HiddenLayer AISec Platform 2.0
https://www.hiddenlayer.com/platform
Targets the supply-chain / lineage layer rather than runtime memory writes. Model Genealogy tracks training/fine-tuning/modification history — catches poisoning baked in during training. AIBOM generates auditable inventory of model components + datasets. Runtime layer also monitors agentic workflows.
At a glance
- Type
- Model Genealogy + AIBOM (supply-chain layer)
- Tier
- T1
- Created
- 2022-03 (founded March 2022; emerged from stealth July 2022 with $6M seed; Series A $50M Sep 2023)
- Latest release
- not applicable — not OSS
- License
- not applicable — not OSS
- GitHub
- not applicable — no GitHub repo
- Pricing
- enterprise pricing; contact sales; no public pricing
- Funding
- $56M total ($6M seed Ten Eleven Ventures Jul 2022; $50M Series A M12+Moore Strategic Sep 2023)
Taxonomy
- storage
- n/a
- retrieval
- n/a
- persistence
- long-term
- update
- read-only
- unit
- model
- governance
- auditable
- conflict
- n/a
When to use
Optimised for: governance + compliance + audit + adversarial hardening
Anti-fit: not for hobbyist / non-production use cases
Pros & cons
Pros
Strong on adversarial ML threats (model evasion, training-data poisoning) extending into memory poisoning at runtime.
Cons
Broad ML-security positioning means memory specifically isn't the focus; pricing is enterprise-tier.
Claims & capabilities
Model-agnostic and agentless — no access to weights or training data required.
Technical surface
- API surface
- REST (typical SaaS REST + first-party SDK pattern; see vendor docs for language coverage)
- Backend storage
- custom
- Deployment
- SaaS cloud or on-prem enterprise; agentless; no weights or training data access needed
- Embedding model
- locked
- Multi-tenancy
- hard-isolation
- MCP
- Yes — Agentic and MCP Security use-case (Use case 04); protects agents and MCP-based systems from prompt injection / unsafe tool use
- A2A
- no data — searched hiddenlayer.com, hiddenlayer.com/platform, docs.hiddenlayer.com; A2A protocol not advertised
- OpenTelemetry
- no data — searched hiddenlayer.com/platform, docs.hiddenlayer.com; OpenTelemetry export not advertised
Compare HiddenLayer AISec Platform 2.0 with…
Similar systems
Other memory governance, privacy & safety in the catalog, ranked by inbound references.
- Acuvity (now Proofpoint) T1
Runtime enforcement targeting memory poisoning, unauthorised execution, identity spoofing per the OWASP LLM threat list. Visibility/control over MCP servers and locally-installed AI tools — the infrastructure layer where memory is most exposed.
- Enkrypt AI T1
Applies guardrails at three points: (1) before write to vector DB, (2) before query reaches embedding model, (3) before response. Detects malicious instructions in stored memory before retrieval; scans for PII/PHI in/out. Text + image + voice modalities.
- Lakera Guard / Lakera Red T1
Screens every prompt, response, and retrieved document for indirect prompt injection — primary vector for memory poisoning. Treats memory as untrusted: anything written to or read from memory is adversarial until proven clean. Lakera Red provides "Agent Breaker" gamified red-teaming.
- Mem0 Security / OpenMemory T1
Commercial Mem0 ships SOC 2 / HIPAA, zero-trust access controls, BYOK encryption, real-time monitoring, audit logs, workspace governance as defaults. OpenMemory is the local self-hosted variant (Docker + FastAPI + Postgres + Qdrant) for privacy-first deployments.
- Microsoft Agent Governance Toolkit T2
Cross-Model Verification Kernel (CMVK) requires majority-voting agreement across multiple model calls before a memory-influenced action. Agent OS package intercepts every action (memory included) at sub-millisecond latency. MIT licensed.
- OWASP Agent Memory Guard T3
Open-source runtime defense. Enforces YAML policies on every memory read/write. SHA-256 baselines detect tampering, injection, sensitive-data leakage, protected-key modification, rapid-change anomalies. Forensic snapshots + rollback. Reference impl for OWASP ASI06 (Memory Poisoning).