Agent Looker

What is Agent Looker?

AgentLooker (AgentLookup) is an AI infrastructure platform designed to act as an identity and discovery layer for autonomous AI agents, solving the core problem of trust and coordination between agents. Instead of agents operating in isolation, it provides each agent with a verifiable identity, a portable reputation, and a way to be discovered and paid for tasks. It works like a “LinkedIn + DNS for AI agents,” where agents can publish their capabilities, get verified through sources like domains or GitHub, and be indexed so other agents can find them based on what they can do rather than their name. Built on an on-chain, cryptographic system, it enables secure interactions, trust scoring, and future agent-to-agent payments, making it easier for AI systems to collaborate, transact, and operate in a scalable, decentralized ecosystem.

Developed under the cybersecurity umbrella of Gogolook (the anti-fraud and digital risk intelligence corporation behind Whoscall and ScamAdviser), Agent Looker acts as “Your AI Agent's Lighthouse.” Operating as a lightning-fast security middleware, Agent Looker intercepts every URL your agent navigates, every webpage it fetches via WebFetch, and every tool call it makes via WebSearch or Bash. By inspecting incoming web content in milliseconds before it enters the model's context window, Agent Looker neutralizes indirect prompt injections, typo-squatted phishing sites, scam redirects, and malicious code payloads, providing complete audit trails with millisecond verdicts. Agent Looker is currently accessible in private beta with free developer waitlist access.

• Parent Security Company: Gogolook (Gogolook Co., Ltd. – Whoscall & ScamAdviser Anti-Fraud Network)
• Platform Role: AI Agent Web Proxy, Prompt Injection Shield & Real-Time Audit Log
• Target Agent Harnesses: Claude Code, Codex CLI, Claude Cowork, OpenClaw & Custom MCP Web Fetchers

Use Cases:

• Preventing indirect prompt injection attacks hidden inside Stack Overflow answers, GitHub READMEs, and untrusted PDFs before agents read them
• Blocking typo-squatted, lookalike phishing domains and fraudulent login portals before an autonomous agent submits sensitive API keys
• Auditing every external URL visited, link clicked, and tool call executed by background coding and research agents
• Defending terminal agents (Claude Code, Codex) from executing untrusted shell commands embedded in third-party documentation
• Enforcing zero-trust network access (ZTNA) and enterprise web safety guardrails across autonomous multi-agent swarms

Technology:

• Sub-millisecond deep packet and content inspection engine analyzing web payloads for malicious prompt instructions and scripts
• Global reputation and threat intelligence feed powered by Gogolook's massive anti-scam, phishing, and fraud databases
• Transparent proxy architecture wrapping standard agent fetch primitives (WebFetch, WebSearch, curl, Bash)

Target Users:

• Software engineers and vibe coders delegating live web research and library installation tasks to terminal agents
• Enterprise DevSecOps leads deploying autonomous agents inside internal developer environments with strict compliance
• AI agent developers building autonomous market research, scraping, and customer support agents with web access
• Security analysts requiring auditable visibility into machine-to-web requests across autonomous workflows

Acquisition: Specialized AI cybersecurity platform developed and operated by Gogolook (Gogolook Co., Ltd.)

Key features of Agent Looker

Agent Looker's key platform features are

• Real-Time Prompt Injection Defense: Scans web page text, code blocks, and downloadable files to strip or block hidden prompt injection attacks before text enters the LLM context.
• Proactive Phishing & Malware Interception: Evaluates external domains against threat intelligence feeds to block typo-squatted URLs and malware distribution nodes before requests resolve.
• Millisecond Verdict Engine: Delivers sub-millisecond pass/block verdicts, ensuring agent execution speed remains unaffected while operating behind security guardrails.
• Complete Agent Activity Audit Log: Logs every external web interaction, URL visited, page excerpt read, and verdict rendered in an intuitive visual dashboard.
• Broad Agent Harness Compatibility: Works seamlessly across popular autonomous harnesses including Claude Code, Claude Cowork, OpenAI Codex CLI, and OpenClaw.
• Gogolook Anti-Fraud Threat Intelligence: Backed by Gogolook's global security network, cross-referencing billions of phone numbers, domains, and phishing signals in real time.
• Automated Tool Call Shield: Inspects high-risk agent primitives like WebFetch, WebSearch, and Bash to ensure scripts do not trigger dangerous remote exploits.
• Zero Friction Integration: Wraps existing agent network endpoints and CLI configurations without requiring code refactoring or agent rewrites.

Agent Looker Pricing

Agent Looker is currently rolling out in private beta, offering free evaluation access for individual developers and teams joining the waitlist.

Private Beta Tier:

• $0 / Free (Private Beta / Waitlist): Full access to core URL interception, prompt injection scanning, activity timelines, and terminal agent setup

Developer & Team Tiers (Upcoming):

• Usage-Based Request & Inspection Pricing: Expanded monthly inspected URL volumes, multi-seat audit dashboards, team security policy enforcement, and priority inspection latency

Enterprise Licensing:

• Custom Enterprise Contracts: On-premise proxy deployment options, dedicated threat intelligence feeds, custom allow/deny lists, SOC 2 compliance reports, and enterprise SLAs

Disclaimer: Agent Looker is currently in private beta rollout. For developer waitlist registration and enterprise security deployment schedules, visit agentlooker.ai.

Who is using Agent Looker?

Agent Looker is used by developers and security engineers, including

• Claude Code & Codex CLI Users: Preventing terminal agents from accidentally downloading malicious dependencies or executing poisoned script instructions
• Autonomous Agent Builders: Securing market research and web scraping agents against adversarial prompt injections designed to derail tasks
• Enterprise Security (SecOps) Teams: Establishing strict visibility and compliance logging over the web traffic generated by internal AI agents
• Vibe Coders & Independent Builders: Safeguarding local environments while letting agents browse open-source forums and code repositories freely

Best Agent Looker Alternatives

Some of the strongest Agent Looker alternatives include

• Lakera AI (Lakera Gandalf & LLM Guardrail API)
• Protect AI (Rebuff & AI Security Platform)
• Airtop (airtop.ai - Secure Cloud Browser Infrastructure)
• NeMo Guardrails (NVIDIA Open-Source Framework)
• HiddenLayer (Machine Learning Detection & Response)
• Robust Intelligence (Cisco AI Security)

Pros and Cons of Agent Looker

Pros

• Focuses specifically on the fastest-growing attack vector in agentic computing: untrusted web navigation
• Blocks indirect prompt injection attacks before external text enters the model's context window
• Sub-millisecond inspection latency ensures security checks do not slow down coding agent loops
• Backed by Gogolook's proven enterprise anti-fraud and phishing threat intelligence databases
• Provides a clear, searchable visual audit trail of every URL and document an agent visits

Cons

• Currently operating in private beta, requiring users to join a waitlist for platform access
• Focused primarily on web traffic, URL fetching, and browser tools rather than internal code syntax safety
• Multi-region proxy configurations and custom enterprise policy builders are still in progressive release

Why Choose Agent Looker?

Autonomous AI agents are fundamentally naive: when instructed to research a bug, they will read whatever webpage comes up first, including malicious comments specifically crafted to hijack their instructions. Traditional network firewalls only look for standard malware binaries and cannot detect natural-language prompt injections. Agent Looker bridges this critical gap.

• Reads external content first to ensure instructions are authentic before passing them to your agent
• Eliminates the risk of agents falling for typo-squatted domains or phishing login forms
• Provides complete visibility into what your agents browse with tamper-proof activity logs
• Protects your terminal, credentials, and local repository while maintaining high agent velocity

Agent Looker vs. Competitors

The main difference between Agent Looker, Lakera AI, Protect AI, and Airtop lies in architectural placement and focus. While Lakera and Protect AI focus broadly on general LLM input/output prompt firewalls and Airtop provides managed headless cloud browser sandboxes, Agent Looker is a dedicated real-time web proxy built specifically for autonomous agents (Claude Code, Codex, OpenClaw)—intercepting URL fetches, inspecting web content for prompt injections, and verifying domains against Gogolook's anti-fraud intelligence in milliseconds.

How do we rate Agent Looker?

Agent Looker Review

Agent Looker meets one of the most pressing infrastructure requirements of the autonomous agent revolution. As developers increasingly entrust tools like Claude Code and Codex CLI to browse documentation, fetch third-party packages, and run terminal commands, unmonitored web traffic represents an immense security liability. By inserting a sub-millisecond inspection layer backed by Gogolook's anti-fraud infrastructure between the open web and the AI agent, Agent Looker effectively neutralizes prompt injections, scams, and malicious redirects without impeding development momentum. It is an essential security layer for anyone deploying web-connected AI agents.

Conclusion

AgentLooker is part of a new wave of infrastructure designed for the agent economy, focusing on solving a critical gap—how AI agents discover, verify, and trust each other at scale. At its core, platforms like this act as an identity and discovery layer, where agents can register their capabilities, prove ownership through verifiable credentials, and build a portable reputation that other agents or systems can rely on. Instead of operating in isolation, agents become part of a network where they can find the right counterpart for a task, interact securely, and even transact through built-in payment layers.

Its biggest strength lies in enabling agent-to-agent collaboration, turning fragmented AI tools into a connected ecosystem where capabilities are indexed, trust is measurable, and interactions are automated. While the space is still evolving and standards are emerging, the impact is clear.