Documents
ROADMAP
ROADMAP
Type
External
Status
Published
Created
Mar 25, 2026
Updated
Mar 30, 2026
Updated by
Dosu Bot

Roadmap#

High-level direction for Pipelock development. Priorities shift based on customer feedback, enterprise requirements, and the evolving AI agent security landscape.

Shipped (v2.1)#

New capabilities added since v2.0:

Evidence and Compliance

  • Flight recorder: hash-chained, tamper-evident JSONL evidence log with Ed25519 signed checkpoints and X25519 encrypted raw escrow
  • Agent Bill of Materials (AgBOM): CycloneDX 1.6 runtime inventory with declared vs observed views
  • Session manifest and signed decision records: per-verdict Ed25519 signing with unified session substrate
  • Compliance evidence: OWASP MCP Top 10, OWASP Agentic Top 10, MITRE ATLAS, EU AI Act, SOC 2 coverage mappings
  • Trust attestation: Ed25519-signed assessment results with SVG badge generation

Detection and Prevention

  • Canary tokens: synthetic secrets for irrefutable compromise detection with zero false positives
  • A2A protocol scanning: Agent Card drift detection, session smuggling, field-level content inspection
  • MCP binary integrity: pre-spawn SHA-256 hash verification with shebang and versioned interpreter parsing
  • Denial-of-wallet detection: loop detection, retry storm detection, fan-out tracking
  • Scanner hardening: improved encoded payload coverage and cross-transport DLP
  • Response scanning exempt_domains: per-domain exemption from injection scanning

Assessment and Simulation

  • pipelock assess: four-stage self-serve security assessment with HTML report, secret redaction, and remediation guidance
  • pipelock simulate: expanded to 54+ attack scenarios (up from 24) across 6 categories

Operational

  • Session admin API: GET/POST endpoints for adaptive enforcement recovery, identity-family scoping
  • MCP redirect handlers: built-in fetch-proxy and quarantine-write profiles
  • Autonomous block_all recovery for adaptive enforcement
  • Trusted domains for forward proxy SSRF exemption
  • SecureIQLab Docker Compose test harness

Developer Experience

  • CLI split into 10 focused subpackages (from monolithic 91-file package)
  • MCPProxyOpts pattern for cleaner internal APIs
  • Shared escalation recording and signal classification helpers

Shipped (v2.0)#

Core capabilities available today:

Traffic Inspection

  • 11-layer scanner pipeline across HTTP, HTTPS, WebSocket, and MCP
  • Forward proxy (CONNECT/HTTPS_PROXY), fetch proxy, reverse proxy, and Scan API modes
  • Optional TLS interception with full body, header, and response scanning
  • Generic HTTP reverse proxy with bidirectional body scanning

Data Loss Prevention

  • 46 credential and secret patterns with encoding-aware matching (base64, hex, URL, Unicode)
  • Environment variable leak detection
  • BIP-39 seed phrase detection with checksum validation
  • Blockchain address poisoning protection (ETH, BTC, SOL, BNB)

Prompt Injection Defense

  • 6-pass normalization pipeline covering zero-width characters, homoglyphs, leetspeak, and encoded payloads
  • 23 response scanning patterns including state manipulation, control flow hijacking, and CJK-language overrides
  • Full-schema tool poisoning detection (recursive inputSchema scanning)

MCP Security

  • Bidirectional scanning for stdio, Streamable HTTP, and HTTP reverse proxy
  • Tool description poisoning detection with rug-pull drift tracking
  • Pre-execution tool policy engine with redirect action (17 built-in rules)
  • Tool call chain detection (10 built-in attack patterns)
  • Session binding and behavioral profiling

Process Sandbox

  • Linux: Landlock filesystem restriction + seccomp syscall filtering + network namespace isolation
  • macOS: sandbox-exec with dynamically generated SBPL profiles
  • Per-agent profiles with strict mode, diagnostics, and preflight checks

Operational Controls

  • OR-composed kill switch (config, signal, sentinel file, remote API)
  • Structured audit logging with MITRE ATT&CK technique IDs
  • Webhook, syslog, OTLP, and Prometheus emission (45 metric families)
  • Grafana dashboard for fleet monitoring
  • HTML/JSON audit reports with Ed25519 signing
  • Config security scoring (pipelock audit score)

Developer Experience

  • IDE integration for Claude Code, Cursor, VS Code, and JetBrains/Junie
  • Preset configs for common agent frameworks
  • pipelock diagnose for config and sandbox validation
  • pipelock audit for project security assessment
  • Git diff scanning for pre-commit secret detection
  • Community rule bundles (signed YAML detection patterns)

Supply Chain

  • Single static binary (~18 MB), 17 direct dependencies
  • Cosign-signed releases, CycloneDX SBOM, SLSA v1.0 provenance
  • OpenSSF Best Practices Silver, published OWASP and NIST 800-53 coverage mappings

Shipped (v2.1)#

  • Cross-request exfiltration detection: entropy budgets, fragment reassembly, multi-turn data staging
  • Financial DLP: blockchain address poisoning protection (ETH, BTC, SOL, BNB) and BIP-39 seed phrase detection
  • Agent process management: pipelock run with sandbox enforcement (Landlock, seccomp, macOS sandbox-exec)
  • Security assessment reports: pipelock assess with HTML/JSON output, Ed25519 signing, and config scoring
  • Tool policy redirect: steer matched tool calls to audited handler programs instead of blocking
  • Profile-then-lock: learned tool baselines from observed behavior, session binding enforcement
  • Behavioral analytics: session profiling, adaptive enforcement escalation, cross-request entropy anomaly detection
  • A2A protocol scanning: Agent Card validation, agent-to-agent header and body scanning

Near-Term#

  • Kubernetes sidecar Helm chart for simplified deployment
  • Multi-agent policy coordination and inter-agent traffic controls
  • Expanded compliance evidence generation (NIST AI RMF, EU AI Act mapping)

Medium-Term#

  • Centralized policy management for multi-team deployments
  • Fleet-wide dashboard and management plane
  • SOC 2 and regulatory compliance report generation

Out of Scope#

These are explicitly not goals:

  • Model training or fine-tuning security
  • Data governance or dataset management
  • Full-lifecycle AI management platforms
  • Replacing network firewalls or endpoint protection
  • Container runtime management (Docker, K8s orchestration)

Feedback#

Feature requests and use case discussions are welcome in GitHub Issues.