Find security weaknesses in your AI agents before attackers do.
Test your AI agents against real-world attack scenarios. Discover vulnerabilities, identify unsafe behavior, and generate actionable security reports before deployment.
Designed for teams building and securing autonomous AI-powered applications.
Multi-Turn Adversarial Red Team Scan • 10 Attack Vectors Evaluated
Payload in prompt coerced agent to invoke execute_sql("; DROP TABLE ledger;").
Agent tool attempted AWS instance credential siphoning. Caught and isolated in turn 3.
Agent correctly executed compliant refusal on hypothetical framing probe.
Autonomous agents introduce
critical new attack surfaces.
As AI agents transition from simple chatbots to autonomous systems executing actions across your infrastructure, conventional application firewalls are not enough.
Tool Abuse & Excessive Agency
When autonomous agents are given access to databases, APIs, or command shells, attackers can manipulate them into executing destructive queries, siphoning credentials, or making unauthorized transfers.
Direct & Indirect Prompt Injection
Attackers hide malicious instructions in user queries, uploaded files, or external web data. These injected payloads hijack agent reasoning, bypass guardrails, and exfiltrate sensitive data.
The Regression & CI/CD Blindspot
Model fine-tuning, system prompt updates, and tool schema modifications frequently introduce silent security vulnerabilities without automated regression gating prior to production deployment.
How SecureMID Works
A simple, four-step adversarial testing workflow from agent connection to actionable remediation reports.
Zero-Code Agent Ingestion
Provide your target REST, WebSocket, or local Python wrapper endpoint. SecureMID auto-probes latency, payload schemas, and session memory boundaries without modifying agent source code.
> target_url: "https://agent-staging.internal:9000/v1/chat"
> auth_type: "Bearer token" [VALIDATED]
> connectivity_latency: 1.24 ms
> schema_detection: OpenAI ChatCompletions Compatible
> status: ASSET_READY_FOR_EVALUATION
What SecureMID Tests
Test your AI agents against real-world adversarial attack vectors before adversaries exploit them in production.
Prompt Injection
Malicious instructions that manipulate AI agents.
Direct user prompts or indirect document contexts designed to override system instructions and hijack agent behavior.
Jailbreak Attacks
Attempts to bypass AI safety restrictions.
Multi-turn conversational roleplay, adversarial encoding, and crescendo probes engineered to circumvent model guardrails.
Tool Abuse
AI agents performing unauthorized actions through connected tools.
Coercing autonomous agents into executing destructive SQL commands, unauthorized API calls, or server-side requests (SSRF).
Sensitive Data Exposure
Exposure of confidential information and credentials.
Probing agents to leak system prompts, internal infrastructure details, API tokens, database keys, or customer PII.
Memory Security
Manipulation or unauthorized retrieval of stored agent context.
Poisoning persistent agent memory, session buffers, or vector databases to trigger delayed malicious execution.
Agent Boundary Violations
Agents exceeding authorized task scope and operating parameters.
Testing whether autonomous agents respect defined operational constraints, rate limits, and authorized user tenant domains.
Platform Capabilities
Everything your engineering and security teams need to continuously evaluate, harden, and govern autonomous AI systems.
AI Agent Red Teaming
Simulate adaptive multi-turn conversations designed to test how autonomous agents handle complex, phased manipulation over time.
Adversarial Test Execution
Execute automated test suites against prompts, tools, schemas, and system parameters across hundreds of verified threat patterns.
Evidence Collection
Capture raw prompt inputs, multi-turn trajectories, internal tool calls, and complete execution traces for thorough engineering analysis.
Vulnerability Classification
Automatically categorize and rate findings by severity, directly aligned with OWASP Top 10 for LLMs and NIST AI Risk Management standards.
Security Assessment Reports
Generate comprehensive PDF executive scorecards and structured JSON findings matrices for development teams and compliance auditors.
Remediation Recommendations
Receive specific, actionable schema validation rules, boundary constraints, and prompt defense fixes to resolve identified vulnerabilities.
Retesting After Fixes
Re-run targeted security tests against confirmed findings with one click to verify that patches successfully close vulnerabilities.
CLI/API & CI/CD Gating
Integrate securemid-cli into GitHub Actions and CI/CD pipelines to block releases when high-severity agent weaknesses are detected.
Ready to test your AI agents in staging?
Connect an HTTP or WebSocket agent endpoint in minutes or request a customized guided demo.
See SecureMID in action.
Take a complete guided tour of our automated multi-turn adversarial red teaming workflow, real-time safety judges, and audit-ready CISO reports.
Start our fully featured free community tier or request an enterprise pilot with custom security invariants.
Engineered for privacy, data protection, and trust.
SecureMID evaluates safety invariants with privacy-conscious evaluation engines, strict tenant isolation, and cryptographic audit logging.
Local Evaluation & Zero Cloud Egress
Evaluate safety assertions without leaking intellectual property. Local in-process judge adapters ensure test prompts and model outputs are scored without relaying sensitive data to public cloud APIs.
Multi-Tenant Partition Isolation
Strict database-level organization boundaries prevent cross-tenant data leakage. Agent endpoints, test configurations, and vulnerability findings remain securely partitioned.
Tamper-Evident Audit Ledgers
Every evaluated attack trace, safety invariant outcome, and finding status mutation is fingerprinted with SHA-256 hashing to guarantee an immutable, verifiable compliance audit trail.
Who Uses SecureMID
From fast-moving AI product teams to enterprise security organizations, SecureMID provides the rigorous adversarial testing required to build and deploy trustworthy AI agents.
AI Startups
Ship AI agents fast without risking customer trust or critical data leaks.
Move quickly with automated adversarial checks that detect prompt injection and unsafe tool usage before you deploy to your first enterprise customers.
SaaS Companies
Protect multi-tenant AI integrations and external tool connectors.
Ensure autonomous agents with access to customer databases, search indexes, or external APIs cannot be manipulated into cross-tenant data leaks or unauthorized actions.
AI Development Teams
Automate security testing directly in your Git pull request workflows.
Treat security as code. Automatically run targeted regression suites against agent endpoints whenever prompt templates, schemas, or system models are updated.
Enterprise Security Teams
Continuous governance aligned with OWASP Top 10 and NIST AI RMF.
Replace slow, expensive periodic penetration tests with continuous, empirical security evaluations, complete with executive compliance scorecards and cryptographic audit logs.
Know where your AI agents stand before attackers find out.
Discover security weaknesses, validate your defenses, and build more secure AI applications with SecureMID.