AI agents are changing how software gets built and how work gets done. They also introduce security challenges that traditional tools weren't designed to handle. AI Security Guard exists to address that gap.
What does AI Security Guard offer?
Threat Detection API
The core of AI Security Guard is a content scanning API that detects prompt injection, credential exposure, social engineering, and other threats in text before it reaches an LLM. The API uses a 5-expert ML pipeline:
- Pattern Expert: Regex signatures and research-backed detection patterns
- Intent Expert: Classification and injection-in-data detection
- Behavior Expert: AST analysis across 8 programming languages
- Semantic Expert: Embedding similarity to known attack families
- Secrets Expert: Credential detection for AWS, GCP, OpenAI, and dozens of other services
The API processes Content DNA (statistical markers) for risk assessment without seeing original content, preserving privacy while enabling threat scoring.
AgentGuard360
AgentGuard360 is a security toolkit delivered via CLI, SDK, and pip package. It wraps the AI Security Guard API and adds local security features, including:
- Device hardening: 16-phase security audit
- Supply chain protection: Blocks 11,000+ known malicious packages
- Behavior analysis: Anomaly detection against personalized baselines
- Cost tracking: Monitor LLM spend with budget alerts
AgentGuard360 works for both humans and AI agents. Agents call a single setup function; humans use a CLI wizard.
Learning Center
Educational resources covering AI agent security topics — how-to guides, research articles, and threat analysis. Content is optimized for both human readers and AI agents.
AI Agent Security Action Pack
A structured resource for teams adopting AI agent security: 15 expert articles mapped to OWASP Agentic Top 10, plus 12 installable skills for Claude Code and Cursor.
Who is AI Security Guard for?
- Developers using AI coding agents: Claude Code, Cursor, Windsurf, Continue users who want visibility into what their agent is doing and protection against prompt injection
- Teams building AI agents: Anyone developing agents that process external content, install dependencies, or operate autonomously
- Security professionals: People responsible for AI adoption who need to understand and mitigate agent-specific risks
- Startups without dedicated security teams: Organizations that need protection without enterprise complexity or pricing
Why does AI agent security matter?
AI agents operate differently than traditional software:
- They execute code autonomously, often without per-action approval
- They can be manipulated through content they process (prompt injection)
- They install packages and make network requests based on context
- Their behavior during long sessions is hard to monitor
A compromised agent can exfiltrate credentials, install backdoors, or modify code in ways that aren't obvious during review. The attack surface requires purpose-built defenses.
How is AI Security Guard different?
Privacy-first
Content stays local unless you explicitly request premium analysis. Risk assessment works on statistical markers (Content DNA) and anomoyized device telemetry not your text, files or other system data.
Personalized detection
The system learns what's normal for your work. Detection calibrates against your patterns rather than generic thresholds, reducing false positives while catching genuine anomalies.
Designed for agents
Not a traditional security tool adapted for AI — built specifically for AI agent workflows from the start. Features like supply chain blocking and behavioral baselines address threats unique to autonomous agents.
