PipeLab Pipelock
Security proxy that inspects and enforces policy on AI agent network traffic.
PipeLab Pipelock
Security proxy that inspects and enforces policy on AI agent network traffic.
Data verified Jun 2026
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Agentic AI Security
MCP Security
Prompt Injection
AI DLP
LLM Security
Proxy
Data Exfiltration
Websocket
MITRE Attack
LLM Guardrails
Pipelock is a security proxy designed to sit between AI agents and the network, providing traffic inspection, enforcement, and audit capabilities for agentic AI workloads. Architecture: - Acts as a capability-separated enforcement boundary: the agent holds secrets, Pipelock holds network access - Supports Fetch Proxy, Forward Proxy (HTTPS_PROXY/CONNECT), and WebSocket Proxy modes - 11-layer scanner pipeline covering HTTP, WebSocket, and MCP traffic Detection Capabilities: - Data Loss Prevention: 48 credential patterns (API keys, tokens, financial data, crypto keys) with checksum validators to reduce false positives; handles base64, hex, URL-encoding, and Unicode evasion - Response Scanning: 25 prompt injection detection patterns with normalization passes for obfuscated payloads (zero-width chars, homoglyphs, leetspeak) - A2A Protocol Scanning: Inspects Google Agent-to-Agent protocol messages for injection and DLP violations - Media Policy: Blocks audio/video by default, strips EXIF/XMP/IPTC metadata, hardens SVG content - Canary Tokens: Synthetic credentials planted to detect exfiltration attempts - Cross-Transport DLP: Scans URLs, headers, request bodies, WebSocket frames, and MCP tool arguments; detects secrets split across requests via entropy tracking - Tool Chain Detection: Subsequence matching on MCP tool call sequences with 10 built-in attack patterns Enforcement Capabilities: - Kill Switch: Four independent activation sources with port isolation - Adaptive Enforcement: Per-session threat scoring with three escalation levels and auto de-escalation - Process Sandbox: OS-level containment using Linux Landlock/seccomp or macOS sandbox-exec - MCP Tool Policy: Pre-execution allow/deny/redirect rules with 17 built-in patterns - Session Binding: SHA256 baseline tracking for MCP tool definitions to detect mid-session rug-pulls - Learn-and-Lock Contracts: Behavioral contract compilation from observed traffic - Denial-of-Wallet Detection: Loop detection, retry storms, fan-out explosions, concurrent tool limits - MCP Binary Integrity: Pre-spawn hash verification for MCP subprocess servers Audit and Compliance: - Flight Recorder: Hash-chained, tamper-evident audit log with Ed25519 signatures - Signed Assessments: Reproducible evidence bundles with HTML/JSON reports - Compliance mappings: OWASP MCP Top 10, MITRE ATLAS, MITRE ATT&CK, EU AI Act, SOC 2, NIST 800-53, SARIF v2.1.0 - Agent Bill of Materials: CycloneDX 1.6 runtime inventory - Attack Simulation: 24 built-in attack scenarios via pipelock simulate - Config Security Scoring: 0-100 score across 12 security categories
PipeLab Pipelock FAQ
Common questions about PipeLab Pipelock including features, pricing, alternatives, and user reviews.
PipeLab Pipelock is Security proxy that inspects and enforces policy on AI agent network traffic, developed by PipeLab. It is a Security for AI solution designed to help security teams with Agentic AI Security, MCP Security, Prompt Injection.
PipeLab Pipelock offers the following core capabilities:
1.11-layer scanner pipeline for HTTP, WebSocket, and MCP traffic
2.Data Loss Prevention with 48 credential patterns and checksum validators
3.Prompt injection and response scanning with obfuscation normalization
4.MCP Tool Policy with pre-execution allow/deny/redirect rules
5.Adaptive per-session threat scoring with automatic escalation
6.Hash-chained tamper-evident audit log with Ed25519 signatures
7.Process sandboxing via Linux Landlock/seccomp or macOS sandbox-exec
8.Learn-and-Lock behavioral contract compilation from observed agent traffic
9.Attack simulation with 24 built-in scenarios and CI JSON output
10.Agent Bill of Materials using CycloneDX 1.6 runtime inventory
PipeLab Pipelock integrates natively with Grafana, Prometheus, GitHub Code Scanning (SARIF v2.1.0), Google A2A (Agent-to-Agent) protocol, Telegram (kill switch). Integration support lets security teams connect PipeLab Pipelock to existing SIEM, ticketing, identity, and notification systems without custom development.
PipeLab Pipelock is built for security teams handling Agentic AI Security, MCP Security, Prompt Injection, AI DLP. It supports workflows including 11-layer scanner pipeline for http, websocket, and mcp traffic, data loss prevention with 48 credential patterns and checksum validators, prompt injection and response scanning with obfuscation normalization. Teams typically adopt PipeLab Pipelock when they need to security for ai capabilities integrated into their existing stack. Explore similar tools at https://cybersectools.com/alternatives/pipelab-pipelock
PipeLab Pipelock is a commercial Security for AI solution. For detailed pricing information, visit https://pipelab.org/pipelock/ or contact PipeLab directly.
Popular alternatives to PipeLab Pipelock include:
1.Archestra Enterprise MCP Platform - Enterprise platform for securing, governing, and orchestrating MCP servers and AI agents. (Commercial)
2.CodeIntegrity AARM Platform - Runtime control plane that mediates & governs AI agent actions before execution. (Commercial)
3.Certiv - Runtime security platform for discovering, monitoring, and controlling AI agents. (Commercial)
4.General Analysis AIDR - Monitors & responds to AI agent risks at the execution layer. (Commercial)
5.Highflame Platform - AI agent security platform with guardrails, governance, and observability. (Commercial)
Compare all PipeLab Pipelock alternatives at https://cybersectools.com/alternatives/pipelab-pipelock
PipeLab Pipelock is for security teams and organizations that need Agentic AI Security, MCP Security, Prompt Injection, AI DLP, LLM Security. It's particularly suitable for enterprises requiring robust, commercial-grade security capabilities. Other Security for AI tools can be found at https://cybersectools.com/categories/ai-security
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