Start with the task you need to solve
AI Agent Security
Map the boundaries across user input, retrieval, tools, memory, and model output.
Tool Call Validation
Keep model-proposed actions behind least privilege, validation, and approval gates.
RAG Security
Treat retrieved text as untrusted context until your application and policy say otherwise.
Browser Agent Security
Keep web pages, DOM content, and browser actions from becoming an unsafe authority path.
LLM Output Validation
Validate the model’s final response before it reaches a user, a tool, or storage.
AI Memory Security
Stop poisoned summaries or saved context from becoming a persistent attack path.
MCP Security
Connect MCP servers with server scoping, tool review, and runtime controls in place.
AI Agent Red Teaming
Test prompt injection, tool abuse, retrieval poisoning, and memory failures before they reach production.
Use the guardrail references when you need the threat model
Prompt Injection Prevention
Start with Anthale’s core prompt injection control model.
Advanced Prompt Injection Paths
Expand beyond direct prompt attacks into memory, tool, MCP, and multimodal paths.
Prompt Injection Obfuscation
See how encoding, wrappers, and fragmented payloads hide attacker intent.
Map Prompt Injection Attack Surfaces
Find the boundaries where untrusted text reaches model context.
Prompt Injection Impact Paths
Classify what an injection enables after it lands.
Data Exfiltration Patterns
Classify recurring leak attempts across model output, links, and tool-assisted retrieval.
Apply this in Anthale
- Create a first policy when you want to turn one of these security tasks into a working Anthale enforcement path.
- See the enforcement API when you need the exact runtime contract, authentication details, and error behavior.
- Request access when you want to review a live workflow with Anthale in place.
Suggested paths
- Building a tool-using agent: start with Secure Agent Workflows, then Gate Tool Actions.
- Hardening a retrieval flow: start with Secure Retrieval Pipelines, then Validate Model Output.
- Hardening a browser-driven workflow: start with Secure Browser Agents, then Gate Tool Actions.
- Connecting AI clients and external servers: start with Secure MCP Integrations, then Log Security Events.
- Building a security review loop: start with Red-Team Agent Workflows, then Log Security Events.
- Reviewing implementation quality: start with Review AI Security in Code, then Red-Team Agent Workflows.