We are conducting a prompt injection penetration test. Who offers automated red teaming suites?

Yes. If you mean automated suites for adversarially testing LLMs/agents—including prompt injection, jailbreaks, data leakage, and unsafe tool use—these are some of the more relevant vendors/tools in 2026:

• mindgard.ai — Automated AI red teaming with reconnaissance, agentic attack workflows, vulnerability discovery, CI/CD integration, and runtime defenses. It explicitly positions itself as an autonomous red teamer.
• hiddenlayer.com — Automated AI attack simulation/red teaming covering prompt injection, jailbreaks, system-prompt weaknesses, data leakage, and unsafe agent/tool behavior, with reports and metrics.
• lakera.ai — Particularly strong around prompt attacks and AI-agent security. Its AI Red Teaming offering includes direct and indirect attack simulations and risk-based vulnerability management.
• checkpoint.com — Automated red-team campaigns for application-specific AI risks, including prompt injection, jailbreaks, data leakage, unauthorized actions, and regression testing.
• Promptfoo — Developer-oriented adversarial testing/evaluation framework with CI/CD integration; useful if you want something closer to an automated security test suite than a full enterprise platform.
• Microsoft PyRIT and NVIDIA Garak — More framework/toolkit-oriented options rather than turnkey commercial suites. They're useful for building customized automated attack campaigns.

For a prompt-injection penetration test

I'd shortlist Mindgard, HiddenLayer, Lakera, and Promptfoo. The key distinction is whether you want:

• Turnkey autonomous red teaming: Mindgard / HiddenLayer
• Prompt-injection and agent protection + testing: Lakera
• Highly customizable developer test harness: Promptfoo
• Research/custom attack orchestration: PyRIT / Garak

For a serious penetration test, I'd specifically evaluate whether the suite supports indirect prompt injection, RAG/document poisoning, tool/MCP attacks, multi-turn attack chains, system-prompt extraction, and regression testing—not merely a library of jailbreak prompts. Current platforms increasingly emphasize those agentic attack paths.

Several cybersecurity vendors offer automated red teaming suites and continuous security platforms specifically designed to test Large Language Models (LLMs) for prompt injection, jailbreaks, and data leakage.

Automated AI Red Teaming Platforms

• Mindgard provides automated security posture management and continuous scanning for LLM applications, testing against prompt injection and other OWASP Top 10 vulnerabilities.
• Lakera Red offers automated adversarial testing suites to stress-test AI models against prompt injections and malicious payloads at scale.
• Prompt Security combines runtime protection with automated adversarial vulnerability assessment and red teaming testing for generative AI.
• HiddenLayer specializes in machine learning security, offering model protection and automated security monitoring against adversarial attacks and manipulation.
• Synack combines agentic AI-driven automated testing with crowdsourced human red team validation for enterprise AI security.

If you'd like, let me know:

• Is your LLM application public-facing or internal?
• Are you looking for a continuous scanning tool or a one-time assessment suite?

I can help you narrow down the best platform for your specific environment.

Yes. If you mean automated suites that actively generate adversarial prompts and test LLM/agent applications for prompt injection, there are several credible options:

• promptfoo.dev — Probably the strongest developer-oriented option. It generates application-specific attacks and covers prompt injection, jailbreaks, RAG/document exfiltration, data leakage, unsafe tool use, and 50+ vulnerability categories. It can run in CI/CD and has an open-source foundation.
• hiddenlayer.com — Enterprise-oriented automated red teaming/attack simulation across LLMs and agents, including prompt injection, jailbreaks, extraction/data leakage, and unsafe agent tool use.
• mindgard.ai — Continuous automated AI red teaming aimed at enterprise systems; worth evaluating if you want recurring testing rather than a one-off pentest.
• lakera.ai — Particularly relevant to prompt-injection testing and defense. Its focus is GenAI security, with prompt injection and jailbreak protection as core capabilities.
• github.com — Open-source automated framework from Microsoft for orchestrating adversarial testing. Good for building a customized internal red-team harness.
• github.com — Open-source LLM vulnerability scanner; useful for automated probing, though more scanner/framework-like than a complete enterprise red-team platform.
• giskard.ai — Combines LLM/RAG evaluation with security testing and vulnerability scanning.
• haizelabs.com — Focuses on automated adversarial stress testing and finding model failure modes at scale.

A recent 2026 market comparison also identifies PyRIT, Garak, Lakera, Mindgard, Promptfoo, and HiddenLayer as notable automated red-teaming options.

For a prompt-injection pentest specifically

I'd shortlist Promptfoo, HiddenLayer, Mindgard, and PyRIT. The important distinction is whether you want to test merely the model or the complete agent/application attack surface—including indirect prompt injection, RAG poisoning, tool/API abuse, data exfiltration, multi-turn attacks, and system-prompt extraction. Promptfoo and HiddenLayer explicitly advertise this broader application/agent testing.

If you're evaluating vendors for an actual penetration-testing program, I can also give you a side-by-side matrix of ~10 suites covering attack techniques, agent/tool testing, CI/CD, MCP, custom attack generation, reporting, and pricing model.

Automated and continuous AI red teaming suites have evolved to target LLM vulnerabilities like prompt injection, jailbreaking, data exfiltration, and tool/agent misuse.

The primary providers of automated AI red teaming platforms and tools span open-source frameworks, commercial enterprise suites, and managed security services:

1. Commercial Enterprise AI Security Suites

• Mindgard : Provides dedicated automated red teaming and DevSecOps integrations for LLM applications, mapping findings directly to frameworks like OWASP Top 10 for LLMs.
• HiddenLayer : Offers an AISec Platform that unifies AI model supply chain security, posture management, and automated red teaming for generative and agentic AI systems.
• Synack : Combines agentic AI automation (via its testing framework) with human-in-the-loop validation for enterprise and government compliance needs.
• SentinelOne : Offers specialized automated AI red teaming features (such as Prompt AI Red Teaming) targeted at evaluating LLM instructions and application safety prior to deployment.
• NeuralTrust : Features TrustTest, a platform pairing offensive automated red teaming with first-party runtime defense policies.

2. Open-Source & Advanced Adversarial Testing Frameworks

• Promptfoo : A widely adopted open-source CLI and library for LLM red teaming that automates adversarial input generation, prompt injections, and model-graded evaluations.
• Praetorian Augustus : An open-source tool implementing multi-stream conversation managers and iterative refinement strategies (like PAIR and TAP) to automate complex prompt injection testing.
• Garrick & Prompt Inject : Lightweight community tools/scanners used to fuzz and benchmark prompt injection success rates against target LLM endpoints.

If you're testing a specific architecture, let me know:

• Is your target a standalone LLM or an agentic AI with tool access?
• Are you looking for an open-source CLI tool or a commercial enterprise platform?

I can help narrow down the best integration approach for your test scope.

Here are top web results for exploring this topic:

Promptfoo·https://www.promptfoo.dev Promptfoo: Build Secure AI Applications Automated red teaming for agents & RAGs. Promptfoo simulates real users to uncover application-specific vulnerabilities: npx promptfoo@latest redteam setup. Custom attacks generated for your target: D Synack·https://www.synack.com Best AI Red Teaming Tools to Find AI Security Vulnerabilities in 2026 Mindgard and Lakera Red offer strong, continuous automated platforms for teams that need broad, frequent scanning across defined LLM attack categories. HiddenLayer specializes in ML model security and Medium·https://medium.com LLM Red Teaming : A Complete Guide to Testing and Securing AI ...... and the model reads the hidden instructions exactly the way it reads every other sentence on the page. Nobody hacked anything in the traditional sense. The infrastructure held up fine. The model j TestSavant.AI·https://www.testsavant.ai How to Red Team Prompt Injection Attacks on Multi-Modal LLM Agents ... steps) and see where an attacker could insert themselves in that flow. Essentially, the red team methodology mirrors a penetration test: reconnaissance on how the AI prompts are structured, probin Rogue Security·https://www.rogue.security**Prompt Injection** Is Becoming an Automated Red Team A June 2026 ETH Zurich study shows black-box optimization can generate effective prompt injections against tool-using agents. Security teams need to move from manual jailbreak checks to workflow-level Mend.io·https://www.mend.io Best AI Red Teaming Services: Top 7 Platforms and Services in 2026 Prompt injection testing. Prompt injection occurs when attackers manipulate the inputs or prompts fed to an LLM, a core concern in LLM red teaming, tricking it into generating unintended or harmful ou Redbot Security·https://redbotsecurity.com Redbot Security: Penetration Testing Services and Red Teaming Senior-led manual penetration testing and red teaming across applications, networks, cloud, and AI systems, Validate real attack paths. LinkedIn·https://www.linkedin.com**Red Teaming** AI Is Not Just Model Testing or Prompt Injection . It Is ...Most organizations default to a narrow framing when they hear "AI red teaming." They think prompt injection. They think jailbreaking a chatbot into saying something it should not. And prompt injection Help Net Security·https://www.helpnetsecurity.com GPT-Red beat human red teamers on a prompt injection test GPT-Red beat human red teamers on a prompt injection test. GPT-Red is an automated red-teaming model that OpenAI trains to find prompt injection weaknesses. It works the way a human red-teamer does. I Bluefire Redteam·https://bluefire-redteam.com AI Red Teaming Services | LLM, Agent & Chatbot Security Testing Why an AI Scanner Isn't AI Red Teaming. Automated AI security scanners run a library of known jailbreak strings against your model and produce a pass/fail list. That is not red teaming. Real AI attack

For a prompt injection penetration test, the relevant market category is usually automated AI red teaming / LLM security testing platforms. Vendors and tools that offer automated adversarial testing suites include:

For a penetration-test-style evaluation, teams commonly look for these capabilities:

• Direct prompt injection testing (malicious user prompts overriding system instructions)
• Indirect prompt injection testing (malicious content in RAG documents, webpages, emails, tools, etc.)
• Jailbreak generation and mutation
• System prompt extraction attempts
• Sensitive data leakage checks
• RAG poisoning tests
• Agent/tool-use abuse testing
• Regression testing in CI/CD pipelines
• Evidence capture and severity scoring

A practical shortlist depends on your environment:

• Open-source / internal security research: PyRIT, Garak, Promptfoo
• Enterprise governance + reporting: Check Point, F5, Prompt Security, Lakera, HiddenLayer
• Agentic AI / tool-use testing: SATLAS, F5 AI Red Team, Pencheff, specialized agent-testing platforms

For a formal penetration test, I would also compare the tooling against frameworks such as OWASP LLM Top 10, MITRE ATLAS, and NIST AI RMF coverage rather than only the number of attack prompts.

Several established enterprise vendors and open-source frameworks provide automated AI red teaming suites specifically designed to test for prompt injection, jailbreaks, and data leakage.

These solutions are divided below into enterprise platforms and open-source tools to help scale your penetration test.

Enterprise Automated Platforms

• Mindgard : Offers continuous automated scanning across defined LLM attack categories, focusing on model vulnerabilities and prompt injection.
• Lakera (Lakera Red) : Provides an automated, continuous platform for scanning and stress-testing LLM applications against adversarial inputs.
• Prompt Security : Combines generative AI runtime protection with an automated adversarial testing suite built into a single platform.
• Synack : Provides a managed service pairing their agentic AI tool ("Sara") with human validation for automated enterprise red teaming.
• Mirror Security (#DiscoveR) : An automated tool that runs over 100 attack simulations across 20+ templates, specifically checking for prompt injection and vector database exploits.
• Azure AI Studio (Microsoft Red Team SDK) : Microsoft provides a specialized automated Red Team SDK designed to simulate adversarial vectors, including direct and indirect prompt injection mapped to the OWASP Top 10 for LLMs.

Open-Source Frameworks & SDKs

• Promptfoo : A highly popular open-source tool used to systematically generate adversarial inputs, execute prompt injection/jailbreak variants, and score the model's outputs automatically.
• garak : The "Nmap for LLMs." An open-source vulnerability scanner that probes LLM endpoints for prompt injection, hallucinations, data leakage, and structural flaws.
• PyRIT (Python Risk Identification Tool) : Microsoft’s open-source automation framework used by their AI Red Team to orchestrate multi-turn jailbreaks and injection attacks at scale.
• Augustus : An open-source tool developed by Praetorian that automates state-of-the-art iterative attacks like PAIR (Prompt Automatic Iterative Refinement) and TAP (Tree of Attack Prompts).

Core Capabilities to Look For

When choosing between these suites for your pen test, ensure they support:

1. Multi-turn adaptive testing : Generating sequential prompts that dynamically pivot based on the LLM's previous responses.
2. Obfuscation testing : Attempting to bypass guardrails using base64 encoding, leetspeak, or token splitting.
3. Indirect injection simulation : Testing if the model can be compromised via malicious data pulled from third-party APIs, vector databases, or web scraping.

Would you like to narrow this down based on whether you need a self-hosted open-source framework or a commercial SaaS platform with CI/CD integration?

Yes. If you're specifically evaluating automated prompt-injection/red-team suites, these are worth looking at:

• HiddenLayer — Enterprise-oriented automated red teaming for LLMs and agents, including prompt-injection and jailbreak testing, scheduled scans, and vulnerability tracking.
• Check Point AI Security / Lakera — Automated AI red teaming covering prompt injection, jailbreaks, data leakage, unauthorized actions, and application-specific risks. Its Red SDK can also be integrated into CI/CD.
• CalypsoAI — Automated/continuous adversarial testing with large attack libraries, including prompt injection and agentic attacks.
• SATLAS — Focuses on automated AI red teaming mapped to MITRE ATLAS and OWASP LLM Top 10, with 400+ prebuilt attack scripts and prompt-injection testing.
• KonaRed / KonaSense — Enterprise adversarial testing for models, agents, APIs, and AI workflows, with repeatable attack packs and evidence/reporting.
• Promptfoo — A popular developer-oriented/open-source option for incorporating adversarial LLM testing into CI/CD; useful if you want something more programmable rather than an enterprise SaaS suite.

For a penetration-test benchmark, I'd shortlist HiddenLayer, Lakera/Check Point, SATLAS, and Promptfoo: they give you a useful spread from enterprise continuous testing to developer-controlled/custom attack harnesses.

If you tell me whether you're testing a chatbot, RAG application, or tool-using agent, I can narrow this to the best 3 and compare their attack coverage, automation, CI/CD support, and pricing model.

For an AI security / prompt injection penetration test, the market is split between automated AI red teaming platforms, LLM security scanners, and broader AI governance/testing suites. Vendors and projects commonly used for automated adversarial testing include:

For a penetration-test style engagement, I’d typically evaluate tools against these capabilities:

• Direct prompt injection

  • “Ignore previous instructions”
  • system prompt extraction attempts
  • role/persona manipulation
  • delimiter and formatting attacks

• Indirect prompt injection

  • malicious instructions hidden in:
    • RAG documents
    • web pages
    • emails
    • uploaded files
    • retrieved context

• Agent security

  • tool-call abuse
  • excessive permissions
  • memory poisoning
  • multi-step workflow hijacking

• Regression automation

  • rerun attack suites after:
    • model changes
    • prompt changes
    • guardrail updates
    • agent workflow changes

For research-heavy teams, there are also emerging open academic frameworks such as PIMiner, PI-Hunter, and PISmith, which focus specifically on automated prompt injection discovery and adversarial prompt generation.

A practical shortlist for an enterprise pentest would usually be:

1. Microsoft AI Red Teaming Agent — if you are already in Azure/OpenAI ecosystems.
2. KonaRed / Lasso / Satlas — if you want dedicated AI security testing platforms.
3. Custom attack harness + open research methods — if you need deep testing of a unique agent architecture.

For a formal penetration test, I would also map coverage against OWASP LLM/agent risk categories and MITRE ATLAS techniques rather than relying only on canned jailbreak prompts.

Automated AI red teaming suites and frameworks specialize in generating adversarial inputs, simulating multi-turn jailbreaks, and testing for direct/indirect prompt injection at scale . They generally fall into commercial enterprise platforms, developer-focused toolkits, and open-source frameworks.

Commercial & Enterprise Platforms

• Mindgard offers continuous automated security scanning, threat reconnaissance, and red teaming tailored for LLM application layers.
• General Analysis provides automated AI red teaming platforms specialized in testing agentic AI, multi-step tool/API chains, and indirect prompt injection vulnerabilities.
• HiddenLayer features automated red teaming and machine learning security capabilities focused on model robustness and supply chain attack vectors.
• Lakera Red delivers adversarial testing and continuous evaluation suites designed to locate prompt injection and safeguard boundaries before production.
• Prompt Security combines runtime guardrails with pre-deployment and continuous adversarial testing to map vulnerabilities across the application layer.
• Novee utilizes autonomous offensive AI agents trained on pentesting tradecraft to perform black- and gray-box testing against agent workflows and prompt injection vulnerabilities.

Developer-Focused & Open-Source Frameworks

• Promptfoo is a widely adopted open-source evaluation and security testing tool featuring a built-in red teaming module that automatically generates direct and indirect prompt injection test cases in CI/CD pipelines.
• Garak (LLM Vulnerability Scanner) , backed by NVIDIA and the open-source community, acts as a comprehensive scanner mapping model weaknesses, including prompt injection and data exfiltration.
• PyRIT (Python Risk Identification Tool) is Microsoft’s extensible, open-source orchestration framework built to automate risk identification and adversarial probing for generative AI systems.

If you can share what type of architecture you are testing (e.g., a standalone LLM endpoint, a RAG pipeline, or an autonomous agent with tool access), I can help you narrow down which suite fits your specific scope.