Security for AI & Agents
Comprehensive security for foundation models, autonomous agents, and enterprise AI workflows.
Secures LLM applications against prompt injections, tool privilege escalation, and sensitive data leakage.
Deploying LLMs and autonomous agents opens fundamentally new attack surfaces: indirect prompt injections via untrusted inputs, tool privilege escalation, context boundary breaking, and accidental data exposure.
Supradim provides an AI-native runtime guardrail and dynamic red-teaming platform that evaluates model inputs, orchestrates multi-step threat modeling across agent tool chains, and enforces real-time trust boundary verification.
| Evaluation Vector | Severity | Status |
|---|---|---|
| Indirect Prompt Injection | HIGH | Blocked |
| Agent Tool Privilege Escalation | HIGH | Blocked |
| Sensitive PII / Credential Leak | MED | Testing |
| Context Boundary Escape | MED | Blocked |
Key Capabilities & Deep Dive
Indirect & Direct Prompt Injection Defense
High-speed semantic filtering and intent classification preventing malicious instruction hijacking.
- Real-time token-level heuristic analysis of user prompts and third-party content
- Resistance against multi-modal, multilingual, and obfuscated adversarial jailbreaks
- Zero noticeable latency penalty on production inference streams
Agent Tool & MCP Trust Boundary Enforcement
Monitors autonomous tool invocations (database queries, shell executions, API calls) against least-privilege policies.
- Tool execution policy enforcement blocking unauthorized command execution
- Validation of tool arguments against malicious parameter injections
- Context confinement preventing recursive agent privilege escalations
Data Loss Prevention (DLP) & Privacy Guard
Inspects both input context and generated output streams for sensitive credentials, PII, and intellectual property.
- Automatic anonymization and token masking of PII, API secrets, and source code
- Hallucination and toxic content policy enforcement
- Comprehensive audit logs fulfilling enterprise compliance obligations
How the System Works
Inbound Semantic Verification
Analyzes user prompts, document chunks, and retrieved knowledge for injection signatures.
Agent Reasoning & Tool Interception
Interposes before every tool invocation to verify permissions, argument safety, and context boundary integrity.
Outbound Data & Policy Inspection
Scans streaming model outputs in real time to redact leaked credentials, proprietary code, or inappropriate text.
Continuous Adversarial Red-Teaming
Runs continuous synthetic red-team attacks against your agents to discover emergent vulnerabilities before release.
Technical Specifications
Runtime & Integration
Risk Coverage
Frequently Asked Questions
Q: How does Supradim prevent indirect prompt injection from third-party documents?
When an agent ingests external documents or web search results, our dual-layer classifier isolates data channels from instruction channels, tagging retrieved content with integrity metadata to prevent the LLM from executing embedded commands.
Q: Will this add latency to our real-time streaming chat application?
Our lightweight neural classifiers and token analyzers are optimized for edge inference, adding sub-15ms overhead to initial tokens while evaluating stream chunks asynchronously.
AI Pentesting & Autonomous Exploit Platform
State-of-the-art AI pentesting that autonomously maps attack surfaces, reasons through multi-step logic flaws, and provides verified proof-of-concepts.
004AI Honeypot & Agent Deception System
An intelligent AI honeypot deploying high-fidelity synthetic decoys to intercept automated bots, reverse attack TTPs, and drain LLM tokens with 0% false positives.
002Intelligent Code Security Review
Tracks true data flows and cross-file call hierarchies to deliver validated fixes directly into Pull Requests.