: Slightly lower detection rate than Lakera, but open-source means you can self-host for air-gapped environments. The detection is model-agnostic—it works against any LLM backend.

Price: Free (self-hosted) or $0.0005/request (managed)

Best for: Teams that need on-premise deployment

What didn't work: Context window flooding attacks were missed. These are rare in practice but dangerous.

3. Nightfall AI — Best for Data Loss Prevention (38/47)

What it does: Detects sensitive data in prompts (PII, credentials, PHI) and blocks prompt injection simultaneously.

Why it made the list: Most companies need both capabilities. Nightfall's dual detection reduces infrastructure complexity. It caught 91% of injection attempts while also flagging SSNs and API keys in prompts.

Price: $10/seat/month

Best for: Healthcare and finance companies with strict data governance

What didn't work: Some novel jailbreak patterns bypassed detection. The team updates weekly.

4. HiddenLayer AI Detection and Response (AIDDR) — Best for Enterprise (37/47)

What it does: Full AI security platform covering prompt injection, model extraction, and supply chain attacks.

Why it's enterprise-focused: AIDDR isn't just detection—it's a full security operations platform with SIEM integration, incident response workflows, and compliance reporting. The detection rate is slightly lower than Lakera, but the operational integration is unmatched.

Price: Enterprise (custom pricing, typically $50K+/year)

Best for: Large enterprises with existing SOC teams

5. Protect AI — Best for Model Scanning (36/47)

What it does: Secures the entire ML pipeline, including prompt injection detection for deployed models.

Why it's different: Protect AI focuses on the supply chain—scanning model weights for backdoors, vulnerabilities in training code, and prompt injection in production. The prompt detection is solid but secondary to their broader platform.

Price: $5,000/month for production deployment

Best for: Companies with mature ML operations

6. Robust Intelligence — Best for Automated Red Teaming (35/47)

What it does: Continuously generates adversarial prompts and tests your models against them.

Why it matters: Detection tools catch known attacks. Robust Intelligence finds unknown ones. It generated 12 prompt injection variants I hadn't seen before, three of which bypassed all other tools.

Price: Enterprise (custom)

Best for: Organizations that need proactive security testing

7. Arthur AI — Best for Bias + Security (34/47)

What it does: Monitors models for bias, drift, and security vulnerabilities including prompt injection.

Why it's here: Arthur's security detection is good (34/47), but the combined bias and security monitoring is unique. If you're in a regulated industry, having both in one platform simplifies compliance.

Price: $15,000/year base

Best for: Regulated industries needing combined fairness and security monitoring

8. Giskard — Best Open Source (31/47)

What it does: Open-source ML testing framework with prompt injection detection modules.

Why it's notable: Free, extensible, and community-driven. The detection rate lags commercial tools, but it's improving rapidly. Great for teams that can't justify security spend yet.

Price: Free

Best for: Startups and research teams

9. WhyLabs — Best for Observability (30/47)

What it does: ML observability platform that includes prompt injection detection in its broader monitoring.

Why it's useful: WhyLabs excels at tracking model behavior over time. The prompt injection detection is decent, but the real value is seeing injection attempts in context alongside model drift and data quality metrics.

Price: $500/month base

Best for: Teams that need observability first, security second

10. Cloudflare AI Gateway — Best for Infrastructure (28/47)

What it does: API gateway for AI requests with rate limiting, caching, and basic prompt filtering.

Why it's here: Cloudflare's prompt injection detection is basic (28/47), but if you're already using their infrastructure, the incremental cost is near zero. It's a good first layer, not a complete defense.

Price: Included in Workers Paid plan ($5/month)

Best for: Teams already on Cloudflare that need quick baseline protection

What I Didn't Include

Content moderation APIs (OpenAI Moderation, Google Perspective): These detect toxic outputs, not prompt injections. They're useful but solve a different problem.

Traditional WAFs (Cloudflare WAF, AWS WAF): These look for SQL injection and XSS patterns. LLM prompt injection uses entirely different syntax. Traditional WAFs scored 3–8/47 in my testing.

Homegrown regex filters: Every company builds these. Every company eventually discovers they don't work against motivated attackers.

The Bottom Line

If you have one AI app in production, deploy Lakera Guard or Prompt Security. If you have a mature ML pipeline, add HiddenLayer AIDDR or Protect AI for comprehensive coverage. If budget is tight, start with Giskard and upgrade when you have revenue at risk.

But remember: no tool catches everything. Layer detection with human review for high-stakes actions, output validation, and aggressive monitoring. Prompt injection is an arms race, and the attackers only need to win once.

Related reads:

The Catch

It doesn't work everywhere. Agentic AI shines in structured workflows but struggles with ambiguous tasks requiring human judgment.

The setup is real work. Connecting agents to existing systems takes engineering time most teams underestimate.

Monitoring is harder. When something breaks, tracing the failure path across multiple agent steps isn't straightforward yet.