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Use Case

AI Red Teaming

Effectively test your AI systems against threats with automated adversarial attacks mapped to MITRE ATT&CK and MITRE ATLAS.
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Challenge

Cloud AI workloads are vulnerable to several attacks, including prompt injection, data poisoning, LLMJacking, guardrail evasion, and agent goal hijacking. These attacks often degrade the end-user experience, and traditional red teaming is not effective against AI-specific threats.

How Mitigant Helps

Mitigant provides a suite of adversarial attacks for safely testing several Bedrock components, including Agents, Knowledge Bases, Guardrails, Prompt Management, and AgentCore. These attacks empower security teams to detect and remediate AI weaknesses effectively.
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Customer Outcomes

Security teams using Mitigant move from assuming Bedrock is secure to proving it, with controls validated against actual attacks rather than left to theory. The ease of execution and automated analysis allow organizations to continuously reduce AI security risks without waiting months for external red-team consultants.

Challenge

Cloud AI workloads are vulnerable to several attacks, including prompt injection, data poisoning, LLMJacking, guardrail evasion, and agent goal hijacking. These attacks often degrade the end-user experience, and traditional red teaming is not effective against AI-specific threats.

How Mitigant Helps

Mitigant provides a suite of adversarial attacks for safely testing several Bedrock components, including Agents, Knowledge Bases, Guardrails, Prompt Management, and AgentCore. These attacks empower security teams to detect and remediate AI weaknesses effectively.
Read More

Customer Outcomes

Security teams using Mitigant move from assuming Bedrock is secure to proving it, with controls validated against actual attacks rather than left to theory. The ease of execution and automated analysis allow organizations to continuously reduce AI security risks without waiting months for external red-team consultants.

Why Mitigant AI Red Teaming

Key capabilities for safely testing Amazon Bedrock workloads against real-world AI threats.

Comprehensive Bedrock Coverage

Test the full Amazon Bedrock attack surface: Agents, Knowledge Bases, Guardrails, Prompt Management, AgentCore, plus the identity and logging layers around them.

Aligned With AI Frameworks

Every attack maps to MITRE ATT&CK, MITRE ATLAS, the CSA Agentic AI Red Teaming Guide, and the OWASP LLM Top 10. Aligning with these frameworks is simplified, and newer versions are quickly implemented.

Continuous AI Red Teaming

Schedule red teaming exercises to run on a cadence, nightly, weekly, or after every deployment. Catch new exposures the moment they appear, not when the next quarterly assessment comes due.

Attack Builder

Build custom AI red teaming scenarios in minutes without scripting. Model threats specific to your Bedrock workloads where our attack library doesn't cover or where there is a need for custom attacks. Read more here

Production-Safe Execution

Safely execute controlled attacks with bounded scope and automated cleanup after every run. Every step is reversible, with you in full control of what runs and when.

Detailed Reporting

Receive detailed attack reports with comprehensive analysis, MITRE-mapped findings, and remediation guidance. Use the provided attack graph for deeper insights and proactive planning.

Frequently Asked Questions

Why Do Organizations Need AI Red Teaming?

AI workloads introduce attack surfaces that traditional security tools don't cover: prompt injection, knowledge base poisoning, guardrail evasion, LLMJacking, and agent goal hijacking. These threats can cause real harm to users through malicious or incorrect AI output, which cannot be detected via posture scanning. AI Red Teaming validates that your AI controls actually hold up against realistic adversarial pressure. Read more →

What AI Workloads Does Mitigant Cover Today?

Mitigant comprehensively covers Amazon Bedrock, including Agents, Knowledge Bases, Guardrails, Prompt Management, AgentCore, and the identity and logging layers around them.

How Is This Different From Application Layer AI Red Teaming Tools?

Application-layer AI red-team tools test models pre-deployment: prompt-injection scanners, jailbreak generators, and content-filter probes. Furthermore, the tests end at the application layer and do not span to the infrastructure layer and runtime posture. Mitigant operates at the cloud infrastructure layer, validating IAM, logging, knowledge bases, agents, guardrails, and AgentCore for your deployed Bedrock workloads.

How Is This Different From AISPM Tools?

AISPM (AI Security Posture Management) tools scan AI configurations and surface misconfigurations, such as overly permissive identities on Bedrock resources, exposed knowledge base sources, and missing guardrails. AI Red Teaming goes further by validating which of those gaps are actually exploitable, executing real attacks against the deployed AI workload. AISPM tells you what looks wrong; Mitigant proves what an attacker can actually do. Mitigant CSPM (https://mitigant.io/en/platform/cloud-security-posture-management) also has some AISPM capabilities.

Is This Safe To Run Against Production Bedrock Workloads?

Yes, every attack runs within a bounded scope with automated cleanup after the run, and you control which scenarios run and when.

Which Frameworks Does Mitigant Align With?

Every Mitigant AI red teaming attack maps to MITRE ATT&CK, MITRE ATLAS, the CSA Agentic AI Red Teaming Guide, and the OWASP LLM Top 10. Results are portable across compliance reviews, threat models, and security architecture discussions.

Featured Resources

View All Blogs
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Effective Red Teaming in the Agentic Era: Amazon Bedrock (Part I)
May 17, 2026
AI Red Teaming plays a central role in AI quality of service, ensuring end users are not harmed or frustrated by malicious output. This article provides practical AI Red Teaming guidance for Amazon Bedrock.
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Bedrock or Bedsand: Attacking Amazon Bedrock’s Achilles Heel
July 10, 2024
Amazon Bedrock's Achilles heel is the adoption of S3 as a RAG data source, leading to several GenAI attack vectors, including data poisoning, denial of service & S3 ransomware. This article delves into these attack vectors, detection, and mitigation.
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Demystifying Amazon Bedrock LLMJacking Attacks
October 13, 2024
LLMJacking attacks are increasingly targeting GenAI workloads on Amazon Bedrock. Cybercriminals illegally gain access to Large Language Models during LLMJacking attacks and resell this access via chatbots for profit.
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See Mitigant Cloud Pentesting in Action

Watch how we validate exploitability and provide evidence-based remediation in under 90 seconds.

Why Mitigant Cloud Pentesting

Key capabilities that differentiate Mitigant from traditional penetration testing and CSPM/CNAPP.

250+ Attacks

Execute real-world cloud attack techniques mapped to MITRE ATT&CK and ATLAS frameworks across AWS and Azure.

Exploitability Validation

Prove which CSPM findings are actually exploitable. Get evidence-based validations, not just theoritical findings with severity scores.

Attack Builder

Create custom penetration testing scenarios in minutes without scripting. Model your specific threat landscape if not already covered in our attack library.

AI-Powered Attack Analytics

AI models are leveraged for intelligent attack analytics to provide contextual, actionable insights including impact, risks and appropriate countermeasures and remediation.

On-Demand Execution

Launch pentests before deployments, after changes, or continuously. No waiting for external consultants. Run your security strategy without any hindrances.

Compliance Ready

Generate detailed pentest report mapped to compliance frameworks including ISO 27001, DORA, SOC 2, PCI DSS, CIS, NIS2 etc

Frequently Asked Questions

Does this replace manual penetration testing?

Yes for routine validation, but annual deep-dive manual pentests still provide value for comprehensive assessments. Mitigant eliminates the need for quarterly external cloud pentests while maintaining continuous security validation. We also offer a combination of human-led and automated with our partners if required.

Is this safe to run in production environments?

Yes. Mitigant uses read-only operations by default with safe modes for production. All attack scenarios validate exploitability without causing service disruption. You control which attacks run and when.

How is this different from CSPM/CNAPP tools like Wiz or Orca?

CSPM/CNAPP tools scan for misconfigurations but can't prove exploitability. Mitigant validates which findings are actually exploitable by executing real attack scenarios, eliminating false positives. Think: posture assessments finds issues, Mitigant proves which ones attackers can exploit (posture validation)

How quickly can we get started?

Most customers run their first attack scenarios within 30 minutes. Setup requires only read-only cloud permissions. No agents, no code changes, no infrastructure modifications.

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